All tracked LLMs
70 open-weight models with benchmarks and hardware requirements.
This is the complete catalogue of open-weight large language models tracked by CanItRun. For each model you can see the exact VRAM needed at every quantization level (FP16 down to Q2_K), the estimated inference speed in tokens per second on any GPU we track, and benchmark scores from the Open LLM Leaderboard v2 and LMSYS Chatbot Arena.
Models range from sub-1B edge models to 1T+ parameter frontier models. Use the homepage calculator to filter by your specific hardware, or browse below to compare models by parameter count. Each model page shows the full compatibility breakdown across all {60+} GPUs we track.
Parameters
License
Releaser
70 models
- DeepSeek V4 Pro 1.6TDeepSeek · 1600B params · 1024k context · MITMMLU-Pro 87.5
- Kimi K2.6Moonshot AI · 1000B params · 250k context · KimiMMLU-Pro 87.2
- GLM-5.1 754BZ.ai · 754B params · 198k context · MITMMLU-Pro 86.5
- GLM-5 744BZ.ai · 744B params · 198k context · MITMMLU-Pro 85.7
- DeepSeek V3 671BDeepSeek · 671B params · 125k context · MITMMLU-Pro 75.9
- DeepSeek R1 671BDeepSeek · 671B params · 125k context · MITMMLU-Pro 85.0
- MiniMax M1 456BMiniMax · 456B params · 1024k context · Apache 2.0MMLU-Pro 81.1
- Llama 3.1 405B InstructMeta · 405B params · 125k context · Llama 3.1 CommunityMMLU-Pro 73.3
- Llama 4 Maverick 400BMeta · 400B params · 977k context · Llama 4 CommunityMMLU-Pro 80.5
- GLM-4.7 358BZ.ai · 358B params · 198k context · MITMMLU-Pro 84.3
- GLM-4.5 355BZ.ai · 355B params · 128k context · MITMMLU-Pro 84.6
- GLM-4.6 355BZ.ai · 355B params · 198k context · MITMMLU-Pro 84.5
- DeepSeek V4 Flash 284BDeepSeek · 284B params · 1024k context · MITMMLU-Pro 86.3
- Qwen3 235B-A22B (MoE)Alibaba · 235B params · 128k context · Apache 2.0MMLU-Pro 84.4
- MiniMax M2.5 229BMiniMax · 229B params · 192k context · MiniMaxMMLU-Pro 84.8
- MiniMax M2.7 229BMiniMax · 229B params · 200k context · MiniMaxMMLU-Pro 86.0
- Mixtral 8x22B Instruct v0.1Mistral AI · 141B params · 64k context · Apache 2.0MMLU-Pro 40.0
- Qwen 3.5 122B-A10B (MoE)Alibaba · 122B params · 256k context · Apache 2.0MMLU-Pro 86.7
- Nemotron 3 Super 120BNVIDIA · 120B params · 1024k context · NVIDIAMMLU-Pro 83.7
- GPT-OSS 120BOpenAI · 117B params · 128k context · Apache 2.0MMLU-Pro 80.7
- Llama 4 Scout 109BMeta · 109B params · 9766k context · Llama 4 CommunityMMLU-Pro 74.3
- GLM-4.5 Air 106BZ.ai · 106B params · 128k context · MITMMLU-Pro 81.4
- GLM-4.6V 106BZ.ai · 106B params · 128k context · MITMMLU-Pro 79.9
- Qwen 2.5 72B InstructAlibaba · 72B params · 125k context · QwenMMLU-Pro 71.1
- Llama 3.3 70B InstructMeta · 70B params · 125k context · Llama 3.3 CommunityMMLU-Pro 68.9
- DeepSeek R1 Distill Llama 70BDeepSeek · 70B params · 125k context · MITMMLU-Pro 70.0
- Llama 3.1 70B InstructMeta · 70B params · 125k context · Llama 3.1 CommunityMMLU-Pro 66.4
- Mixtral 8x7B Instruct v0.1Mistral AI · 46.7B params · 32k context · Apache 2.0MMLU-Pro 29.7
- Command-R 35BCohere · 35B params · 125k context · CC-BY-NC 4.0MMLU-Pro 33.0
- Qwen 3.5 35B-A3B (MoE)Alibaba · 35B params · 256k context · Apache 2.0MMLU-Pro 84.2
- Qwen 3.6 35BAlibaba · 35B params · 256k context · Apache 2.0MMLU-Pro 85.2
- Yi 1.5 34B Chat01.AI · 34.4B params · 32k context · Apache 2.0MMLU-Pro 37.0
- Qwen3 32BAlibaba · 32.8B params · 128k context · Apache 2.0MMLU-Pro 65.5
- Qwen 2.5 32B InstructAlibaba · 32.5B params · 125k context · Apache 2.0MMLU-Pro 69.0
- Qwen 2.5 Coder 32B InstructAlibaba · 32.5B params · 125k context · Apache 2.0MMLU-Pro 50.4
- DeepSeek R1 Distill Qwen 32BDeepSeek · 32.5B params · 125k context · MITMMLU-Pro 65.0
- Nemotron 3 Nano 30BNVIDIA · 32B params · 1024k context · NVIDIAMMLU-Pro 78.3
- Gemma 4 31BGoogle · 31B params · 250k context · Apache 2.0MMLU-Pro 85.2
- Qwen3 30B-A3B (MoE)Alibaba · 30B params · 128k context · Apache 2.0MMLU-Pro 61.5
- Gemma 2 27B InstructGoogle · 27.2B params · 8k context · GemmaMMLU-Pro 38.0
- Gemma 3 27B InstructGoogle · 27B params · 128k context · GemmaMMLU-Pro 67.5
- Qwen 3.6 27BAlibaba · 27B params · 256k context · Apache 2.0MMLU-Pro 86.2
- Gemma 4 26B (MoE)Google · 26B params · 250k context · Apache 2.0MMLU-Pro 82.6
- Mistral Small 3.1 24B InstructMistral AI · 24B params · 128k context · Apache 2.0MMLU-Pro 66.8
- Mistral Small 22BMistral AI · 22.2B params · 32k context · Mistral ResearchMMLU-Pro 49.2
- GPT-OSS 20BOpenAI · 21B params · 128k context · Apache 2.0MMLU-Pro 67.9
- Qwen3 14BAlibaba · 14.8B params · 128k context · Apache 2.0MMLU-Pro 61.0
- Qwen 2.5 14B InstructAlibaba · 14.7B params · 125k context · Apache 2.0MMLU-Pro 63.7
- Phi-4 14B InstructMicrosoft · 14B params · 16k context · MITMMLU-Pro 70.4
- Mistral Nemo 12B InstructMistral AI · 12.2B params · 125k context · Apache 2.0MMLU-Pro 35.6
- Gemma 3 12B InstructGoogle · 12.2B params · 128k context · GemmaMMLU-Pro 60.6
- Gemma 2 9B InstructGoogle · 9.2B params · 8k context · GemmaMMLU-Pro 32.0
- Llama 3.1 8B InstructMeta · 8B params · 125k context · Llama 3.1 CommunityMMLU-Pro 48.3
- DeepSeek R1 Distill Llama 8BDeepSeek · 8B params · 125k context · MITMMLU-Pro 41.0
- Qwen3 8BAlibaba · 8B params · 128k context · Apache 2.0MMLU-Pro 56.7
- Qwen 2.5 7B InstructAlibaba · 7.6B params · 125k context · Apache 2.0MMLU-Pro 56.3
- Mistral 7B Instruct v0.3Mistral AI · 7.25B params · 32k context · Apache 2.0MMLU-Pro 30.0
- Gemma 3 4B InstructGoogle · 4B params · 128k context · GemmaMMLU-Pro 43.6
- Gemma 4 E4BGoogle · 4B params · 125k context · Apache 2.0MMLU-Pro 69.4
- Phi-3.5 Mini InstructMicrosoft · 3.8B params · 125k context · MITMMLU-Pro 47.4
- Llama 3.2 3B InstructMeta · 3.2B params · 125k context · Llama 3.2 CommunityMMLU-Pro 24.0
- Qwen 2.5 3B InstructAlibaba · 3.1B params · 32k context · Qwen ResearchMMLU-Pro 32.4
- Gemma 2 2B InstructGoogle · 2.6B params · 8k context · GemmaMMLU-Pro 17.8
- Gemma 4 E2BGoogle · 2B params · 125k context · Apache 2.0MMLU-Pro 60.0
- SmolLM2 1.7B InstructHugging Face · 1.7B params · 8k context · Apache 2.0MMLU-Pro 19.0
- Qwen 2.5 1.5B InstructAlibaba · 1.5B params · 32k context · Apache 2.0MMLU-Pro 16.8
- Llama 3.2 1B InstructMeta · 1.24B params · 125k context · Llama 3.2 CommunityMMLU-Pro 12.5
- Gemma 3 1B InstructGoogle · 1B params · 32k context · GemmaMMLU-Pro 14.7
- Qwen 2.5 0.5B InstructAlibaba · 0.5B params · 32k context · Apache 2.0MMLU-Pro 10.0
- SmolLM2 360M InstructHugging Face · 0.36B params · 8k context · Apache 2.0MMLU-Pro 8.0