Vantage RuntimeAI · Benchmarks

Model catalog

Every OpenRouter text-chat model we can benchmark — mirrored pricing, catalog metadata, and whether the Vantage team has scored benchmark sims on public scenarios. Per-scenario rankings live on Rankings.

29 models tested · 2613 scored runs · 323 in catalog · Pricing updated Aug 3, 2026

Models

Click a column header to sort the catalog.
openai/gpt-oss-20b
OpenAI: gpt-oss-20b
YesAug 25, 202620 scenarios · avg 8.1/10 · 4.0s–40s/turn · 154 runs131,072 ctx · 131,072 max out$0.030/M in · $0.130/M out · $0.000181–$0.004435/simOpenRouter
ibm-granite/granite-4.0-h-micro
IBM: Granite 4.0 Micro
YesAug 25, 202620 scenarios · avg 8.3/10 · 3.6s–41s/turn · 147 runs131,000 ctx · 131,000 max out$0.017/M in · $0.112/M out · $0.000129–$0.003170/simOpenRouter
qwen/qwen3.7-flash
Qwen: Qwen3.7 Flash
YesAug 25, 20266 scenarios · avg 8.6/10 · 17s–50s/turn · 28 runs1,000,000 ctx · 65,536 max out$0.030/M in · $0.130/M out · $0.000181–$0.004435/simOpenRouter
nex-agi/nex-n2-mini
Nex AGI: Nex-N2-Mini
YesAug 25, 20269 scenarios · avg 8.6/10 · 2.3s–38s/turn · 34 runs262,144 ctx · 262,144 max out$0.025/M in · $0.100/M out · $0.000145–$0.003553/simOpenRouter
sao10k/l3-lunaris-8b
Sao10K: Llama 3 8B Lunaris
YesAug 25, 202619 scenarios · avg 8.2/10 · 2.2s–12s/turn · 165 runs8,192 ctx · 16,384 max out$0.040/M in · $0.050/M out · $0.000155–$0.003798/simOpenRouter
anthropic/claude-sonnet-4.6
Anthropic: Claude Sonnet 4.6
YesJul 28, 20267 scenarios · avg 9.0/10 · 7.5s–22s/turn · 42 runs1,000,000 ctx · 128,000 max out$3.00/M in · $15.0/M out · $0.0195–$0.4778/simOpenRouter
anthropic/claude-opus-4.7
Anthropic: Claude Opus 4.7
YesJul 28, 20266 scenarios · avg 9.1/10 · 6.5s–18s/turn · 27 runs1,000,000 ctx · 128,000 max out$5.00/M in · $25.0/M out · $0.0325–$0.7963/simOpenRouter
meta-llama/llama-3.1-8b-instruct
Llama 3.1 8B
YesJul 28, 202620 scenarios · avg 8.3/10 · 1.5s–42s/turn · 160 runs131,072 ctx · 131,072 max out$0.050/M in · $0.080/M out · $0.000206–$0.005047/simOpenRouter
amazon/nova-micro-v1
Amazon: Nova Micro 1.0
YesJul 28, 202620 scenarios · avg 8.4/10 · 1.0s–16s/turn · 174 runs128,000 ctx · 5,120 max out$0.035/M in · $0.140/M out · $0.000203–$0.004973/simOpenRouter
openai/gpt-4.1
OpenAI: GPT-4.1
YesJul 28, 20266 scenarios · avg 8.9/10 · 2.6s–8.5s/turn · 27 runs1,047,576 ctx · 32,768 max out$2.00/M in · $8.00/M out · $0.0116–$0.2842/simOpenRouter
qwen/qwen-2.5-7b-instruct
Qwen: Qwen2.5 7B Instruct
YesJul 28, 202619 scenarios · avg 8.3/10 · 1.4s–16s/turn · 164 runs32,768 ctx · 32,768 max out$0.100/M in · $0.200/M out · $0.000440–$0.0108/simOpenRouter
qwen/qwen3-235b-a22b-2507
Qwen: Qwen3 235B A22B Instruct 2507
YesJul 14, 202611 scenarios · avg 8.0/10 · 6.5s–48s/turn · 108 runs262,144 ctx · 32,768 max out$0.149/M in · $0.598/M out · $0.000867–$0.0212/simOpenRouter
openai/gpt-oss-120b
GPT-OSS 120B
YesJul 14, 202614 scenarios · avg 8.0/10 · 3.5s–54s/turn · 136 runs131,072 ctx · 131,072 max out$0.037/M in · $0.170/M out · $0.000230–$0.005635/simOpenRouter
meta-llama/llama-4-maverick
Meta: Llama 4 Maverick
YesJul 14, 202613 scenarios · avg 8.1/10 · 2.4s–5.7m/turn · 132 runs1,048,576 ctx · 16,384 max out$0.200/M in · $0.800/M out · $0.001160–$0.0284/simOpenRouter
openai/gpt-4.1-mini
OpenAI: GPT-4.1 Mini
YesJul 14, 202611 scenarios · avg 8.1/10 · 3.5s–27s/turn · 110 runs1,047,576 ctx · 32,768 max out$0.400/M in · $1.60/M out · $0.002320–$0.0568/simOpenRouter
openai/gpt-4.1-nano
OpenAI: GPT-4.1 Nano
YesJul 14, 202613 scenarios · avg 8.1/10 · 2.0s–14s/turn · 138 runs1,047,576 ctx · 32,768 max out$0.100/M in · $0.400/M out · $0.000580–$0.0142/simOpenRouter
meta-llama/llama-3.3-70b-instruct
Meta: Llama 3.3 70B Instruct
YesJul 14, 202611 scenarios · avg 8.0/10 · 8.0s–5.8m/turn · 108 runs131,072 ctx · 128,000 max out$0.130/M in · $0.400/M out · $0.000670–$0.0164/simOpenRouter
deepseek/deepseek-v4-flash
DeepSeek: DeepSeek V4 Flash
YesJul 14, 202613 scenarios · avg 8.1/10 · 5.7s–3.2m/turn · 121 runs1,048,576 ctx · 393,216 max out$0.140/M in · $0.280/M out · $0.000616–$0.0151/simOpenRouter
qwen/qwen3-32b
Qwen: Qwen3 32B
YesJul 14, 202611 scenarios · avg 8.0/10 · 7.0s–56s/turn · 104 runs131,072 ctx · 16,384 max out$0.080/M in · $0.280/M out · $0.000436–$0.0107/simOpenRouter
google/gemma-4-31b-it
Gemma 4 31B IT
YesJul 14, 202612 scenarios · avg 8.0/10 · 3.0s–6.0m/turn · 92 runs262,144 ctx · 262,144 max out$0.100/M in · $0.340/M out · $0.000538–$0.0132/simOpenRouter
openai/gpt-4o-mini
OpenAI: GPT-4o-mini
YesJul 14, 202613 scenarios · avg 8.2/10 · 2.7s–14s/turn · 114 runs128,000 ctx · 16,384 max out$0.150/M in · $0.600/M out · $0.000870–$0.0213/simOpenRouter
google/gemma-3-12b-it
Google: Gemma 3 12B
YesJul 14, 202611 scenarios · avg 8.1/10 · 7.5s–2.2m/turn · 88 runs131,072 ctx · 16,384 max out$0.050/M in · $0.150/M out · $0.000255–$0.006247/simOpenRouter
deepseek/deepseek-chat
DeepSeek: DeepSeek V3
YesJul 14, 202611 scenarios · avg 8.1/10 · 8.0s–2.4m/turn · 88 runs163,840 ctx · 16,000 max out$0.257/M in · $1.03/M out · $0.001492–$0.0366/simOpenRouter
google/gemini-2.5-flash
Google: Gemini 2.5 Flash
YesJul 14, 202611 scenarios · avg 8.1/10 · 2.5s–8.0s/turn · 88 runs1,048,576 ctx · 65,535 max out$0.300/M in · $2.50/M out · $0.002650–$0.0649/simOpenRouter
anthropic/claude-haiku-4.5
Anthropic: Claude Haiku 4.5
YesJul 13, 202611 scenarios · avg 8.1/10 · 3.5s–8.3s/turn · 22 runs200,000 ctx · 64,000 max out$1.00/M in · $5.00/M out · $0.006500–$0.1593/simOpenRouter
anthropic/claude-opus-4
Anthropic: Claude Opus 4
YesJun 29, 20261 scenario · avg 9.0/10 · 10s–16s/turn · 10 runs200,000 ctx · 32,000 max out$15.0/M in · $75.0/M out · $0.0975–$2.39/simOpenRouter
openai/gpt-5.5
OpenAI: GPT-5.5
YesJun 29, 20261 scenario · avg 8.6/10 · 9.7s–13s/turn · 11 runs1,050,000 ctx · 128,000 max out$5.00/M in · $30.0/M out · $0.0360–$0.8820/simOpenRouter
anthropic/claude-sonnet-4
Anthropic: Claude Sonnet 4
YesJun 29, 20261 scenario · avg 8.3/10 · 4.0s–10s/turn · 11 runs1,000,000 ctx · 64,000 max out$3.00/M in · $15.0/M out · $0.0195–$0.4778/simOpenRouter
openai/gpt-4o
OpenAI: GPT-4o
YesJun 29, 20261 scenario · avg 8.6/10 · 2.0s–4.8s/turn · 10 runs128,000 ctx · 16,384 max out$2.50/M in · $10.0/M out · $0.0145–$0.3553/simOpenRouter
aion-labs/aion-2.0
AionLabs: Aion-2.0
No——131,072 ctx · 32,768 max out$0.800/M in · $1.60/M out · $0.003520–$0.0862/simOpenRouter
aion-labs/aion-3.0
AionLabs: Aion-3.0
No——131,072 ctx · 32,768 max out$3.00/M in · $6.00/M out · $0.0132–$0.3234/simOpenRouter
aion-labs/aion-3.0-mini
AionLabs: Aion-3.0-Mini
No——131,072 ctx · 32,768 max out$0.700/M in · $1.40/M out · $0.003080–$0.0755/simOpenRouter
aion-labs/aion-rp-llama-3.1-8b
AionLabs: Aion-RP 1.0 (8B)
No——32,768 ctx · 32,768 max out$0.800/M in · $1.60/M out · $0.003520–$0.0862/simOpenRouter
allenai/olmo-3-32b-think
AllenAI: Olmo 3 32B Think
No——65,536 ctx · 65,536 max out$0.150/M in · $0.500/M out · $0.000800–$0.0196/simOpenRouter
amazon/nova-2-lite-v1
Amazon: Nova 2 Lite
No——1,000,000 ctx · 65,535 max out$0.300/M in · $2.50/M out · $0.002650–$0.0649/simOpenRouter
amazon/nova-lite-v1
Amazon: Nova Lite 1.0
No——300,000 ctx · 5,120 max out$0.060/M in · $0.240/M out · $0.000348–$0.008526/simOpenRouter
amazon/nova-premier-v1
Amazon: Nova Premier 1.0
No——1,000,000 ctx · 32,000 max out$2.50/M in · $12.5/M out · $0.0163–$0.3981/simOpenRouter
amazon/nova-pro-v1
Amazon: Nova Pro 1.0
No——300,000 ctx · 5,120 max out$0.800/M in · $3.20/M out · $0.004640–$0.1137/simOpenRouter
anthracite-org/magnum-v4-72b
Magnum v4 72B
No——16,384 ctx · 2,048 max out$3.00/M in · $5.00/M out · $0.0125–$0.3063/simOpenRouter
anthropic/claude-3-haiku
Anthropic: Claude 3 Haiku
No——200,000 ctx · 4,096 max out$0.250/M in · $1.25/M out · $0.001625–$0.0398/simOpenRouter
anthropic/claude-fable-5
Anthropic: Claude Fable 5
No——1,000,000 ctx · 128,000 max out$10.0/M in · $50.0/M out · $0.0650–$1.59/simOpenRouter
anthropic/claude-fable-5:batch
Anthropic: Claude Fable 5 (batch)
No——1,000,000 ctx · 128,000 max out$5.00/M in · $25.0/M out · $0.0325–$0.7963/simOpenRouter
anthropic/claude-haiku-4.5:batch
Anthropic: Claude Haiku 4.5 (batch)
No——200,000 ctx · 64,000 max out$0.500/M in · $2.50/M out · $0.003250–$0.0796/simOpenRouter
anthropic/claude-opus-4.1
Anthropic: Claude Opus 4.1
No——200,000 ctx · 32,000 max out$15.0/M in · $75.0/M out · $0.0975–$2.39/simOpenRouter
anthropic/claude-opus-4.1:batch
Anthropic: Claude Opus 4.1 (batch)
No——200,000 ctx · 32,000 max out$7.50/M in · $37.5/M out · $0.0488–$1.19/simOpenRouter
anthropic/claude-opus-4.5
Anthropic: Claude Opus 4.5
No——200,000 ctx · 64,000 max out$5.00/M in · $25.0/M out · $0.0325–$0.7963/simOpenRouter
anthropic/claude-opus-4.5:batch
Anthropic: Claude Opus 4.5 (batch)
No——200,000 ctx · 64,000 max out$2.50/M in · $12.5/M out · $0.0163–$0.3981/simOpenRouter
anthropic/claude-opus-4.6
Anthropic: Claude Opus 4.6
No——1,000,000 ctx · 128,000 max out$5.00/M in · $25.0/M out · $0.0325–$0.7963/simOpenRouter
anthropic/claude-opus-4.6:batch
Anthropic: Claude Opus 4.6 (batch)
No——1,000,000 ctx · 128,000 max out$2.50/M in · $12.5/M out · $0.0163–$0.3981/simOpenRouter
anthropic/claude-opus-4.7-fast
Anthropic: Claude Opus 4.7 (Fast)
No——1,000,000 ctx · 128,000 max out$30.0/M in · $150/M out · $0.1950–$4.78/simOpenRouter
anthropic/claude-opus-4.7:batch
Anthropic: Claude Opus 4.7 (batch)
No——1,000,000 ctx · 128,000 max out$2.50/M in · $12.5/M out · $0.0163–$0.3981/simOpenRouter
anthropic/claude-opus-4.8
Anthropic: Claude Opus 4.8
No——1,000,000 ctx · 128,000 max out$5.00/M in · $25.0/M out · $0.0325–$0.7963/simOpenRouter
anthropic/claude-opus-4.8-fast
Anthropic: Claude Opus 4.8 (Fast)
No——1,000,000 ctx · 128,000 max out$10.0/M in · $50.0/M out · $0.0650–$1.59/simOpenRouter
anthropic/claude-opus-4.8:batch
Anthropic: Claude Opus 4.8 (batch)
No——1,000,000 ctx · 128,000 max out$2.50/M in · $12.5/M out · $0.0163–$0.3981/simOpenRouter
anthropic/claude-opus-5
Claude Opus 5
No——1,000,000 ctx · 128,000 max out$5.00/M in · $25.0/M out · $0.0325–$0.7963/simOpenRouter
anthropic/claude-opus-5-fast
Claude Opus 5 (Fast)
No——1,000,000 ctx · 128,000 max out$10.0/M in · $50.0/M out · $0.0650–$1.59/simOpenRouter
anthropic/claude-opus-5:batch
Claude Opus 5 (batch)
No——1,000,000 ctx · 128,000 max out$2.50/M in · $12.5/M out · $0.0163–$0.3981/simOpenRouter
anthropic/claude-sonnet-4.5
Anthropic: Claude Sonnet 4.5
No——1,000,000 ctx · 64,000 max out$3.00/M in · $15.0/M out · $0.0195–$0.4778/simOpenRouter
anthropic/claude-sonnet-4.5:batch
Anthropic: Claude Sonnet 4.5 (batch)
No——1,000,000 ctx · 64,000 max out$1.50/M in · $7.50/M out · $0.009750–$0.2389/simOpenRouter
anthropic/claude-sonnet-5
Anthropic: Claude Sonnet 5
No——1,000,000 ctx · 128,000 max out$2.00/M in · $10.0/M out · $0.0130–$0.3185/simOpenRouter
anthropic/claude-sonnet-5:batch
Anthropic: Claude Sonnet 5 (batch)
No——1,000,000 ctx · 128,000 max out$1.00/M in · $5.00/M out · $0.006500–$0.1593/simOpenRouter
arcee-ai/trinity-large-thinking
Arcee AI: Trinity Large Thinking
No——262,144 ctx · 262,144 max out$0.220/M in · $0.850/M out · $0.001255–$0.0307/simOpenRouter
arcee-ai/virtuoso-large
Arcee AI: Virtuoso Large
No——131,072 ctx · 64,000 max out$0.750/M in · $1.20/M out · $0.003090–$0.0757/simOpenRouter
baidu/ernie-4.5-vl-424b-a47b
Baidu: ERNIE 4.5 VL 424B A47B
No——123,000 ctx · 16,000 max out$0.420/M in · $1.25/M out · $0.002135–$0.0523/simOpenRouter
bytedance-seed/seed-1.6
ByteDance Seed: Seed 1.6
No——262,144 ctx · 32,768 max out$0.250/M in · $2.00/M out · $0.002150–$0.0527/simOpenRouter
bytedance-seed/seed-1.6-flash
ByteDance Seed: Seed 1.6 Flash
No——262,144 ctx · 32,768 max out$0.075/M in · $0.300/M out · $0.000435–$0.0107/simOpenRouter
bytedance-seed/seed-2.0-lite
ByteDance Seed: Seed-2.0-Lite
No——262,144 ctx · 131,072 max out$0.250/M in · $2.00/M out · $0.002150–$0.0527/simOpenRouter
bytedance-seed/seed-2.0-mini
ByteDance Seed: Seed-2.0-Mini
No——262,144 ctx · 131,072 max out$0.100/M in · $0.400/M out · $0.000580–$0.0142/simOpenRouter
bytedance/ui-tars-1.5-7b
ByteDance: UI-TARS 7B
No——128,000 ctx · 2,048 max out$0.100/M in · $0.200/M out · $0.000440–$0.0108/simOpenRouter
cognitivecomputations/dolphin-mistral-24b-venice-edition
Venice: Uncensored
No——128,000 ctx · 8,192 max out$0.200/M in · $0.900/M out · $0.001230–$0.0301/simOpenRouter
cohere/command-a
Cohere: Command A
No——256,000 ctx · 8,192 max out$2.50/M in · $10.0/M out · $0.0145–$0.3553/simOpenRouter
cohere/command-r-08-2024
Cohere: Command R (08-2024)
No——128,000 ctx · 4,000 max out$0.150/M in · $0.600/M out · $0.000870–$0.0213/simOpenRouter
cohere/command-r-plus-08-2024
Cohere: Command R+ (08-2024)
No——128,000 ctx · 4,000 max out$2.50/M in · $10.0/M out · $0.0145–$0.3553/simOpenRouter
cohere/command-r7b-12-2024
Cohere: Command R7B (12-2024)
No——128,000 ctx · 4,000 max out$0.037/M in · $0.150/M out · $0.000217–$0.005329/simOpenRouter
deepseek/deepseek-chat-v3-0324
DeepSeek: DeepSeek V3 0324
No——163,840 ctx · 65,536 max out$0.270/M in · $1.12/M out · $0.001594–$0.0391/simOpenRouter
deepseek/deepseek-chat-v3.1
DeepSeek: DeepSeek V3.1
No——163,840 ctx · 32,768 max out$0.250/M in · $0.950/M out · $0.001415–$0.0347/simOpenRouter
deepseek/deepseek-r1
DeepSeek: R1
No——163,840 ctx · 16,000 max out$0.700/M in · $2.50/M out · $0.003850–$0.0943/simOpenRouter
deepseek/deepseek-r1-0528
DeepSeek: R1 0528
No——163,840 ctx · 32,768 max out$0.500/M in · $2.15/M out · $0.003005–$0.0736/simOpenRouter
deepseek/deepseek-r1-distill-llama-70b
DeepSeek: R1 Distill Llama 70B
No——8,192 ctx · 8,192 max out$0.800/M in · $0.800/M out · $0.002960–$0.0725/simOpenRouter
deepseek/deepseek-v3.1-terminus
DeepSeek: DeepSeek V3.1 Terminus
No——163,840 ctx · 32,768 max out$0.270/M in · $1.00/M out · $0.001510–$0.0370/simOpenRouter
deepseek/deepseek-v3.2
DeepSeek: DeepSeek V3.2
No——163,840 ctx · 65,536 max out$0.269/M in · $0.400/M out · $0.001087–$0.0266/simOpenRouter
deepseek/deepseek-v3.2-exp
DeepSeek: DeepSeek V3.2 Exp
No——163,840 ctx · 65,536 max out$0.270/M in · $0.410/M out · $0.001097–$0.0269/simOpenRouter
deepseek/deepseek-v4-flash-0731
DeepSeek: DeepSeek V4 Flash 0731
No——1,048,576 ctx · 65,536 max out$0.090/M in · $0.180/M out · $0.000396–$0.009702/simOpenRouter
deepseek/deepseek-v4-pro
DeepSeek: DeepSeek V4 Pro
No——1,048,576 ctx · 384,000 max out$0.435/M in · $0.870/M out · $0.001914–$0.0469/simOpenRouter
google/gemini-2.5-flash-lite
Google: Gemini 2.5 Flash Lite
No——1,048,576 ctx · 65,535 max out$0.100/M in · $0.400/M out · $0.000580–$0.0142/simOpenRouter
google/gemini-2.5-flash-lite:batch
Google: Gemini 2.5 Flash Lite (batch)
No——1,048,576 ctx · 65,535 max out$0.050/M in · $0.200/M out · $0.000290–$0.007105/simOpenRouter
google/gemini-2.5-flash:batch
Google: Gemini 2.5 Flash (batch)
No——1,048,576 ctx · 65,535 max out$0.150/M in · $1.25/M out · $0.001325–$0.0325/simOpenRouter
google/gemini-2.5-pro
Google: Gemini 2.5 Pro
No——1,048,576 ctx · 65,536 max out$1.25/M in · $10.0/M out · $0.0107–$0.2634/simOpenRouter
google/gemini-2.5-pro-preview
Google: Gemini 2.5 Pro Preview 06-05
No——1,048,576 ctx · 65,536 max out$1.25/M in · $10.0/M out · $0.0107–$0.2634/simOpenRouter
google/gemini-2.5-pro-preview-05-06
Google: Gemini 2.5 Pro Preview 05-06
No——1,048,576 ctx · 65,535 max out$1.25/M in · $10.0/M out · $0.0107–$0.2634/simOpenRouter
google/gemini-2.5-pro:batch
Google: Gemini 2.5 Pro (batch)
No——1,048,576 ctx · 65,536 max out$0.625/M in · $5.00/M out · $0.005375–$0.1317/simOpenRouter
google/gemini-3-flash-preview
Google: Gemini 3 Flash Preview
No——1,048,576 ctx · 65,535 max out$0.500/M in · $3.00/M out · $0.003600–$0.0882/simOpenRouter
google/gemini-3-flash-preview:batch
Google: Gemini 3 Flash Preview (batch)
No——1,048,576 ctx · 65,535 max out$0.250/M in · $1.50/M out · $0.001800–$0.0441/simOpenRouter
google/gemini-3-pro-image
Google: Nano Banana Pro (Gemini 3 Pro Image)
No——131,072 ctx · 32,768 max out$2.00/M in · $12.0/M out · $0.0144–$0.3528/simOpenRouter
google/gemini-3.1-flash-lite
Google: Gemini 3.1 Flash Lite
No——1,048,576 ctx · 65,536 max out$0.250/M in · $1.50/M out · $0.001800–$0.0441/simOpenRouter
google/gemini-3.1-flash-lite-image
Google: Nano Banana 2 Lite (Gemini 3.1 Flash Lite Image)
No——65,536 ctx · 65,536 max out$0.250/M in · $1.50/M out · $0.001800–$0.0441/simOpenRouter
google/gemini-3.1-flash-lite-preview
Google: Gemini 3.1 Flash Lite Preview
No——1,048,576 ctx · 65,536 max out$0.250/M in · $1.50/M out · $0.001800–$0.0441/simOpenRouter
google/gemini-3.1-flash-lite:batch
Google: Gemini 3.1 Flash Lite (batch)
No——1,048,576 ctx · 65,536 max out$0.125/M in · $0.750/M out · $0.000900–$0.0221/simOpenRouter
google/gemini-3.1-pro-preview
Google: Gemini 3.1 Pro Preview
No——1,048,576 ctx · 65,536 max out$2.00/M in · $12.0/M out · $0.0144–$0.3528/simOpenRouter
google/gemini-3.1-pro-preview-customtools
Google: Gemini 3.1 Pro Preview Custom Tools
No——1,048,576 ctx · 65,536 max out$2.00/M in · $12.0/M out · $0.0144–$0.3528/simOpenRouter
google/gemini-3.1-pro-preview:batch
Google: Gemini 3.1 Pro Preview (batch)
No——1,048,576 ctx · 65,536 max out$1.00/M in · $6.00/M out · $0.007200–$0.1764/simOpenRouter
google/gemini-3.5-flash
Google: Gemini 3.5 Flash
No——1,048,576 ctx · 65,536 max out$1.50/M in · $9.00/M out · $0.0108–$0.2646/simOpenRouter
google/gemini-3.5-flash-lite
Google: Gemini 3.5 Flash-Lite
No——1,048,576 ctx · 65,536 max out$0.300/M in · $2.50/M out · $0.002650–$0.0649/simOpenRouter
google/gemini-3.5-flash-lite:batch
Google: Gemini 3.5 Flash Lite (batch)
No——1,048,576 ctx · 65,536 max out$0.150/M in · $1.25/M out · $0.001325–$0.0325/simOpenRouter
google/gemini-3.5-flash:batch
Google: Gemini 3.5 Flash (batch)
No——1,048,576 ctx · 65,536 max out$0.750/M in · $4.50/M out · $0.005400–$0.1323/simOpenRouter
google/gemini-3.6-flash
Google: Gemini 3.6 Flash
No——1,048,576 ctx · 65,536 max out$1.50/M in · $7.50/M out · $0.009750–$0.2389/simOpenRouter
google/gemini-3.6-flash:batch
Google: Gemini 3.6 Flash (batch)
No——1,048,576 ctx · 65,536 max out$0.750/M in · $3.75/M out · $0.004875–$0.1194/simOpenRouter
google/gemma-2-27b-it
Google: Gemma 2 27B
No——8,192 ctx · 2,048 max out$0.650/M in · $0.650/M out · $0.002405–$0.0589/simOpenRouter
google/gemma-3-27b-it
Google: Gemma 3 27B
No——262,144 ctx · 131,072 max out$0.080/M in · $0.450/M out · $0.000555–$0.0136/simOpenRouter
google/gemma-3-4b-it
Google: Gemma 3 4B
No——131,072 ctx · 16,384 max out$0.050/M in · $0.100/M out · $0.000220–$0.005390/simOpenRouter
google/gemma-4-26b-a4b-it
Google: Gemma 4 26B A4B
No——262,144 ctx · 16,384 max out$0.070/M in · $0.340/M out · $0.000448–$0.0110/simOpenRouter
gryphe/mythomax-l2-13b
MythoMax 13B
No——8,192 ctx · 4,096 max out$0.060/M in · $0.060/M out · $0.000222–$0.005439/simOpenRouter
ibm-granite/granite-4.1-8b
IBM: Granite 4.1 8B
No——131,072 ctx · 131,072 max out$0.050/M in · $0.100/M out · $0.000220–$0.005390/simOpenRouter
inception/mercury-2
Inception: Mercury 2
No——128,000 ctx · 50,000 max out$0.250/M in · $0.750/M out · $0.001275–$0.0312/simOpenRouter
kwaipilot/kat-coder-air-v2.5
Kwaipilot: KAT-Coder-Air V2.5
No——256,000 ctx · 80,000 max out$0.150/M in · $0.600/M out · $0.000870–$0.0213/simOpenRouter
kwaipilot/kat-coder-pro-v2
Kwaipilot: KAT-Coder-Pro V2
No——262,144 ctx · 80,000 max out$0.300/M in · $1.20/M out · $0.001740–$0.0426/simOpenRouter
kwaipilot/kat-coder-pro-v2.5
Kwaipilot: KAT-Coder-Pro V2.5
No——256,000 ctx · 80,000 max out$0.740/M in · $2.96/M out · $0.004292–$0.1052/simOpenRouter
mancer/weaver
Mancer: Weaver (alpha)
No——8,000 ctx · 2,000 max out$0.500/M in · $0.750/M out · $0.002025–$0.0496/simOpenRouter
meituan/longcat-2.0
Meituan: LongCat 2.0
No——1,048,756 ctx · 262,144 max out$0.300/M in · $1.20/M out · $0.001740–$0.0426/simOpenRouter
meta-llama/llama-3.1-70b-instruct
Meta: Llama 3.1 70B Instruct
No——131,072 ctx · 16,384 max out$0.400/M in · $0.400/M out · $0.001480–$0.0363/simOpenRouter
meta-llama/llama-3.2-1b-instruct
Meta: Llama 3.2 1B Instruct
No——60,000 ctx · 60,000 max out$0.027/M in · $0.201/M out · $0.000222–$0.005432/simOpenRouter
meta-llama/llama-3.2-3b-instruct
Meta: Llama 3.2 3B Instruct
No——131,072 ctx · 131,072 max out$0.050/M in · $0.330/M out · $0.000381–$0.009334/simOpenRouter
meta-llama/llama-4-scout
Meta: Llama 4 Scout
No——1,310,720 ctx · 16,384 max out$0.100/M in · $0.300/M out · $0.000510–$0.0125/simOpenRouter
meta-llama/llama-guard-4-12b
Meta: Llama Guard 4 12B
No——1,048,576 ctx · 16,384 max out$0.180/M in · $0.180/M out · $0.000666–$0.0163/simOpenRouter
meta/muse-spark-1.1
Meta: Muse Spark 1.1
No——1,048,576 ctx · — max out$1.25/M in · $4.25/M out · $0.006725–$0.1648/simOpenRouter
microsoft/phi-4
Microsoft: Phi 4
No——16,384 ctx · 16,384 max out$0.070/M in · $0.140/M out · $0.000308–$0.007546/simOpenRouter
microsoft/wizardlm-2-8x22b
WizardLM-2 8x22B
No——65,535 ctx · 8,000 max out$0.620/M in · $0.620/M out · $0.002294–$0.0562/simOpenRouter
minimax/minimax-01
MiniMax: MiniMax-01
No——1,000,192 ctx · 1,000,192 max out$0.200/M in · $1.10/M out · $0.001370–$0.0336/simOpenRouter
minimax/minimax-m1
MiniMax: MiniMax M1
No——1,000,000 ctx · 40,000 max out$0.550/M in · $2.20/M out · $0.003190–$0.0782/simOpenRouter
minimax/minimax-m2
MiniMax: MiniMax M2
No——204,800 ctx · 131,072 max out$0.255/M in · $1.02/M out · $0.001479–$0.0362/simOpenRouter
minimax/minimax-m2-her
MiniMax: MiniMax M2-her
No——65,536 ctx · 2,048 max out$0.300/M in · $1.20/M out · $0.001740–$0.0426/simOpenRouter
minimax/minimax-m2.1
MiniMax: MiniMax M2.1
No——204,800 ctx · 131,072 max out$0.300/M in · $1.20/M out · $0.001740–$0.0426/simOpenRouter
minimax/minimax-m2.5
MiniMax: MiniMax M2.5
No——204,800 ctx · 196,608 max out$0.150/M in · $0.900/M out · $0.001080–$0.0265/simOpenRouter
minimax/minimax-m2.7
MiniMax: MiniMax M2.7
No——204,800 ctx · 131,072 max out$0.250/M in · $1.00/M out · $0.001450–$0.0355/simOpenRouter
minimax/minimax-m3
MiniMax: MiniMax M3
No——1,048,576 ctx · 512,000 max out$0.300/M in · $1.20/M out · $0.001740–$0.0426/simOpenRouter
minimax/minimax-m3:batch
MiniMax: MiniMax M3 (batch)
No——524,288 ctx · — max out$0.150/M in · $0.600/M out · $0.000870–$0.0213/simOpenRouter
moonshotai/kimi-k2
MoonshotAI: Kimi K2 0711
No——131,072 ctx · 100,352 max out$0.570/M in · $2.30/M out · $0.003320–$0.0813/simOpenRouter
moonshotai/kimi-k2-0905
MoonshotAI: Kimi K2 0905
No——262,144 ctx · 100,352 max out$0.600/M in · $2.50/M out · $0.003550–$0.0870/simOpenRouter
moonshotai/kimi-k2-thinking
MoonshotAI: Kimi K2 Thinking
No——262,144 ctx · 100,352 max out$0.600/M in · $2.50/M out · $0.003550–$0.0870/simOpenRouter
moonshotai/kimi-k2.5
MoonshotAI: Kimi K2.5
No——262,144 ctx · 262,144 max out$0.570/M in · $2.85/M out · $0.003705–$0.0908/simOpenRouter
moonshotai/kimi-k2.6
MoonshotAI: Kimi K2.6
No——262,144 ctx · 262,144 max out$0.600/M in · $3.41/M out · $0.004187–$0.1026/simOpenRouter
moonshotai/kimi-k2.7-code
MoonshotAI: Kimi K2.7 Code
No——262,144 ctx · 262,144 max out$0.730/M in · $3.50/M out · $0.004640–$0.1137/simOpenRouter
moonshotai/kimi-k3
MoonshotAI: Kimi K3
No——1,048,576 ctx · — max out$3.00/M in · $15.0/M out · $0.0195–$0.4778/simOpenRouter
morph/morph-v3-fast
Morph: Morph V3 Fast
No——81,920 ctx · 38,000 max out$0.800/M in · $1.20/M out · $0.003240–$0.0794/simOpenRouter
morph/morph-v3-large
Morph: Morph V3 Large
No——262,144 ctx · 131,072 max out$0.900/M in · $1.90/M out · $0.004030–$0.0987/simOpenRouter
nex-agi/nex-n2-pro
Nex AGI: Nex-N2-Pro
No——262,144 ctx · 262,144 max out$0.250/M in · $1.00/M out · $0.001450–$0.0355/simOpenRouter
nousresearch/hermes-3-llama-3.1-405b
Nous: Hermes 3 405B Instruct
No——131,072 ctx · 16,384 max out$1.00/M in · $1.00/M out · $0.003700–$0.0906/simOpenRouter
nousresearch/hermes-3-llama-3.1-70b
Nous: Hermes 3 70B Instruct
No——131,072 ctx · 16,384 max out$0.700/M in · $0.700/M out · $0.002590–$0.0635/simOpenRouter
nousresearch/hermes-4-405b
Nous: Hermes 4 405B
No——131,072 ctx · — max out$1.00/M in · $3.00/M out · $0.005100–$0.1250/simOpenRouter
nousresearch/hermes-4-70b
Nous: Hermes 4 70B
No——131,072 ctx · — max out$0.130/M in · $0.400/M out · $0.000670–$0.0164/simOpenRouter
nvidia/nemotron-3-nano-30b-a3b
NVIDIA: Nemotron 3 Nano 30B A3B
No——262,144 ctx · 262,144 max out$0.050/M in · $0.200/M out · $0.000290–$0.007105/simOpenRouter
nvidia/nemotron-3-super-120b-a12b
NVIDIA: Nemotron 3 Super
No——1,000,000 ctx · 16,384 max out$0.085/M in · $0.400/M out · $0.000535–$0.0131/simOpenRouter
nvidia/nemotron-3-ultra-550b-a55b
NVIDIA: Nemotron 3 Ultra
No——512,288 ctx · 16,384 max out$0.600/M in · $3.60/M out · $0.004320–$0.1058/simOpenRouter
openai/gpt-3.5-turbo
OpenAI: GPT-3.5 Turbo
No——16,385 ctx · 4,096 max out$0.500/M in · $1.50/M out · $0.002550–$0.0625/simOpenRouter
openai/gpt-3.5-turbo-0613
OpenAI: GPT-3.5 Turbo (older v0613)
No——4,095 ctx · 4,096 max out$1.00/M in · $2.00/M out · $0.004400–$0.1078/simOpenRouter
openai/gpt-3.5-turbo-16k
OpenAI: GPT-3.5 Turbo 16k
No——16,385 ctx · 4,096 max out$3.00/M in · $4.00/M out · $0.0118–$0.2891/simOpenRouter
openai/gpt-3.5-turbo-instruct
OpenAI: GPT-3.5 Turbo Instruct
No——4,095 ctx · 4,096 max out$1.50/M in · $2.00/M out · $0.005900–$0.1446/simOpenRouter
openai/gpt-3.5-turbo:batch
OpenAI: GPT-3.5 Turbo (batch)
No——16,385 ctx · 4,096 max out$0.250/M in · $0.750/M out · $0.001275–$0.0312/simOpenRouter
openai/gpt-4
OpenAI: GPT-4
No——8,191 ctx · 4,096 max out$30.0/M in · $60.0/M out · $0.1320–$3.23/simOpenRouter
openai/gpt-4-turbo
OpenAI: GPT-4 Turbo
No——128,000 ctx · 4,096 max out$10.0/M in · $30.0/M out · $0.0510–$1.25/simOpenRouter
openai/gpt-4-turbo-preview
OpenAI: GPT-4 Turbo Preview
No——128,000 ctx · 4,096 max out$10.0/M in · $30.0/M out · $0.0510–$1.25/simOpenRouter
openai/gpt-4-turbo:batch
OpenAI: GPT-4 Turbo (batch)
No——128,000 ctx · 4,096 max out$5.00/M in · $15.0/M out · $0.0255–$0.6248/simOpenRouter
openai/gpt-4.1-mini:batch
OpenAI: GPT-4.1 Mini (batch)
No——1,047,576 ctx · 32,768 max out$0.200/M in · $0.800/M out · $0.001160–$0.0284/simOpenRouter
openai/gpt-4.1-nano:batch
OpenAI: GPT-4.1 Nano (batch)
No——1,047,576 ctx · 32,768 max out$0.050/M in · $0.200/M out · $0.000290–$0.007105/simOpenRouter
openai/gpt-4.1:batch
OpenAI: GPT-4.1 (batch)
No——1,047,576 ctx · 32,768 max out$1.00/M in · $4.00/M out · $0.005800–$0.1421/simOpenRouter
openai/gpt-4o-2024-05-13
OpenAI: GPT-4o (2024-05-13)
No——128,000 ctx · 4,096 max out$5.00/M in · $15.0/M out · $0.0255–$0.6248/simOpenRouter
openai/gpt-4o-2024-08-06
OpenAI: GPT-4o (2024-08-06)
No——128,000 ctx · 16,384 max out$2.50/M in · $10.0/M out · $0.0145–$0.3553/simOpenRouter
openai/gpt-4o-2024-11-20
OpenAI: GPT-4o (2024-11-20)
No——128,000 ctx · 16,384 max out$2.50/M in · $10.0/M out · $0.0145–$0.3553/simOpenRouter
openai/gpt-4o-mini-2024-07-18
OpenAI: GPT-4o-mini (2024-07-18)
No——128,000 ctx · 16,384 max out$0.150/M in · $0.600/M out · $0.000870–$0.0213/simOpenRouter
openai/gpt-4o-mini:batch
OpenAI: GPT-4o-mini (batch)
No——128,000 ctx · 16,384 max out$0.075/M in · $0.300/M out · $0.000435–$0.0107/simOpenRouter
openai/gpt-4o:batch
OpenAI: GPT-4o (batch)
No——128,000 ctx · 16,384 max out$1.25/M in · $5.00/M out · $0.007250–$0.1776/simOpenRouter
openai/gpt-5
OpenAI: GPT-5
No——400,000 ctx · 128,000 max out$1.25/M in · $10.0/M out · $0.0107–$0.2634/simOpenRouter
openai/gpt-5-image
OpenAI: GPT-5 Image
No——400,000 ctx · 128,000 max out$10.0/M in · $10.0/M out · $0.0370–$0.9065/simOpenRouter
openai/gpt-5-image-mini
OpenAI: GPT-5 Image Mini
No——400,000 ctx · 128,000 max out$2.50/M in · $2.00/M out · $0.008900–$0.2180/simOpenRouter
openai/gpt-5-mini
OpenAI: GPT-5 Mini
No——400,000 ctx · 128,000 max out$0.250/M in · $2.00/M out · $0.002150–$0.0527/simOpenRouter
openai/gpt-5-mini:batch
OpenAI: GPT-5 Mini (batch)
No——400,000 ctx · 128,000 max out$0.125/M in · $1.00/M out · $0.001075–$0.0263/simOpenRouter
openai/gpt-5-nano
OpenAI: GPT-5 Nano
No——400,000 ctx · 128,000 max out$0.050/M in · $0.400/M out · $0.000430–$0.0105/simOpenRouter
openai/gpt-5-nano:batch
OpenAI: GPT-5 Nano (batch)
No——400,000 ctx · 128,000 max out$0.025/M in · $0.200/M out · $0.000215–$0.005267/simOpenRouter
openai/gpt-5-pro
OpenAI: GPT-5 Pro
No——400,000 ctx · 128,000 max out$15.0/M in · $120/M out · $0.1290–$3.16/simOpenRouter
openai/gpt-5.1
OpenAI: GPT-5.1
No——400,000 ctx · 128,000 max out$1.25/M in · $10.0/M out · $0.0107–$0.2634/simOpenRouter
openai/gpt-5.1-codex
OpenAI: GPT-5.1-Codex
No——400,000 ctx · 128,000 max out$1.25/M in · $10.0/M out · $0.0107–$0.2634/simOpenRouter
openai/gpt-5.1-codex-max
OpenAI: GPT-5.1-Codex-Max
No——400,000 ctx · 128,000 max out$1.25/M in · $10.0/M out · $0.0107–$0.2634/simOpenRouter
openai/gpt-5.1-codex-mini
OpenAI: GPT-5.1-Codex-Mini
No——400,000 ctx · 128,000 max out$0.250/M in · $2.00/M out · $0.002150–$0.0527/simOpenRouter
openai/gpt-5.1:batch
OpenAI: GPT-5.1 (batch)
No——400,000 ctx · 128,000 max out$0.625/M in · $5.00/M out · $0.005375–$0.1317/simOpenRouter
openai/gpt-5.2
OpenAI: GPT-5.2
No——400,000 ctx · 128,000 max out$1.75/M in · $14.0/M out · $0.0150–$0.3687/simOpenRouter
openai/gpt-5.2-chat
OpenAI: GPT-5.2 Chat
No——128,000 ctx · 16,384 max out$1.75/M in · $14.0/M out · $0.0150–$0.3687/simOpenRouter
openai/gpt-5.2-codex
OpenAI: GPT-5.2-Codex
No——400,000 ctx · 128,000 max out$1.75/M in · $14.0/M out · $0.0150–$0.3687/simOpenRouter
openai/gpt-5.2-pro
OpenAI: GPT-5.2 Pro
No——400,000 ctx · 128,000 max out$21.0/M in · $168/M out · $0.1806–$4.42/simOpenRouter
openai/gpt-5.2-pro:batch
OpenAI: GPT-5.2 Pro (batch)
No——400,000 ctx · 128,000 max out$10.5/M in · $84.0/M out · $0.0903–$2.21/simOpenRouter
openai/gpt-5.2:batch
OpenAI: GPT-5.2 (batch)
No——400,000 ctx · 128,000 max out$0.875/M in · $7.00/M out · $0.007525–$0.1844/simOpenRouter
openai/gpt-5.3-codex
OpenAI: GPT-5.3-Codex
No——400,000 ctx · 128,000 max out$1.75/M in · $14.0/M out · $0.0150–$0.3687/simOpenRouter
openai/gpt-5.4
OpenAI: GPT-5.4
No——1,050,000 ctx · 128,000 max out$2.50/M in · $15.0/M out · $0.0180–$0.4410/simOpenRouter
openai/gpt-5.4-image-2
OpenAI: GPT-5.4 Image 2
No——272,000 ctx · 128,000 max out$8.00/M in · $15.0/M out · $0.0345–$0.8452/simOpenRouter
openai/gpt-5.4-mini
OpenAI: GPT-5.4 Mini
No——400,000 ctx · 128,000 max out$0.750/M in · $4.50/M out · $0.005400–$0.1323/simOpenRouter
openai/gpt-5.4-mini:batch
OpenAI: GPT-5.4 Mini (batch)
No——400,000 ctx · 128,000 max out$0.375/M in · $2.25/M out · $0.002700–$0.0662/simOpenRouter
openai/gpt-5.4-nano
OpenAI: GPT-5.4 Nano
No——400,000 ctx · 128,000 max out$0.200/M in · $1.25/M out · $0.001475–$0.0361/simOpenRouter
openai/gpt-5.4-nano:batch
OpenAI: GPT-5.4 Nano (batch)
No——400,000 ctx · 128,000 max out$0.100/M in · $0.625/M out · $0.000737–$0.0181/simOpenRouter
openai/gpt-5.4-pro
OpenAI: GPT-5.4 Pro
No——1,050,000 ctx · 128,000 max out$30.0/M in · $180/M out · $0.2160–$5.29/simOpenRouter
openai/gpt-5.4-pro:batch
OpenAI: GPT-5.4 Pro (batch)
No——1,050,000 ctx · 128,000 max out$15.0/M in · $90.0/M out · $0.1080–$2.65/simOpenRouter
openai/gpt-5.4:batch
OpenAI: GPT-5.4 (batch)
No——1,050,000 ctx · 128,000 max out$1.25/M in · $7.50/M out · $0.009000–$0.2205/simOpenRouter
openai/gpt-5.5-pro
OpenAI: GPT-5.5 Pro
No——1,050,000 ctx · 128,000 max out$30.0/M in · $180/M out · $0.2160–$5.29/simOpenRouter
openai/gpt-5.5-pro:batch
OpenAI: GPT-5.5 Pro (batch)
No——1,050,000 ctx · 128,000 max out$15.0/M in · $90.0/M out · $0.1080–$2.65/simOpenRouter
openai/gpt-5.5:batch
OpenAI: GPT-5.5 (batch)
No——1,050,000 ctx · 128,000 max out$2.50/M in · $15.0/M out · $0.0180–$0.4410/simOpenRouter
openai/gpt-5.6-luna
OpenAI: GPT-5.6 Luna
No——1,050,000 ctx · 128,000 max out$0.100/M in · $0.600/M out · $0.000720–$0.0176/simOpenRouter
openai/gpt-5.6-luna-pro
OpenAI: GPT-5.6 Luna Pro
No——1,050,000 ctx · 128,000 max out$0.100/M in · $0.600/M out · $0.000720–$0.0176/simOpenRouter
openai/gpt-5.6-sol
OpenAI: GPT-5.6 Sol
No——1,050,000 ctx · 128,000 max out$5.00/M in · $30.0/M out · $0.0360–$0.8820/simOpenRouter
openai/gpt-5.6-sol-pro
OpenAI: GPT-5.6 Sol Pro
No——1,050,000 ctx · 128,000 max out$5.00/M in · $30.0/M out · $0.0360–$0.8820/simOpenRouter
openai/gpt-5.6-terra
OpenAI: GPT-5.6 Terra
No——1,050,000 ctx · 128,000 max out$1.00/M in · $6.00/M out · $0.007200–$0.1764/simOpenRouter
openai/gpt-5.6-terra-pro
OpenAI: GPT-5.6 Terra Pro
No——1,050,000 ctx · 128,000 max out$1.00/M in · $6.00/M out · $0.007200–$0.1764/simOpenRouter
openai/gpt-5:batch
OpenAI: GPT-5 (batch)
No——400,000 ctx · 128,000 max out$0.625/M in · $5.00/M out · $0.005375–$0.1317/simOpenRouter
openai/gpt-audio
OpenAI: GPT Audio
No——128,000 ctx · 16,384 max out$2.50/M in · $10.0/M out · $0.0145–$0.3553/simOpenRouter
openai/gpt-audio-mini
OpenAI: GPT Audio Mini
No——128,000 ctx · 16,384 max out$0.600/M in · $2.40/M out · $0.003480–$0.0853/simOpenRouter
openai/gpt-chat-latest
OpenAI: GPT Chat Latest
No——400,000 ctx · 128,000 max out$5.00/M in · $30.0/M out · $0.0360–$0.8820/simOpenRouter
openai/gpt-oss-safeguard-20b
OpenAI: gpt-oss-safeguard-20b
No——131,072 ctx · 65,536 max out$0.075/M in · $0.300/M out · $0.000435–$0.0107/simOpenRouter
openai/o1
OpenAI: o1
No——200,000 ctx · 100,000 max out$15.0/M in · $60.0/M out · $0.0870–$2.13/simOpenRouter
openai/o1-pro
OpenAI: o1-pro
No——200,000 ctx · 100,000 max out$150/M in · $600/M out · $0.8700–$21.32/simOpenRouter
openai/o3
OpenAI: o3
No——200,000 ctx · 100,000 max out$2.00/M in · $8.00/M out · $0.0116–$0.2842/simOpenRouter
openai/o3-mini
OpenAI: o3 Mini
No——200,000 ctx · 100,000 max out$1.10/M in · $4.40/M out · $0.006380–$0.1563/simOpenRouter
openai/o3-mini-high
OpenAI: o3 Mini High
No——200,000 ctx · 100,000 max out$1.10/M in · $4.40/M out · $0.006380–$0.1563/simOpenRouter
openai/o3-pro
OpenAI: o3 Pro
No——200,000 ctx · 100,000 max out$20.0/M in · $80.0/M out · $0.1160–$2.84/simOpenRouter
openai/o4-mini
OpenAI: o4 Mini
No——200,000 ctx · 100,000 max out$1.10/M in · $4.40/M out · $0.006380–$0.1563/simOpenRouter
openai/o4-mini-high
OpenAI: o4 Mini High
No——200,000 ctx · 100,000 max out$1.10/M in · $4.40/M out · $0.006380–$0.1563/simOpenRouter
perceptron/perceptron-mk1
Perceptron: Perceptron Mk1
No——32,768 ctx · 8,192 max out$0.150/M in · $1.50/M out · $0.001500–$0.0367/simOpenRouter
perplexity/sonar
Perplexity: Sonar
No——127,072 ctx · — max out$1.00/M in · $1.00/M out · $0.003700–$0.0906/simOpenRouter
perplexity/sonar-deep-research
Perplexity: Sonar Deep Research
No——128,000 ctx · — max out$2.00/M in · $8.00/M out · $0.0116–$0.2842/simOpenRouter
perplexity/sonar-pro
Perplexity: Sonar Pro
No——200,000 ctx · 8,000 max out$3.00/M in · $15.0/M out · $0.0195–$0.4778/simOpenRouter
perplexity/sonar-pro-search
Perplexity: Sonar Pro Search
No——200,000 ctx · 8,000 max out$3.00/M in · $15.0/M out · $0.0195–$0.4778/simOpenRouter
perplexity/sonar-reasoning-pro
Perplexity: Sonar Reasoning Pro
No——128,000 ctx · — max out$2.00/M in · $8.00/M out · $0.0116–$0.2842/simOpenRouter
poolside/laguna-s-2.1
Poolside: Laguna S 2.1
No——1,048,576 ctx · 131,072 max out$0.090/M in · $0.180/M out · $0.000396–$0.009702/simOpenRouter
poolside/laguna-xs-2.1
Poolside: Laguna XS 2.1
No——262,144 ctx · 32,768 max out$0.060/M in · $0.120/M out · $0.000264–$0.006468/simOpenRouter
qwen/qwen-2.5-72b-instruct
Qwen2.5 72B Instruct
No——32,768 ctx · 16,384 max out$0.360/M in · $0.400/M out · $0.001360–$0.0333/simOpenRouter
qwen/qwen-2.5-coder-32b-instruct
Qwen2.5 Coder 32B Instruct
No——32,768 ctx · 32,768 max out$0.660/M in · $1.00/M out · $0.002680–$0.0657/simOpenRouter
qwen/qwen-plus
Qwen: Qwen-Plus
No——1,000,000 ctx · 32,768 max out$0.260/M in · $0.780/M out · $0.001326–$0.0325/simOpenRouter
qwen/qwen-plus-2025-07-28
Qwen: Qwen Plus 0728
No——1,000,000 ctx · 32,768 max out$0.260/M in · $0.780/M out · $0.001326–$0.0325/simOpenRouter
qwen/qwen2.5-vl-72b-instruct
Qwen: Qwen2.5 VL 72B Instruct
No——128,000 ctx · 128,000 max out$0.800/M in · $1.00/M out · $0.003100–$0.0760/simOpenRouter
qwen/qwen3-14b
Qwen: Qwen3 14B
No——131,072 ctx · 8,192 max out$0.228/M in · $0.910/M out · $0.001319–$0.0323/simOpenRouter
qwen/qwen3-235b-a22b-thinking-2507
Qwen: Qwen3 235B A22B Thinking 2507
No——262,144 ctx · 32,768 max out$0.230/M in · $2.30/M out · $0.002300–$0.0563/simOpenRouter
qwen/qwen3-30b-a3b
Qwen: Qwen3 30B A3B
No——131,072 ctx · 16,384 max out$0.120/M in · $0.500/M out · $0.000710–$0.0174/simOpenRouter
qwen/qwen3-30b-a3b-instruct-2507
Qwen: Qwen3 30B A3B Instruct 2507
No——262,144 ctx · 32,000 max out$0.048/M in · $0.193/M out · $0.000280–$0.006850/simOpenRouter
qwen/qwen3-30b-a3b-thinking-2507
Qwen: Qwen3 30B A3B Thinking 2507
No——81,920 ctx · 32,768 max out$0.200/M in · $2.40/M out · $0.002280–$0.0559/simOpenRouter
qwen/qwen3-8b
Qwen: Qwen3 8B
No——131,072 ctx · 8,192 max out$0.117/M in · $0.455/M out · $0.000669–$0.0164/simOpenRouter
qwen/qwen3-coder
Qwen: Qwen3 Coder 480B A35B
No——262,144 ctx · 65,536 max out$0.300/M in · $1.00/M out · $0.001600–$0.0392/simOpenRouter
qwen/qwen3-coder-30b-a3b-instruct
Qwen: Qwen3 Coder 30B A3B Instruct
No——262,144 ctx · 262,144 max out$0.070/M in · $0.280/M out · $0.000406–$0.009947/simOpenRouter
qwen/qwen3-coder-flash
Qwen: Qwen3 Coder Flash
No——1,000,000 ctx · 65,536 max out$0.195/M in · $0.975/M out · $0.001267–$0.0311/simOpenRouter
qwen/qwen3-coder-next
Qwen: Qwen3 Coder Next
No——262,144 ctx · 262,144 max out$0.120/M in · $0.800/M out · $0.000920–$0.0225/simOpenRouter
qwen/qwen3-coder-plus
Qwen: Qwen3 Coder Plus
No——1,000,000 ctx · 65,536 max out$0.650/M in · $3.25/M out · $0.004225–$0.1035/simOpenRouter
qwen/qwen3-max
Qwen: Qwen3 Max
No——262,144 ctx · 65,536 max out$0.780/M in · $3.90/M out · $0.005070–$0.1242/simOpenRouter
qwen/qwen3-max-thinking
Qwen: Qwen3 Max Thinking
No——262,144 ctx · 65,536 max out$0.780/M in · $3.90/M out · $0.005070–$0.1242/simOpenRouter
qwen/qwen3-next-80b-a3b-instruct
Qwen: Qwen3 Next 80B A3B Instruct
No——262,144 ctx · 262,144 max out$0.100/M in · $1.10/M out · $0.001070–$0.0262/simOpenRouter
qwen/qwen3-next-80b-a3b-thinking
Qwen: Qwen3 Next 80B A3B Thinking
No——262,144 ctx · 32,768 max out$0.150/M in · $1.20/M out · $0.001290–$0.0316/simOpenRouter
qwen/qwen3-vl-235b-a22b-instruct
Qwen: Qwen3 VL 235B A22B Instruct
No——262,144 ctx · 32,768 max out$0.210/M in · $1.90/M out · $0.001960–$0.0480/simOpenRouter
qwen/qwen3-vl-235b-a22b-thinking
Qwen: Qwen3 VL 235B A22B Thinking
No——131,072 ctx · 32,768 max out$0.980/M in · $3.95/M out · $0.005705–$0.1398/simOpenRouter
qwen/qwen3-vl-30b-a3b-instruct
Qwen: Qwen3 VL 30B A3B Instruct
No——262,144 ctx · 32,768 max out$0.130/M in · $0.520/M out · $0.000754–$0.0185/simOpenRouter
qwen/qwen3-vl-30b-a3b-thinking
Qwen: Qwen3 VL 30B A3B Thinking
No——262,144 ctx · 32,768 max out$0.200/M in · $2.40/M out · $0.002280–$0.0559/simOpenRouter
qwen/qwen3-vl-32b-instruct
Qwen: Qwen3 VL 32B Instruct
No——131,072 ctx · 32,768 max out$0.104/M in · $0.416/M out · $0.000603–$0.0148/simOpenRouter
qwen/qwen3-vl-8b-instruct
Qwen: Qwen3 VL 8B Instruct
No——262,144 ctx · 32,768 max out$0.117/M in · $0.455/M out · $0.000669–$0.0164/simOpenRouter
qwen/qwen3-vl-8b-thinking
Qwen: Qwen3 VL 8B Thinking
No——131,072 ctx · 32,768 max out$0.180/M in · $2.10/M out · $0.002010–$0.0492/simOpenRouter
qwen/qwen3.5-122b-a10b
Qwen: Qwen3.5-122B-A10B
No——262,144 ctx · 65,536 max out$0.260/M in · $2.08/M out · $0.002236–$0.0548/simOpenRouter
qwen/qwen3.5-27b
Qwen: Qwen3.5-27B
No——262,144 ctx · 65,536 max out$0.195/M in · $1.56/M out · $0.001677–$0.0411/simOpenRouter
qwen/qwen3.5-35b-a3b
Qwen: Qwen3.5-35B-A3B
No——262,144 ctx · 262,144 max out$0.140/M in · $1.00/M out · $0.001120–$0.0274/simOpenRouter
qwen/qwen3.5-397b-a17b
Qwen: Qwen3.5 397B A17B
No——262,144 ctx · 65,536 max out$0.390/M in · $2.34/M out · $0.002808–$0.0688/simOpenRouter
qwen/qwen3.5-9b
Qwen: Qwen3.5-9B
No——262,144 ctx · 262,144 max out$0.100/M in · $0.150/M out · $0.000405–$0.009922/simOpenRouter
qwen/qwen3.5-flash-02-23
Qwen: Qwen3.5-Flash
No——1,000,000 ctx · 65,536 max out$0.065/M in · $0.260/M out · $0.000377–$0.009236/simOpenRouter
qwen/qwen3.5-plus-02-15
Qwen: Qwen3.5 Plus 2026-02-15
No——1,000,000 ctx · 65,536 max out$0.260/M in · $1.56/M out · $0.001872–$0.0459/simOpenRouter
qwen/qwen3.5-plus-20260420
Qwen: Qwen3.5 Plus 2026-04-20
No——1,000,000 ctx · 65,536 max out$0.300/M in · $1.80/M out · $0.002160–$0.0529/simOpenRouter
qwen/qwen3.6-27b
Qwen: Qwen3.6 27B
No——262,144 ctx · 131,072 max out$0.289/M in · $2.40/M out · $0.002547–$0.0624/simOpenRouter
qwen/qwen3.6-35b-a3b
Qwen: Qwen3.6 35B A3B
No——262,144 ctx · 262,144 max out$0.140/M in · $1.00/M out · $0.001120–$0.0274/simOpenRouter
qwen/qwen3.6-flash
Qwen: Qwen3.6 Flash
No——1,000,000 ctx · 65,536 max out$0.188/M in · $1.12/M out · $0.001350–$0.0331/simOpenRouter
qwen/qwen3.6-max-preview
Qwen: Qwen3.6 Max Preview
No——262,144 ctx · 65,536 max out$1.03/M in · $6.16/M out · $0.007394–$0.1812/simOpenRouter
qwen/qwen3.6-plus
Qwen: Qwen3.6 Plus
No——1,000,000 ctx · 65,536 max out$0.325/M in · $1.95/M out · $0.002340–$0.0573/simOpenRouter
qwen/qwen3.7-max
Qwen: Qwen3.7 Max
No——1,000,000 ctx · 131,072 max out$1.48/M in · $4.42/M out · $0.007522–$0.1843/simOpenRouter
qwen/qwen3.7-plus
Qwen: Qwen3.7 Plus
No——1,000,000 ctx · 131,072 max out$0.320/M in · $1.28/M out · $0.001856–$0.0455/simOpenRouter
rekaai/reka-edge
Reka Edge
No——16,384 ctx · 16,384 max out$0.100/M in · $0.100/M out · $0.000370–$0.009065/simOpenRouter
rekaai/reka-flash-3
Reka Flash 3
No——65,536 ctx · 65,536 max out$0.100/M in · $0.200/M out · $0.000440–$0.0108/simOpenRouter
relace/relace-apply-3
Relace: Relace Apply 3
No——256,000 ctx · 128,000 max out$0.850/M in · $1.25/M out · $0.003425–$0.0839/simOpenRouter
relace/relace-search
Relace: Relace Search
No——256,000 ctx · 128,000 max out$1.00/M in · $3.00/M out · $0.005100–$0.1250/simOpenRouter
sakana/fugu-ultra
Sakana: Fugu Ultra
No——1,000,000 ctx · 128,000 max out$5.00/M in · $30.0/M out · $0.0360–$0.8820/simOpenRouter
sao10k/l3.1-euryale-70b
Sao10K: Llama 3.1 Euryale 70B v2.2
No——131,072 ctx · 16,384 max out$0.850/M in · $0.850/M out · $0.003145–$0.0771/simOpenRouter
sao10k/l3.3-euryale-70b
Sao10K: Llama 3.3 Euryale 70B
No——131,072 ctx · 16,384 max out$0.650/M in · $0.750/M out · $0.002475–$0.0606/simOpenRouter
stepfun/step-3.5-flash
StepFun: Step 3.5 Flash
No——262,144 ctx · 65,536 max out$0.100/M in · $0.300/M out · $0.000510–$0.0125/simOpenRouter
stepfun/step-3.7-flash
StepFun: Step 3.7 Flash
No——262,144 ctx · 256,000 max out$0.200/M in · $1.15/M out · $0.001405–$0.0344/simOpenRouter
tencent/hunyuan-a13b-instruct
Tencent: Hunyuan A13B Instruct
No——131,072 ctx · 131,072 max out$0.140/M in · $0.570/M out · $0.000819–$0.0201/simOpenRouter
tencent/hy3
Tencent: Hy3
No——262,144 ctx · 128,000 max out$0.132/M in · $0.528/M out · $0.000766–$0.0188/simOpenRouter
tencent/hy3-preview
Tencent: Hy3 preview
No——262,144 ctx · — max out$0.063/M in · $0.210/M out · $0.000336–$0.008232/simOpenRouter
thedrummer/cydonia-24b-v4.1
TheDrummer: Cydonia 24B V4.1
No——131,072 ctx · 131,072 max out$0.300/M in · $0.500/M out · $0.001250–$0.0306/simOpenRouter
thedrummer/rocinante-12b
TheDrummer: Rocinante 12B
No——65,536 ctx · 65,536 max out$0.250/M in · $0.500/M out · $0.001100–$0.0270/simOpenRouter
thedrummer/skyfall-36b-v2
TheDrummer: Skyfall 36B V2
No——32,768 ctx · 32,768 max out$0.550/M in · $0.800/M out · $0.002210–$0.0541/simOpenRouter
thedrummer/unslopnemo-12b
TheDrummer: UnslopNemo 12B
No——1,024,000 ctx · 1,024,000 max out$0.400/M in · $0.400/M out · $0.001480–$0.0363/simOpenRouter
thinkingmachines/inkling
Thinking Machines: Inkling
No——1,048,576 ctx · — max out$1.00/M in · $4.05/M out · $0.005835–$0.1430/simOpenRouter
thinkingmachines/inkling-small
Thinking Machines: Inkling Small
No——524,288 ctx · — max out$0.500/M in · $1.20/M out · $0.002340–$0.0573/simOpenRouter
undi95/remm-slerp-l2-13b
ReMM SLERP 13B
No——6,144 ctx · 2,048 max out$0.450/M in · $0.650/M out · $0.001805–$0.0442/simOpenRouter
upstage/solar-pro-3
Upstage: Solar Pro 3
No——128,000 ctx · — max out$0.150/M in · $0.600/M out · $0.000870–$0.0213/simOpenRouter
writer/palmyra-x5
Writer: Palmyra X5
No——1,040,000 ctx · 8,192 max out$0.600/M in · $6.00/M out · $0.006000–$0.1470/simOpenRouter
x-ai/grok-4.20
xAI: Grok 4.20
No——2,000,000 ctx · — max out$1.25/M in · $2.50/M out · $0.005500–$0.1348/simOpenRouter
x-ai/grok-4.20-multi-agent
xAI: Grok 4.20 Multi-Agent
No——2,000,000 ctx · — max out$1.25/M in · $2.50/M out · $0.005500–$0.1348/simOpenRouter
x-ai/grok-4.3
xAI: Grok 4.3
No——1,000,000 ctx · — max out$1.25/M in · $2.50/M out · $0.005500–$0.1348/simOpenRouter
x-ai/grok-4.5
xAI: Grok 4.5
No——500,000 ctx · — max out$2.00/M in · $6.00/M out · $0.0102–$0.2499/simOpenRouter
x-ai/grok-build-0.1
xAI: Grok Build 0.1
No——256,000 ctx · — max out$1.00/M in · $2.00/M out · $0.004400–$0.1078/simOpenRouter
xiaomi/mimo-v2.5
Xiaomi: MiMo-V2.5
No——1,050,000 ctx · 131,072 max out$0.140/M in · $0.280/M out · $0.000616–$0.0151/simOpenRouter
xiaomi/mimo-v2.5-pro
Xiaomi: MiMo-V2.5-Pro
No——1,050,000 ctx · 131,072 max out$0.435/M in · $0.870/M out · $0.001914–$0.0469/simOpenRouter
z-ai/glm-4.5
Z.ai: GLM 4.5
No——131,072 ctx · 98,304 max out$0.600/M in · $2.20/M out · $0.003340–$0.0818/simOpenRouter
z-ai/glm-4.5-air
Z.ai: GLM 4.5 Air
No——131,072 ctx · 98,304 max out$0.130/M in · $0.850/M out · $0.000985–$0.0241/simOpenRouter
z-ai/glm-4.5v
Z.ai: GLM 4.5V
No——65,536 ctx · 16,384 max out$0.600/M in · $1.80/M out · $0.003060–$0.0750/simOpenRouter
z-ai/glm-4.6
Z.ai: GLM 4.6
No——204,800 ctx · 131,072 max out$0.500/M in · $2.00/M out · $0.002900–$0.0711/simOpenRouter
z-ai/glm-4.6v
Z.ai: GLM 4.6V
No——131,072 ctx · 32,768 max out$0.300/M in · $0.900/M out · $0.001530–$0.0375/simOpenRouter
z-ai/glm-4.7
Z.ai: GLM 4.7
No——204,800 ctx · 131,072 max out$0.400/M in · $1.75/M out · $0.002425–$0.0594/simOpenRouter
z-ai/glm-4.7-flash
Z.ai: GLM 4.7 Flash
No——202,752 ctx · 16,384 max out$0.060/M in · $0.400/M out · $0.000460–$0.0113/simOpenRouter
z-ai/glm-5
Z.ai: GLM 5
No——204,800 ctx · 131,072 max out$0.950/M in · $2.55/M out · $0.004635–$0.1136/simOpenRouter
z-ai/glm-5-turbo
Z.ai: GLM 5 Turbo
No——202,752 ctx · 131,072 max out$1.20/M in · $4.00/M out · $0.006400–$0.1568/simOpenRouter
z-ai/glm-5.1
Z.ai: GLM 5.1
No——204,800 ctx · 128,000 max out$0.966/M in · $3.04/M out · $0.005023–$0.1231/simOpenRouter
z-ai/glm-5.2
Z.ai: GLM 5.2
No——1,048,576 ctx · 131,072 max out$0.615/M in · $1.93/M out · $0.003196–$0.0783/simOpenRouter
z-ai/glm-5v-turbo
Z.ai: GLM 5V Turbo
No——202,752 ctx · 131,072 max out$1.20/M in · $4.00/M out · $0.006400–$0.1568/simOpenRouter
~anthropic/claude-fable-latest
Anthropic: Claude Fable Latest
No——1,000,000 ctx · 128,000 max out$10.0/M in · $50.0/M out · $0.0650–$1.59/simOpenRouter
~anthropic/claude-haiku-latest
Anthropic Claude Haiku Latest
No——200,000 ctx · 64,000 max out$1.00/M in · $5.00/M out · $0.006500–$0.1593/simOpenRouter
~anthropic/claude-opus-latest
Anthropic: Claude Opus Latest
No——1,000,000 ctx · 128,000 max out$5.00/M in · $25.0/M out · $0.0325–$0.7963/simOpenRouter
~anthropic/claude-sonnet-latest
Anthropic Claude Sonnet Latest
No——1,000,000 ctx · 128,000 max out$2.00/M in · $10.0/M out · $0.0130–$0.3185/simOpenRouter
~deepseek/deepseek-v4-flash-latest
DeepSeek V4 Flash Latest
No——1,048,576 ctx · 65,536 max out$0.090/M in · $0.180/M out · $0.000396–$0.009702/simOpenRouter
~google/gemini-flash-latest
Google Gemini Flash Latest
No——1,048,576 ctx · 65,536 max out$1.50/M in · $7.50/M out · $0.009750–$0.2389/simOpenRouter
~google/gemini-pro-latest
Google Gemini Pro Latest
No——1,048,576 ctx · 65,536 max out$2.00/M in · $12.0/M out · $0.0144–$0.3528/simOpenRouter
~moonshotai/kimi-latest
MoonshotAI Kimi Latest
No——1,048,576 ctx · 1,048,576 max out$2.90/M in · $14.0/M out · $0.0185–$0.4532/simOpenRouter
~openai/gpt-latest
OpenAI GPT Latest
No——1,050,000 ctx · 128,000 max out$5.00/M in · $30.0/M out · $0.0360–$0.8820/simOpenRouter
~openai/gpt-mini-latest
OpenAI GPT Mini Latest
No——400,000 ctx · 128,000 max out$0.750/M in · $4.50/M out · $0.005400–$0.1323/simOpenRouter
~x-ai/grok-latest
xAI: Grok Latest
No——500,000 ctx · — max out$2.00/M in · $6.00/M out · $0.0102–$0.2499/simOpenRouter
For search engines and LLMs
# RuntimeAI Model Catalog
Generated: 2026-08-27T08:50:03Z
Pricing updated: 2026-08-03T15:10:18Z
Tested models: 29 / 323 in OpenRouter catalog

## Recently benchmarked models
- openai/gpt-oss-20b: 20 scenarios, avg=8.1/10, speed=4.0s–40s/turn, n=154, last=2026-08-25T14:55:11.931904+00:00
- ibm-granite/granite-4.0-h-micro: 20 scenarios, avg=8.3/10, speed=3.6s–41s/turn, n=147, last=2026-08-25T14:54:48.958597+00:00
- qwen/qwen3.7-flash: 6 scenarios, avg=8.6/10, speed=17s–50s/turn, n=28, last=2026-08-25T14:21:29.448713+00:00
- nex-agi/nex-n2-mini: 9 scenarios, avg=8.6/10, speed=2.3s–38s/turn, n=34, last=2026-08-25T14:20:46.661735+00:00
- sao10k/l3-lunaris-8b: 19 scenarios, avg=8.2/10, speed=2.2s–12s/turn, n=165, last=2026-08-25T12:44:34.167233+00:00
- anthropic/claude-sonnet-4.6: 7 scenarios, avg=9.0/10, speed=7.5s–22s/turn, n=42, last=2026-07-28T12:13:01.630432+00:00
- anthropic/claude-opus-4.7: 6 scenarios, avg=9.1/10, speed=6.5s–18s/turn, n=27, last=2026-07-28T12:12:46.363726+00:00
- meta-llama/llama-3.1-8b-instruct: 20 scenarios, avg=8.3/10, speed=1.5s–42s/turn, n=160, last=2026-07-28T12:12:42.416288+00:00
- amazon/nova-micro-v1: 20 scenarios, avg=8.4/10, speed=1.0s–16s/turn, n=174, last=2026-07-28T12:12:40.852495+00:00
- openai/gpt-4.1: 6 scenarios, avg=8.9/10, speed=2.6s–8.5s/turn, n=27, last=2026-07-28T12:12:37.475574+00:00
- qwen/qwen-2.5-7b-instruct: 19 scenarios, avg=8.3/10, speed=1.4s–16s/turn, n=164, last=2026-07-28T12:12:29.392902+00:00
- qwen/qwen3-235b-a22b-2507: 11 scenarios, avg=8.0/10, speed=6.5s–48s/turn, n=108, last=2026-07-14T07:52:01.057212+00:00
- openai/gpt-oss-120b: 14 scenarios, avg=8.0/10, speed=3.5s–54s/turn, n=136, last=2026-07-14T07:49:35.611274+00:00
- meta-llama/llama-4-maverick: 13 scenarios, avg=8.1/10, speed=2.4s–5.7m/turn, n=132, last=2026-07-14T07:47:19.895467+00:00
- openai/gpt-4.1-mini: 11 scenarios, avg=8.1/10, speed=3.5s–27s/turn, n=110, last=2026-07-14T07:46:22.982033+00:00
- openai/gpt-4.1-nano: 13 scenarios, avg=8.1/10, speed=2.0s–14s/turn, n=138, last=2026-07-14T07:46:02.970126+00:00
- meta-llama/llama-3.3-70b-instruct: 11 scenarios, avg=8.0/10, speed=8.0s–5.8m/turn, n=108, last=2026-07-14T07:45:37.662161+00:00
- deepseek/deepseek-v4-flash: 13 scenarios, avg=8.1/10, speed=5.7s–3.2m/turn, n=121, last=2026-07-14T07:44:55.512838+00:00
- qwen/qwen3-32b: 11 scenarios, avg=8.0/10, speed=7.0s–56s/turn, n=104, last=2026-07-14T07:33:46.768790+00:00
- google/gemma-4-31b-it: 12 scenarios, avg=8.0/10, speed=3.0s–6.0m/turn, n=92, last=2026-07-14T07:31:26.447997+00:00
- openai/gpt-4o-mini: 13 scenarios, avg=8.2/10, speed=2.7s–14s/turn, n=114, last=2026-07-14T03:48:47.393716+00:00
- google/gemma-3-12b-it: 11 scenarios, avg=8.1/10, speed=7.5s–2.2m/turn, n=88, last=2026-07-14T03:44:05.140340+00:00
- deepseek/deepseek-chat: 11 scenarios, avg=8.1/10, speed=8.0s–2.4m/turn, n=88, last=2026-07-14T03:43:09.862569+00:00
- google/gemini-2.5-flash: 11 scenarios, avg=8.1/10, speed=2.5s–8.0s/turn, n=88, last=2026-07-14T03:42:37.430524+00:00
- anthropic/claude-haiku-4.5: 11 scenarios, avg=8.1/10, speed=3.5s–8.3s/turn, n=22, last=2026-07-13T05:50:24.008406+00:00
- anthropic/claude-opus-4: 1 scenarios, avg=9.0/10, speed=10s–16s/turn, n=10, last=2026-06-29T11:18:02.290770+00:00
- openai/gpt-5.5: 1 scenarios, avg=8.6/10, speed=9.7s–13s/turn, n=11, last=2026-06-29T11:17:12.863667+00:00
- anthropic/claude-sonnet-4: 1 scenarios, avg=8.3/10, speed=4.0s–10s/turn, n=11, last=2026-06-29T11:16:29.068881+00:00
- openai/gpt-4o: 1 scenarios, avg=8.6/10, speed=2.0s–4.8s/turn, n=10, last=2026-06-29T11:09:59.062453+00:00

## Pricing source
OpenRouter public API → vantageai.cc model-costs.json