Comparison of Models: Intelligence, Performance & Price Analysis
Comparison and analysis of AI models across key performance metrics including quality, price, output speed, latency, context window & others. Click on any model to see detailed metrics. For more details including relating to our methodology, see our FAQs.
Model Comparison Summary
GPT-5.2 (xhigh) and 
Claude Opus 4.5 are the highest intelligence models, followed by GPT-5.2 Codex (xhigh) & 
Gemini 3 Pro Preview (high).Output Speed (tokens/s): Gemini 2.5 Flash-Lite (Sep) (576 t/s) and 
Granite 3.3 8B (488 t/s) are the fastest models, followed by Gemini 2.5 Flash-Lite (Sep) & 
Nova Micro.Latency (seconds):
Apriel-v1.5-15B-Thinker (0.18s) and 
NVIDIA Nemotron Nano 12B v2 VL (0.21s) are the lowest latency models, followed by NVIDIA Nemotron 3 Nano & 
Olmo 3.1 32B Instruct.Price ($ per M tokens): Gemma 3n E4B ($0.03) and 
DeepSeek-OCR ($0.05) are the cheapest models, followed by 
Llama 3.2 1B & Llama 3.2 3B.Context Window: Llama 4 Scout (10m) and 
Grok 4.1 Fast (2m) are the largest context window models, followed by Grok 4.1 Fast & Gemini 2.0 Pro Experimental.Highlights
Intelligence
Artificial Analysis Intelligence Index
Artificial Analysis Intelligence Index v4.0 includes: GDPval-AA, 𝜏²-Bench Telecom, Terminal-Bench Hard, SciCode, AA-LCR, AA-Omniscience, IFBench, Humanity's Last Exam, GPQA Diamond, CritPt. See Intelligence Index methodology for further details, including a breakdown of each evaluation and how we run them.
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Artificial Analysis Intelligence Index by Open Weights vs Proprietary
Artificial Analysis Intelligence Index v4.0 includes: GDPval-AA, 𝜏²-Bench Telecom, Terminal-Bench Hard, SciCode, AA-LCR, AA-Omniscience, IFBench, Humanity's Last Exam, GPQA Diamond, CritPt. See Intelligence Index methodology for further details, including a breakdown of each evaluation and how we run them.
Indicates whether the model weights are available. Models are labelled as 'Commercial Use Restricted' if the weights are available but commercial use is limited (typically requires obtaining a paid license).
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Intelligence Evaluations
While model intelligence generally translates across use cases, specific evaluations may be more relevant for certain use cases.
Artificial Analysis Intelligence Index v4.0 includes: GDPval-AA, 𝜏²-Bench Telecom, Terminal-Bench Hard, SciCode, AA-LCR, AA-Omniscience, IFBench, Humanity's Last Exam, GPQA Diamond, CritPt. See Intelligence Index methodology for further details, including a breakdown of each evaluation and how we run them.
Artificial Analysis Omniscience
AA-Omniscience Index
AA-Omniscience Index (higher is better) measures knowledge reliability and hallucination. It rewards correct answers, penalizes hallucinations, and has no penalty for refusing to answer. Scores range from -100 to 100, where 0 means as many correct as incorrect answers, and negative scores mean more incorrect than correct.
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LLM benchmarks dataset. https://artificialanalysis.ai","data":"modelName,omniscienceIndex,detailsUrl,isLabClaimedValue\nGemini 3 Pro Preview (high),12.867,/models/gemini-3-pro/providers,false\nClaude Opus 4.5,10.233,/models/claude-opus-4-5-thinking/providers,false\nGemini 3 Flash,8.233,/models/gemini-3-flash-reasoning/providers,false\nClaude 4.1 Opus,4.933,/models/claude-4-1-opus-thinking/providers,false\nGPT-5.1 (high),2.2,/models/gpt-5-1/providers,false\nGrok 4,0.95,/models/grok-4/providers,false\nRing-1T,0.017,/models/ring-1t/providers,false\nJamba 1.7 Large,-0.217,/models/jamba-1-7-large/providers,false\nLing-mini-2.0,-0.45,/models/ling-mini-2-0/providers,false\nJamba 1.7 Mini,-0.5,/models/jamba-1-7-mini/providers,false\nGemini 3 Flash,-0.917,/models/gemini-3-flash/providers,false\nGemini 3 Pro Preview (low),-1.05,/models/gemini-3-pro-low/providers,false\nClaude 3.7 Sonnet,-1.733,/models/claude-3-7-sonnet-thinking/providers,false\nClaude 4 Sonnet,-1.767,/models/claude-4-sonnet-thinking/providers,false\nClaude 4.5 Sonnet,-2.083,/models/claude-4-5-sonnet-thinking/providers,false\nGPT-5.2 (medium),-2.7,/models/gpt-5-2-medium/providers,false\nGPT-5.2 (xhigh),-4.317,/models/gpt-5-2/providers,false\nGPT-5.2 Codex (xhigh),-5.55,/models/gpt-5-2-codex/providers,false\nClaude 4.5 Haiku,-5.667,/models/claude-4-5-haiku-reasoning/providers,false\nClaude Opus 4.5,-6.45,/models/claude-opus-4-5/providers,false\nGPT-5.1 Codex (high),-7.017,/models/gpt-5-1-codex/providers,false\nGrok 3 mini Reasoning (high),-7.15,/models/grok-3-mini-reasoning/providers,false\nClaude 4.5 Haiku,-7.95,/models/claude-4-5-haiku/providers,false\nGPT-5 Codex (high),-9.667,/models/gpt-5-codex/providers,false\nClaude 4 Sonnet,-10.367,/models/claude-4-sonnet/providers,false\nClaude 4.5 Sonnet,-10.65,/models/claude-4-5-sonnet/providers,false\nClaude 3.7 Sonnet,-10.983,/models/claude-3-7-sonnet/providers,false\nGPT-5 (high),-11.1,/models/gpt-5/providers,false\nGPT-4o (Nov),-12.05,/models/gpt-4o/providers,false\no1,-12.817,/models/o1/providers,false\nGPT-5 (low),-12.933,/models/gpt-5-low/providers,false\nGPT-5 mini (medium),-12.933,/models/gpt-5-mini-medium/providers,false\nGPT-5 (medium),-13.733,/models/gpt-5-medium/providers,false\nGPT-5.2,-15.4,/models/gpt-5-2-non-reasoning/providers,false\no3,-17.183,/models/o3/providers,false\nGemini 2.5 Pro,-17.95,/models/gemini-2-5-pro/providers,false\nLlama 3.1 405B,-18.167,/models/llama-3-1-instruct-405b/providers,false\nGPT-5.1 Codex mini (high),-18.283,/models/gpt-5-1-codex-mini/providers,false\nDeepSeek V3.2 Speciale,-19.233,/models/deepseek-v3-2-speciale/providers,false\nGPT-5 mini (high),-19.617,/models/gpt-5-mini/providers,false\nGPT-4o (Aug),-21.733,/models/gpt-4o-2024-08-06/providers,false\nDeepSeek V3.2,-23.317,/models/deepseek-v3-2-reasoning/providers,false\nClaude 3.5 Haiku,-23.35,/models/claude-3-5-haiku/providers,false\nKimi K2 Thinking,-23.417,/models/kimi-k2-thinking/providers,false\nQwen3 Coder 480B,-23.967,/models/qwen3-coder-480b-a35b-instruct/providers,false\nGLM-4.6V,-26.25,/models/glm-4-6v-reasoning/providers,false\nDeepSeek V3.1 Terminus,-26.7,/models/deepseek-v3-1-terminus-reasoning/providers,false\nGPT-5 nano (medium),-27.35,/models/gpt-5-nano-medium/providers,false\nCogito v2.1,-27.417,/models/cogito-v2-1-reasoning/providers,false\nMagistral Medium 1.2,-27.633,/models/magistral-medium-2509/providers,false\nMagistral Medium 1,-28,/models/magistral-medium/providers,false\nKimi K2 0905,-28.35,/models/kimi-k2-0905/providers,false\nGLM-4.5,-29.017,/models/glm-4.5/providers,false\nGPT-5 nano (high),-29.65,/models/gpt-5-nano/providers,false\nDeepSeek R1 0528,-29.667,/models/deepseek-r1/providers,false\nMiniMax-M2.1,-29.8,/models/minimax-m2-1/providers,false\nKimi K2,-30.117,/models/kimi-k2/providers,false\nGrok 4 Fast,-30.5,/models/grok-4-fast-reasoning/providers,false\nDeepSeek V3.1,-30.583,/models/deepseek-v3-1-reasoning/providers,false\nGemini 2.5 Flash,-30.85,/models/gemini-2-5-flash-reasoning/providers,false\nGrok 4.1 Fast,-31.383,/models/grok-4-1-fast-reasoning/providers,false\nLlama 3.1 8B,-31.6,/models/llama-3-1-instruct-8b/providers,false\nDeepSeek V3.2 Exp,-31.9,/models/deepseek-v3-2-reasoning-0925/providers,false\nMistral Medium 3,-32.617,/models/mistral-medium-3/providers,false\nDevstral Medium,-32.8,/models/devstral-medium/providers,false\nGLM-4.6,-33.25,/models/glm-4-6/providers,false\nDeepSeek R1 (Jan),-33.633,/models/deepseek-r1-0120/providers,false\nHermes 4 405B,-34.633,/models/hermes-4-llama-3-1-405b/providers,false\nGrok 3,-35.267,/models/grok-3/providers,false\nMistral Large 2 (Nov),-35.517,/models/mistral-large-2/providers,false\nKAT-Coder-Pro V1,-35.533,/models/kat-coder-pro-v1/providers,false\nDoubao Seed Code,-35.933,/models/doubao-seed-code/providers,false\nGLM-4.7,-36.267,/models/glm-4-7/providers,false\nGPT-5.1,-36.583,/models/gpt-5-1-non-reasoning/providers,false\nGPT-5 (minimal),-36.667,/models/gpt-5-minimal/providers,false\nERNIE 4.5 300B A47B,-36.833,/models/ernie-4-5-300b-a47b/providers,false\no4-mini (high),-37.183,/models/o4-mini/providers,false\nHermes 4 405B,-37.367,/models/hermes-4-llama-3-1-405b-reasoning/providers,false\nGemini 2.5 Flash (Sep),-37.5,/models/gemini-2-5-flash-preview-09-2025-reasoning/providers,false\nGrok Code Fast 1,-38.033,/models/grok-code-fast-1/providers,false\nNova Premier,-38.317,/models/nova-premier/providers,false\nGLM-4.6V,-38.65,/models/glm-4-6v/providers,false\nOlmo 3.1 32B Think,-39.483,/models/olmo-3-1-32b-think/providers,false\nQwen3 Max Thinking,-39.783,/models/qwen3-max-thinking/providers,false\nMistral Large 3,-40.983,/models/mistral-large-3/providers,false\nGemini 2.5 Flash (Sep),-41.317,/models/gemini-2-5-flash-preview-09-2025/providers,false\nLlama 3.1 Nemotron 70B,-41.417,/models/llama-3-1-nemotron-instruct-70b/providers,false\nMiMo-V2-Flash,-41.833,/models/mimo-v2-flash-reasoning/providers,false\nGPT-4.1,-42.133,/models/gpt-4-1/providers,false\nDeepSeek V3 0324,-42.283,/models/deepseek-v3-0324/providers,false\nERNIE 5.0 Thinking Preview,-42.367,/models/ernie-5-0-thinking-preview/providers,false\nNVIDIA Nemotron Nano 9B V2,-43.217,/models/nvidia-nemotron-nano-9b-v2-reasoning/providers,false\nLlama 4 Maverick,-43.467,/models/llama-4-maverick/providers,false\nDeepSeek V3.1,-43.533,/models/deepseek-v3-1/providers,false\nNova Lite,-43.55,/models/nova-lite/providers,false\nQwen3 Max (Preview),-43.567,/models/qwen3-max-preview/providers,false\nDeepSeek V3 (Dec),-43.633,/models/deepseek-v3/providers,false\nGemini 2.5 Flash-Lite (Sep),-43.717,/models/gemini-2-5-flash-lite-preview-09-2025/providers,false\nGemini 2.5 Flash,-43.75,/models/gemini-2-5-flash/providers,false\nGLM-4.6,-43.883,/models/glm-4-6-reasoning/providers,false\no3-mini (high),-44.283,/models/o3-mini-high/providers,false\nGemini 2.0 Flash,-44.333,/models/gemini-2-0-flash/providers,false\nLlama 3.1 70B,-44.417,/models/llama-3-1-instruct-70b/providers,false\nDeepSeek V3.1 Terminus,-44.583,/models/deepseek-v3-1-terminus/providers,false\nMiMo-V2-Flash,-44.6,/models/mimo-v2-flash/providers,false\nQwen3 Max,-44.9,/models/qwen3-max/providers,false\nMagistral Small 1,-45.2,/models/magistral-small/providers,false\nQwen3 235B 2507,-45.383,/models/qwen3-235b-a22b-instruct-2507/providers,false\nQwen3 235B,-45.55,/models/qwen3-235b-a22b-instruct-reasoning/providers,false\nLlama Nemotron Ultra,-46.2,/models/llama-3-1-nemotron-ultra-253b-v1-reasoning/providers,false\nGLM-4.5V,-46.417,/models/glm-4-5v-reasoning/providers,false\nQwen3 VL 235B A22B,-46.567,/models/qwen3-vl-235b-a22b-reasoning/providers,false\nGemini 2.5 Flash-Lite,-46.983,/models/gemini-2-5-flash-lite-reasoning/providers,false\nLlama Nemotron Super 49B v1.5,-47.2,/models/llama-nemotron-super-49b-v1-5/providers,false\nDeepSeek R1 Distill Llama 70B,-47.433,/models/deepseek-r1-distill-llama-70b/providers,false\nLlama Nemotron Super 49B v1.5,-47.467,/models/llama-nemotron-super-49b-v1-5-reasoning/providers,false\nNova 2.0 Pro Preview (low),-47.5,/models/nova-2-0-pro-reasoning-low/providers,false\nQwen3 235B A22B 2507,-47.7,/models/qwen3-235b-a22b-instruct-2507-reasoning/providers,false\nMistral Medium 3.1,-47.9,/models/mistral-medium-3-1/providers,false\nDevstral 2,-47.917,/models/devstral-2/providers,false\nGLM-4.7,-48.233,/models/glm-4-7-non-reasoning/providers,false\nNova Pro,-48.517,/models/nova-pro/providers,false\nDeepSeek V3.2,-48.683,/models/deepseek-v3-2/providers,false\nK2-V2 (low),-49.017,/models/k2-v2-low/providers,false\nDeepSeek V3.2 Exp,-49.117,/models/deepseek-v3-2-0925/providers,false\nNova Micro,-49.35,/models/nova-micro/providers,false\nMiniMax-M2,-49.533,/models/minimax-m2/providers,false\nCommand A,-49.583,/models/command-a/providers,false\nHermes 4 70B,-50.033,/models/hermes-4-llama-3-1-70b/providers,false\nMiniMax M1 80k,-50.167,/models/minimax-m1-80k/providers,false\nNova 2.0 Pro Preview (medium),-50.3,/models/nova-2-0-pro-reasoning-medium/providers,false\nQwen3 14B,-50.317,/models/qwen3-14b-instruct-reasoning/providers,false\nNova 2.0 Pro Preview,-50.367,/models/nova-2-0-pro/providers,false\nK2-V2 (medium),-50.6,/models/k2-v2-medium/providers,false\nHermes 4 70B,-50.717,/models/hermes-4-llama-3-1-70b-reasoning/providers,false\nLlama 3.3 Nemotron Super 49B,-51.017,/models/llama-3-3-nemotron-super-49b/providers,false\nMistral Small 3.2,-51.3,/models/mistral-small-3-2/providers,false\nNova 2.0 Omni (low),-51.4,/models/nova-2-0-omni-reasoning-low/providers,false\nQwen3 32B,-51.5,/models/qwen3-32b-instruct-reasoning/providers,false\nQwen3 Coder 30B A3B,-51.7,/models/qwen3-coder-30b-a3b-instruct/providers,false\ngpt-oss-120B (high),-51.933,/models/gpt-oss-120b/providers,false\nDevstral Small,-51.967,/models/devstral-small/providers,false\nHyperCLOVA X SEED Think (32B),-51.983,/models/hyperclova-x-seed-think-32b/providers,false\nMistral Small 3.1,-52.183,/models/mistral-small-3-1/providers,false\nGrok 4.1 Fast,-52.317,/models/grok-4-1-fast/providers,false\nQwen3 30B,-52.333,/models/qwen3-30b-a3b-instruct-reasoning/providers,false\nNVIDIA Nemotron 3 Nano,-52.383,/models/nvidia-nemotron-3-nano-30b-a3b-reasoning/providers,false\nINTELLECT-3,-52.383,/models/intellect-3/providers,false\nQwen3 Next 80B A3B,-52.783,/models/qwen3-next-80b-a3b-reasoning/providers,false\nLlama 4 Scout,-53.05,/models/llama-4-scout/providers,false\nQwen3 VL 32B,-53.233,/models/qwen3-vl-32b-reasoning/providers,false\nOlmo 3.1 32B Instruct,-53.317,/models/olmo-3-1-32b-instruct/providers,false\nQwen2.5 72B,-53.517,/models/qwen2-5-72b-instruct/providers,false\nSeed-OSS-36B-Instruct,-53.533,/models/seed-oss-36b-instruct/providers,false\nQwen3 VL 8B,-53.8,/models/qwen3-vl-8b-instruct/providers,false\nQwen3 4B 2507,-53.833,/models/qwen3-4b-2507-instruct/providers,false\nQwen3 VL 235B A22B,-53.867,/models/qwen3-vl-235b-a22b-instruct/providers,false\nQwen3 VL 8B,-54.317,/models/qwen3-vl-8b-reasoning/providers,false\nQwen3 235B,-54.333,/models/qwen3-235b-a22b-instruct/providers,false\nGemini 2.5 Flash-Lite (Sep),-54.633,/models/gemini-2-5-flash-lite-preview-09-2025-reasoning/providers,false\nQwen3 4B 2507,-54.667,/models/qwen3-4b-2507-instruct-reasoning/providers,false\nNova 2.0 Lite (low),-54.95,/models/nova-2-0-lite-reasoning-low/providers,false\nLFM2 2.6B,-54.95,/models/lfm2-2-6b/providers,false\nLlama 3 70B,-54.95,/models/llama-3-instruct-70b/providers,false\nMi:dm K 2.5 Pro,-55.217,/models/mi-dm-k-2-5-pro-dec28/providers,false\nLlama 3.2 1B,-55.433,/models/llama-3-2-instruct-1b/providers,false\nLlama 3.3 70B,-55.467,/models/llama-3-3-instruct-70b/providers,false\nGPT-5 mini (minimal),-55.6,/models/gpt-5-mini-minimal/providers,false\nGrok 4 Fast,-55.683,/models/grok-4-fast/providers,false\nGPT-4.1 mini,-55.7,/models/gpt-4-1-mini/providers,false\nApriel-v1.5-15B-Thinker,-55.85,/models/apriel-v1-5-15b-thinker/providers,false\ngpt-oss-120B (low),-55.933,/models/gpt-oss-120b-low/providers,false\nMi:dm K 2.5 Pro Preview,-56.017,/models/midm-250-pro-rsnsft/providers,false\nSolar Open 100B,-56.133,/models/solar-open-100b-reasoning/providers,false\nPhi-4,-56.167,/models/phi-4/providers,false\nGLM-4.5V,-56.867,/models/glm-4-5v/providers,false\nLing-1T,-57.167,/models/ling-1t/providers,false\nK2-V2 (high),-57.283,/models/k2-v2/providers,false\nQwen3 30B A3B 2507,-57.433,/models/qwen3-30b-a3b-2507-reasoning/providers,false\nSolar Pro 2,-57.533,/models/solar-pro-2-reasoning/providers,false\nNova 2.0 Lite (medium),-57.633,/models/nova-2-0-lite-reasoning-medium/providers,false\nDevstral Small (May),-58.017,/models/devstral-small-2505/providers,false\nNVIDIA Nemotron Nano 9B V2,-58.383,/models/nvidia-nemotron-nano-9b-v2/providers,false\nK-EXAONE,-58.75,/models/k-exaone/providers,false\nDevstral Small 2,-58.883,/models/devstral-small-2/providers,false\nGPT-4.1 nano,-58.95,/models/gpt-4-1-nano/providers,false\nQwen3 VL 30B A3B,-59.133,/models/qwen3-vl-30b-a3b-reasoning/providers,false\nGemini 2.5 Flash-Lite,-59.45,/models/gemini-2-5-flash-lite/providers,false\nNova 2.0 Omni (medium),-59.7,/models/nova-2-0-omni-reasoning-medium/providers,false\nRing-flash-2.0,-59.767,/models/ring-flash-2-0/providers,false\nApriel-v1.6-15B-Thinker,-59.833,/models/apriel-v1-6-15b-thinker/providers,false\nOlmo 3 32B Think,-60.25,/models/olmo-3-32b-think/providers,false\nNova 2.0 Lite,-60.483,/models/nova-2-0-lite/providers,false\nQwen3 Next 80B A3B,-60.483,/models/qwen3-next-80b-a3b-instruct/providers,false\ngpt-oss-20B (low),-60.6,/models/gpt-oss-20b-low/providers,false\nEXAONE 4.0 32B,-61.417,/models/exaone-4-0-32b-reasoning/providers,false\nQwen3 Omni 30B A3B,-61.767,/models/qwen3-omni-30b-a3b-reasoning/providers,false\nFalcon-H1R-7B,-61.917,/models/falcon-h1r-7b/providers,false\nGranite 4.0 H Small,-62.067,/models/granite-4-0-h-small/providers,false\nMotif-2-12.7B,-62.233,/models/motif-2-12-7b/providers,false\nPhi-4 Mini,-62.7,/models/phi-4-mini/providers,false\nJamba Reasoning 3B,-62.833,/models/jamba-reasoning-3b/providers,false\nLlama 3.2 11B (Vision),-62.967,/models/llama-3-2-instruct-11b-vision/providers,false\nSolar Pro 2,-63.117,/models/solar-pro-2/providers,false\nGLM-4.5-Air,-63.15,/models/glm-4-5-air/providers,false\nGranite 4.0 350M,-63.683,/models/granite-4-0-350m/providers,false\nQwen3 VL 32B,-63.9,/models/qwen3-vl-32b-instruct/providers,false\nMinistral 3 3B,-63.967,/models/ministral-3-3b/providers,false\nQwen3 VL 30B A3B,-64.033,/models/qwen3-vl-30b-a3b-instruct/providers,false\nEXAONE 4.0 32B,-64.3,/models/exaone-4-0-32b/providers,false\ngpt-oss-20B (high),-64.9,/models/gpt-oss-20b/providers,false\nNVIDIA Nemotron 3 Nano,-65.2,/models/nvidia-nemotron-3-nano-30b-a3b/providers,false\nNova 2.0 Omni,-65.233,/models/nova-2-0-omni/providers,false\nReka Flash 3,-65.233,/models/reka-flash-3/providers,false\nDeepSeek R1 0528 Qwen3 8B,-65.317,/models/deepseek-r1-qwen3-8b/providers,false\nK-EXAONE,-65.95,/models/k-exaone-non-reasoning/providers,false\nQwen3 8B,-66.117,/models/qwen3-8b-instruct-reasoning/providers,false\nMistral 7B,-66.25,/models/mistral-7b-instruct/providers,false\nNVIDIA Nemotron Nano 12B v2 VL,-66.35,/models/nvidia-nemotron-nano-12b-v2-vl-reasoning/providers,false\nGPT-5 nano (minimal),-66.367,/models/gpt-5-nano-minimal/providers,false\nMagistral Small 1.2,-66.383,/models/magistral-small-2509/providers,false\nQwen3 30B A3B 2507,-66.8,/models/qwen3-30b-a3b-2507/providers,false\nMinistral 3 14B,-67.383,/models/ministral-3-14b/providers,false\nLing-flash-2.0,-67.45,/models/ling-flash-2-0/providers,false\nGemma 3 27B,-67.95,/models/gemma-3-27b/providers,false\nQwen3 30B,-67.983,/models/qwen3-30b-a3b-instruct/providers,false\nQwen3 14B,-68.3,/models/qwen3-14b-instruct/providers,false\nMolmo2-8B,-69.433,/models/molmo2-8b/providers,false\nQwen3 Omni 30B A3B,-69.75,/models/qwen3-omni-30b-a3b-instruct/providers,false\nMinistral 3 8B,-69.983,/models/ministral-3-8b/providers,false\nLFM2 1.2B,-71.217,/models/lfm2-1-2b/providers,false\nLlama 3 8B,-71.65,/models/llama-3-instruct-8b/providers,false\nNVIDIA Nemotron Nano 12B v2 VL,-73.167,/models/nvidia-nemotron-nano-12b-v2-vl/providers,false\nOlmo 3 7B Think,-73.967,/models/olmo-3-7b-think/providers,false\nGranite 4.0 H 1B,-74.383,/models/granite-4-0-h-nano-1b/providers,false\nLFM2.5-1.2B-Instruct,-74.75,/models/lfm2-5-1-2b-instruct/providers,false\nQwen3 8B,-75.4,/models/qwen3-8b-instruct/providers,false\nGemma 3 12B,-77.25,/models/gemma-3-12b/providers,false\nLFM2 8B A1B,-77.517,/models/lfm2-8b-a1b/providers,false\nOlmo 3 7B,-78.183,/models/olmo-3-7b-instruct/providers,false\nGranite 4.0 Micro,-78.35,/models/granite-4-0-micro/providers,false\nQwen3 1.7B,-78.35,/models/qwen3-1.7b-instruct-reasoning/providers,false\nGranite 3.3 8B,-78.95,/models/granite-3-3-8b-instruct/providers,false\nGemma 3 1B,-80.25,/models/gemma-3-1b/providers,false\nGemma 3n E2B,-80.617,/models/gemma-3n-e2b/providers,false\nGemma 3n E4B,-81.983,/models/gemma-3n-e4b/providers,false\nQwen3 1.7B,-82.367,/models/qwen3-1.7b-instruct/providers,false\nQwen3 0.6B,-82.45,/models/qwen3-0.6b-instruct-reasoning/providers,false\nExaone 4.0 1.2B,-82.467,/models/exaone-4-0-1-2b-reasoning/providers,false\nGranite 4.0 1B,-83,/models/granite-4-0-nano-1b/providers,false\nExaone 4.0 1.2B,-83.167,/models/exaone-4-0-1-2b/providers,false\nGemma 3 4B,-83.817,/models/gemma-3-4b/providers,false\nLFM2.5-VL-1.6B,-85.6,/models/lfm2-5-vl-1-6b/providers,false\nQwen3 0.6B,-86.85,/models/qwen3-0.6b-instruct/providers,false\nGranite 4.0 H 350M,-89.467,/models/granite-4-0-h-350m/providers,false"}
Openness
Artificial Analysis Openness Index: Results
Intelligence Index Comparisons
Intelligence vs. Price
While higher intelligence models are typically more expensive, they do not all follow the same price-quality curve.
Artificial Analysis Intelligence Index v4.0 includes: GDPval-AA, 𝜏²-Bench Telecom, Terminal-Bench Hard, SciCode, AA-LCR, AA-Omniscience, IFBench, Humanity's Last Exam, GPQA Diamond, CritPt. See Intelligence Index methodology for further details, including a breakdown of each evaluation and how we run them.
Price per token, represented as USD per million Tokens. Price is a blend of Input & Output token prices (3:1 ratio).
Figures represent performance of the model's first-party API (e.g. OpenAI for o1) or the median across providers where a first-party API is not available (e.g. Meta's Llama models).
Intelligence Index Token Use & Cost
Output Tokens Used to Run Artificial Analysis Intelligence Index
The number of tokens required to run all evaluations in the Artificial Analysis Intelligence Index (excluding repeats).
Cost to Run Artificial Analysis Intelligence Index
The cost to run the evaluations in the Artificial Analysis Intelligence Index, calculated using the model's input and output token pricing and the number of tokens used across evaluations (excluding repeats).
Context Window
Context Window
Larger context windows are relevant to RAG (Retrieval Augmented Generation) LLM workflows which typically involve reasoning and information retrieval of large amounts of data.
Maximum number of combined input & output tokens. Output tokens commonly have a significantly lower limit (varied by model).
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Pricing
Pricing: Input and Output Prices
Price per token included in the request/message sent to the API, represented as USD per million Tokens.
Figures represent performance of the model's first-party API (e.g. OpenAI for o1) or the median across providers where a first-party API is not available (e.g. Meta's Llama models).
Intelligence vs. Price (Log Scale)
While higher intelligence models are typically more expensive, they do not all follow the same price-quality curve.
Artificial Analysis Intelligence Index v4.0 includes: GDPval-AA, 𝜏²-Bench Telecom, Terminal-Bench Hard, SciCode, AA-LCR, AA-Omniscience, IFBench, Humanity's Last Exam, GPQA Diamond, CritPt. See Intelligence Index methodology for further details, including a breakdown of each evaluation and how we run them.
Price per token, represented as USD per million Tokens. Price is a blend of Input & Output token prices (3:1 ratio).
Figures represent performance of the model's first-party API (e.g. OpenAI for o1) or the median across providers where a first-party API is not available (e.g. Meta's Llama models).
Speed
Measured by Output Speed (tokens per second)
Output Speed
Tokens per second received while the model is generating tokens (ie. after first chunk has been received from the API for models which support streaming).
Figures represent performance of the model's first-party API (e.g. OpenAI for o1) or the median across providers where a first-party API is not available (e.g. Meta's Llama models).
{"@context":"https://schema.org","@type":"Dataset","name":"Output Speed","creator":{"@type":"Organization","name":"Artificial Analysis","url":"https://artificialanalysis.ai"},"description":"Output Tokens per Second; Higher is better","measurementTechnique":"Independent test run by Artificial Analysis on dedicated hardware.","spatialCoverage":"Worldwide","keywords":["analytics","llm","AI","benchmark","model","gpt","claude"],"license":"https://creativecommons.org/licenses/by/4.0/","isAccessibleForFree":true,"citation":"Artificial Analysis (2025). LLM benchmarks dataset. https://artificialanalysis.ai","data":""}
Output Speed vs. Price
Tokens per second received while the model is generating tokens (ie. after first chunk has been received from the API for models which support streaming).
Price per token, represented as USD per million Tokens. Price is a blend of Input & Output token prices (3:1 ratio).
Latency
Measured by Time (seconds) to First Token
Latency: Time To First Answer Token
Time to first answer token received, in seconds, after API request sent. For reasoning models, this includes the 'thinking' time of the model before providing an answer. For models which do not support streaming, this represents time to receive the completion.
End-to-End Response Time
Seconds to output 500 Tokens, calculated based on time to first token, 'thinking' time for reasoning models, and output speed
End-to-End Response Time
Seconds to receive a 500 token response. Key components:
- Input time: Time to receive the first response token
- Thinking time (only for reasoning models): Time reasoning models spend outputting tokens to reason prior to providing an answer. Amount of tokens based on the average reasoning tokens across a diverse set of 60 prompts (methodology details).
- Answer time: Time to generate 500 output tokens, based on output speed
Figures represent performance of the model's first-party API (e.g. OpenAI for o1) or the median across providers where a first-party API is not available (e.g. Meta's Llama models).
Model Size (Open Weights Models Only)
Model Size: Total and Active Parameters
The total number of trainable weights and biases in the model, expressed in billions. These parameters are learned during training and determine the model's ability to process and generate responses.
The number of parameters actually executed during each inference forward pass, expressed in billions. For Mixture of Experts (MoE) models, a routing mechanism selects a subset of experts per token, resulting in fewer active than total parameters. Dense models use all parameters, so active equals total.
Mistral
Mistral Small 3.2
Perplexity
R1 1776
TII UAE
Microsoft Azure
Liquid AI
Upstage
MiniMax
Kimi
Kimi K2 Thinking
Reka AI
Nous Research
DeepHermes 3 - Llama-3.1 8B Preview (Non-reasoning)
LG AI Research
EXAONE 4.0 32B (Reasoning)
Xiaomi
Baidu
Deep Cogito
Cogito v2.1 (Reasoning)
KwaiKAT
Prime Intellect
Motif Technologies
MBZUAI Institute of Foundation Models
Korea Telecom
Mi:dm K 2.5 Pro
Naver
HyperCLOVA X SEED Think (32B)
Z AI
Cohere
AI21 Labs
Alibaba
InclusionAI
Ling-mini-2.0
ByteDance Seed
OpenChat
OpenChat 3.5 (1210)
Databricks
DBRX Instruct
SnowflakeModels compared: OpenAI: GPT 4o Audio, GPT 4o Realtime, GPT 4o Speech Pipeline, GPT Realtime, GPT Realtime Mini (Oct '25), GPT-3.5 Turbo, GPT-3.5 Turbo (0125), GPT-3.5 Turbo (0301), GPT-3.5 Turbo (0613), GPT-3.5 Turbo (1106), GPT-3.5 Turbo Instruct, GPT-4, GPT-4 Turbo, GPT-4 Turbo (0125), GPT-4 Turbo (1106), GPT-4 Vision, GPT-4.1, GPT-4.1 mini, GPT-4.1 nano, GPT-4.5 (Preview), GPT-4o (Apr), GPT-4o (Aug), GPT-4o (ChatGPT), GPT-4o (Mar), GPT-4o (May), GPT-4o (Nov), GPT-4o Realtime (Dec), GPT-4o mini, GPT-4o mini Realtime (Dec), GPT-5 (ChatGPT), GPT-5 (high), GPT-5 (low), GPT-5 (medium), GPT-5 (minimal), GPT-5 Codex (high), GPT-5 Pro (high), GPT-5 mini (high), GPT-5 mini (medium), GPT-5 mini (minimal), GPT-5 nano (high), GPT-5 nano (medium), GPT-5 nano (minimal), GPT-5.1, GPT-5.1 (high), GPT-5.1 Codex (high), GPT-5.1 Codex mini (high), GPT-5.2, GPT-5.2 (high), GPT-5.2 (medium), GPT-5.2 (xhigh), GPT-5.2 Codex (xhigh), gpt-oss-120B (high), gpt-oss-120B (low), gpt-oss-20B (high), gpt-oss-20B (low), o1, o1-mini, o1-preview, o1-pro, o3, o3-mini, o3-mini (high), o3-pro, and o4-mini (high), Meta: Code Llama 70B, Llama 2 Chat 13B, Llama 2 Chat 70B, Llama 2 Chat 7B, Llama 3 70B, Llama 3 8B, Llama 3.1 405B, Llama 3.1 70B, Llama 3.1 8B, Llama 3.2 11B (Vision), Llama 3.2 1B, Llama 3.2 3B, Llama 3.2 90B (Vision), Llama 3.3 70B, Llama 4 Behemoth, Llama 4 Maverick, Llama 4 Scout, and Llama 65B, Google: Gemini 1.0 Pro, Gemini 1.0 Ultra, Gemini 1.5 Flash (May), Gemini 1.5 Flash (Sep), Gemini 1.5 Flash-8B, Gemini 1.5 Pro (May), Gemini 1.5 Pro (Sep), Gemini 2.0 Flash, Gemini 2.0 Flash (exp), Gemini 2.0 Flash Thinking exp. (Dec), Gemini 2.0 Flash Thinking exp. (Jan), Gemini 2.0 Flash-Lite (Feb), Gemini 2.0 Flash-Lite (Preview), Gemini 2.0 Pro Experimental, Gemini 2.5 Flash, Gemini 2.5 Flash Live Preview, Gemini 2.5 Flash Native Audio, Gemini 2.5 Flash Native Audio Dialog, Gemini 2.5 Flash (Sep), Gemini 2.5 Flash-Lite, Gemini 2.5 Flash-Lite (Sep), Gemini 2.5 Pro, Gemini 2.5 Pro (Mar), Gemini 2.5 Pro (May), Gemini 3 Flash, Gemini 3 Pro Preview (high), Gemini 3 Pro Preview (low), Gemini Experimental (Nov), Gemma 2 27B, Gemma 2 2B, Gemma 2 9B, Gemma 3 12B, Gemma 3 1B, Gemma 3 270M, Gemma 3 27B, Gemma 3 4B, Gemma 3n E2B, Gemma 3n E4B, Gemma 3n E4B (May), Gemma 7B, PALM-2, and Whisperwind, Anthropic: Claude 2.0, Claude 2.1, Claude 3 Haiku, Claude 3 Opus, Claude 3 Sonnet, Claude 3.5 Haiku, Claude 3.5 Sonnet (June), Claude 3.5 Sonnet (Oct), Claude 3.7 Sonnet, Claude 4 Opus, Claude 4 Sonnet, Claude 4.1 Opus, Claude 4.5 Haiku, Claude 4.5 Sonnet, Claude Instant, Claude Opus 4.5, claude-flan-v3-p, claude-flan-v3-p (low), and claude-flan-v3-p (medium), Mistral: Codestral (Jan), Codestral (May), Codestral-Mamba, Devstral 2, Devstral Medium, Devstral Small, Devstral Small (May), Devstral Small 2, Magistral Medium 1, Magistral Medium 1.1, Magistral Medium 1.2, Magistral Small 1, Magistral Small 1.1, Magistral Small 1.2, Ministral 3 14B, Ministral 3 3B, Ministral 3 8B, Ministral 3B, Ministral 8B, Mistral 7B, Mistral Large (Feb), Mistral Large 2 (Jul), Mistral Large 2 (Nov), Mistral Large 3, Mistral Medium, Mistral Medium 3, Mistral Medium 3.1, Mistral NeMo, Mistral Saba, Mistral Small (Feb), Mistral Small (Sep), Mistral Small 3, Mistral Small 3.1, Mistral Small 3.2, Mixtral 8x22B, Mixtral 8x7B, Pixtral 12B, and Pixtral Large, DeepSeek: DeepSeek Coder V2 Lite, DeepSeek LLM 67B (V1), DeepSeek Prover V2 671B, DeepSeek R1 (FP4), DeepSeek R1 (Jan), DeepSeek R1 0528, DeepSeek R1 0528 Qwen3 8B, DeepSeek R1 Distill Llama 70B, DeepSeek R1 Distill Llama 8B, DeepSeek R1 Distill Qwen 1.5B, DeepSeek R1 Distill Qwen 14B, DeepSeek R1 Distill Qwen 32B, DeepSeek V3 (Dec), DeepSeek V3 0324, DeepSeek V3.1, DeepSeek V3.1 Terminus, DeepSeek V3.2, DeepSeek V3.2 Exp, DeepSeek V3.2 Speciale, DeepSeek-Coder-V2, DeepSeek-OCR, DeepSeek-V2, DeepSeek-V2.5, DeepSeek-V2.5 (Dec), DeepSeek-VL2, and Janus Pro 7B, Perplexity: PPLX-70B Online, PPLX-7B-Online, R1 1776, Sonar, Sonar 3.1 Huge, Sonar 3.1 Large, Sonar 3.1 Small , Sonar Large, Sonar Pro, Sonar Reasoning, Sonar Reasoning Pro, and Sonar Small, TII UAE: Falcon-H1R-7B, xAI: Grok 2, Grok 3, Grok 3 Reasoning Beta, Grok 3 mini, Grok 3 mini Reasoning (low), Grok 3 mini Reasoning (high), Grok 4, Grok 4 Fast, Grok 4 Fast 1111 (Reasoning), Grok 4 mini (0908), Grok 4.1 Fast, Grok 4.1 Fast v4, Grok Beta, Grok Code Fast 1, Grok Voice Agent, Grok-1, and test model, OpenChat: OpenChat 3.5, Amazon: Nova 2.0 Lite, Nova 2.0 Lite (high), Nova 2.0 Lite (low), Nova 2.0 Lite (medium), Nova 2.0 Omni, Nova 2.0 Omni (high), Nova 2.0 Omni (low), Nova 2.0 Omni (medium), Nova 2.0 Pro Preview, Nova 2.0 Pro Preview (high), Nova 2.0 Pro Preview (low), Nova 2.0 Pro Preview (medium), Nova 2.0 Realtime, Nova 2.0 Sonic, Nova Lite, Nova Micro, Nova Premier, and Nova Pro, Microsoft Azure: Phi-3 Medium 14B, Phi-3 Mini, Phi-4, Phi-4 Mini, Phi-4 Multimodal, Phi-4 mini reasoning, Phi-4 reasoning, Phi-4 reasoning plus, Yosemite-1-1, Yosemite-1-1-d36, Yosemite 1.1 d36 Updated, Yosemite-1-1-d64, Yosemite 1.1 d64 Updated, and Yosemite, Liquid AI: LFM 1.3B, LFM 3B, LFM 40B, LFM2 1.2B, LFM2 2.6B, LFM2 8B A1B, LFM2.5-1.2B-Instruct, LFM2.5-1.2B-Thinking, and LFM2.5-VL-1.6B, Upstage: Solar Mini, Solar Open 100B, Solar Pro, Solar Pro (Nov), Solar Pro 2, and Solar Pro 2 , Databricks: DBRX, MiniMax: MiniMax M1 40k, MiniMax M1 80k, MiniMax-M2, MiniMax-M2.1, and MiniMax-Text-01, NVIDIA: Cosmos Nemotron 34B, Llama 3.1 Nemotron 70B, Llama 3.1 Nemotron Nano 4B v1.1, Llama 3.1 Nemotron Nano 8B, Llama 3.3 Nemotron Nano 8B, Llama Nemotron Ultra, Llama 3.3 Nemotron Super 49B, Llama Nemotron Super 49B v1.5, NVIDIA Nemotron 3 Nano, NVIDIA Nemotron Nano 12B v2 VL, NVIDIA Nemotron Nano 9B V2, and Nemotron Nano V3 (30B A3B), StepFun: Step-2, Step-2-Mini, Step-Audio R1.1 (Realtime), Step3, step-1-128k, step-1-256k, step-1-32k, step-1-8k, step-1-flash, step-2-16k-exp, and step-r1-v-mini, IBM: Granite 3.0 2B, Granite 3.0 8B, Granite 3.3 8B, Granite 4.0 1B, Granite 4.0 350M, Granite 4.0 8B, Granite 4.0 H 1B, Granite 4.0 H 350M, Granite 4.0 H Small, Granite 4.0 Micro, Granite 4.0 Tiny, and Granite Vision 3.3 2B, Inceptionlabs: Mercury, Mercury Coder Mini, Mercury Coder Small, and Mercury Instruct, Reka AI: Reka Core, Reka Edge, Reka Flash (Feb), Reka Flash, Reka Flash 3, and Reka Flash 3.1, LG AI Research: EXAONE 4.0 32B, EXAONE Deep 32B, Exaone 4.0 1.2B, and K-EXAONE, Xiaomi: MiMo 7B RL and MiMo-V2-Flash, Baidu: ERNIE 4.5, ERNIE 4.5 0.3B, ERNIE 4.5 21B A3B, ERNIE 4.5 300B A47B, ERNIE 4.5 VL 28B A3B, ERNIE 4.5 VL 424B A47B, ERNIE 5.0 Thinking Preview, and ERNIE X1, Baichuan: Baichuan 4 and Baichuan M1 (Preview), vercel: v0-1.0-md, Apple: Apple On-Device and FastVLM, Other: LLaVA-v1.5-7B, Tencent: Hunyuan A13B, Hunyuan 80B A13B, Hunyuan T1, and Hunyuan-TurboS, Prime Intellect: INTELLECT-3, Motif Technologies: Motif-2-12.7B, Korea Telecom: Mi:dm K 2.5 Pro and Mi:dm K 2.5 Pro Preview, Z AI: GLM-4 32B, GLM-4 9B, GLM-4-Air, GLM-4 AirX, GLM-4 FlashX, GLM-4-Long, GLM-4-Plus, GLM-4.1V 9B Thinking, GLM-4.5, GLM-4.5-Air, GLM-4.5V, GLM-4.6, GLM-4.6V, GLM-4.7, GLM-4.7-Flash, GLM-Z1 32B, GLM-Z1 9B, GLM-Z1 Rumination 32B, and GLM-Zero (Preview), Cohere: Aya Expanse 32B, Aya Expanse 8B, Command, Command A, Command Light, Command R7B, Command-R, Command-R (Mar), Command-R+ (Apr), and Command-R+, Bytedance: Duobao 1.5 Pro, Seed-Thinking-v1.5, Skylark Lite, and Skylark Pro, AI21 Labs: Jamba 1.5 Large, Jamba 1.5 Large (Feb), Jamba 1.5 Mini, Jamba 1.5 Mini (Feb), Jamba 1.6 Large, Jamba 1.6 Mini, Jamba 1.7 Large, Jamba 1.7 Mini, Jamba Instruct, and Jamba Reasoning 3B, Snowflake: Arctic and Snowflake Llama 3.3 70B, PaddlePaddle: PaddleOCR-VL-0.9B, Alibaba: QwQ-32B, QwQ 32B-Preview, Qwen Chat 14B, Qwen Chat 72B, Qwen Chat 7B, Qwen1.5 Chat 110B, Qwen1.5 Chat 14B, Qwen1.5 Chat 32B, Qwen1.5 Chat 72B, Qwen1.5 Chat 7B, Qwen2 72B, Qwen2 Instruct 7B, Qwen2 Instruct A14B 57B, Qwen2-VL 72B, Qwen2.5 Coder 32B, Qwen2.5 Coder 7B , Qwen2.5 Instruct 14B, Qwen2.5 Instruct 32B, Qwen2.5 72B, Qwen2.5 Instruct 7B, Qwen2.5 Max, Qwen2.5 Max 01-29, Qwen2.5 Omni 7B, Qwen2.5 Plus, Qwen2.5 Turbo, Qwen2.5 VL 72B, Qwen2.5 VL 7B, Qwen3 0.6B, Qwen3 1.7B, Qwen3 14B, Qwen3 235B, Qwen3 235B A22B 2507, Qwen3 235B 2507, Qwen3 30B, Qwen3 30B A3B 2507, Qwen3 32B, Qwen3 4B, Qwen3 4B 2507, Qwen3 8B, Qwen3 Coder 30B A3B, Qwen3 Coder 480B, Qwen3 Max, Qwen3 Max (Preview), Qwen3 Max Thinking, Qwen3 Next 80B A3B, Qwen3 Omni 30B A3B, Qwen3 VL 235B A22B, Qwen3 VL 30B A3B, Qwen3 VL 32B, Qwen3 VL 4B, and Qwen3 VL 8B, InclusionAI: Ling-1T, Ling-flash-2.0, Ling-mini-2.0, Ring-1T, and Ring-flash-2.0, 01.AI: Yi-Large and Yi-Lightning, and ByteDance Seed: Doubao Seed Code, Doubao-Seed-1.8, and Seed-OSS-36B-Instruct.