Type ranking

# Best Open-Source LLMs in October 2026

> Best Open-Source LLMs: As of October 2026, Kimi K3 leads the Noometry Index with a score of 59.5, ahead of GLM-5.3 at 54.8. 190 models ranked with sources.
- Canonical page: https://noometry.com/best/open-source
- Last updated: 2026-10-10
- Title: Best Open-Source LLMs (October 2026) | Noometry

As of October 2026, Kimi K3 leads the Noometry Index with a score of 59.5, ahead of GLM-5.3 at 54.8.

Last verified October 10, 2026

Models whose weights you can download and run yourself. Check each license for commercial terms.

Best Open-Source LLMs: top 10

1.  Kimi K3 59.5
2.  GLM-5.3 54.8
3.  DeepSeek V4 Pro 54.3
4.  DeepSeek V4 Flash 53.6
5.  DeepSeek V4.1 Flash 52.8
6.  GLM-5.3-Flash 51.8
7.  GLM-5.2 51.1
8.  MiMo-V2.6-Pro 50.3
9.  MiMo-V2.6-Flash 48.5
10.  Kimi K2.5 48.1
11.  45505560

## Full ranking

   190 models

Best Open-Source LLMs
|  |  |  |  |  |  |  |  |  |  |
| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- |
| 1 | Moonshot AI [Kimi K3](https://noometry.com/models/kimi-k3) | [Moonshot AI](https://noometry.com/providers/moonshot) | Open | 1.05M | 59.5 | $3 | $15 | 9.92 | — |
| 2 | Z.ai (Zhipu) [GLM-5.3](https://noometry.com/models/glm-5-3) | [Z.ai (Zhipu)](https://noometry.com/providers/zai) | Open | 1M | 54.8 | $1.40 | $4.40 | 25.5 | — |
| 3 |  ![](/logos/deepseek.svg) DeepSeek [DeepSeek V4 Pro](https://noometry.com/models/deepseek-v4-pro) | [DeepSeek](https://noometry.com/providers/deepseek) | Open | 1M | 54.3 | $0.66 | $1.98 | 54.9 | 16 |
| 4 |  ![](/logos/deepseek.svg) DeepSeek [DeepSeek V4 Flash](https://noometry.com/models/deepseek-v4-flash) | [DeepSeek](https://noometry.com/providers/deepseek) | Open | 1M | 53.6 | $0.15 | $0.60 | 204 | 6 |
| 5 |  ![](/logos/deepseek.svg) DeepSeek [DeepSeek V4.1 Flash](https://noometry.com/models/deepseek-v4-1-flash) | [DeepSeek](https://noometry.com/providers/deepseek) | Open | 1M | 52.8 | $0.15 | $0.60 | 201 | — |
| 6 | Z.ai (Zhipu) [GLM-5.3-Flash](https://noometry.com/models/glm-5-3-flash) | [Z.ai (Zhipu)](https://noometry.com/providers/zai) | Open | 1M | 51.8 | $0.15 | $0.50 | 218 | — |
| 7 | Z.ai (Zhipu) [GLM-5.2](https://noometry.com/models/glm-5-2) | [Z.ai (Zhipu)](https://noometry.com/providers/zai) | Open | 1M | 51.1 | $1.40 | $4.40 | 23.8 | 23 |
| 8 | Xiaomi [MiMo-V2.6-Pro](https://noometry.com/models/mimo-v2-6-pro) | [Xiaomi](https://noometry.com/providers/xiaomi) | Open | 1.05M | 50.3 | $0.43 | $0.87 | 92.5 | — |
| 9 | Xiaomi [MiMo-V2.6-Flash](https://noometry.com/models/mimo-v2-6-flash) | [Xiaomi](https://noometry.com/providers/xiaomi) | Open | 1.05M | 48.5 | $0.14 | $0.28 | 277 | — |
| 10 | Moonshot AI [Kimi K2.5](https://noometry.com/models/kimi-k2-5) | [Moonshot AI](https://noometry.com/providers/moonshot) | Open | 262K | 48.1 | $0.45 | $2.25 | 53.4 | 66 |
| 11 | Z.ai (Zhipu) [GLM-5.1](https://noometry.com/models/glm-5-1) | [Z.ai (Zhipu)](https://noometry.com/providers/zai) | Open | 200K | 47.8 | $1.40 | $4.40 | 22.2 | — |
| 12 | Moonshot AI [Kimi K2.6](https://noometry.com/models/kimi-k2-6) | [Moonshot AI](https://noometry.com/providers/moonshot) | Open | 262K | 47.7 | $0.95 | $4 | 27.8 | — |
| 13 | T Thinking Machines Lab [Inkling-Small](https://noometry.com/models/inkling-small) | [Thinking Machines Lab](https://noometry.com/providers/thinking-machines) | Open | 524K | 46.5 | $0.45 | $1.20 | 72.9 | — |
| 14 | Z.ai (Zhipu) [GLM-5](https://noometry.com/models/glm-5) | [Z.ai (Zhipu)](https://noometry.com/providers/zai) | Open | 205K | 46.1 | $1 | $3.20 | 29.7 | 23 |
| 15 |  ![](/logos/alibaba.svg) Alibaba (Qwen) [Qwen3.5 397B-A17B](https://noometry.com/models/qwen3-5-397b-a17b) | [Alibaba (Qwen)](https://noometry.com/providers/alibaba) | Open | 262K | 46.0 | $0.60 | $3.60 | 34.1 | 9 |
| 16 |  ![](/logos/alibaba.svg) Alibaba (Qwen) [Qwen3.8 27B](https://noometry.com/models/qwen3-8-27b) | [Alibaba (Qwen)](https://noometry.com/providers/alibaba) | Open | 262K | 46.0 | $0.99 | $1.49 | 41.2 | — |
| 17 | Moonshot AI [Kimi K2 Thinking Turbo](https://noometry.com/models/kimi-k2-thinking-turbo) | [Moonshot AI](https://noometry.com/providers/moonshot) | Open | — | 45.8 | — | — | — | — |
| 18 |  ![](/logos/tencent.svg) Tencent [Hy4 preview](https://noometry.com/models/hy4-preview) | [Tencent](https://noometry.com/providers/tencent) | Open | 1.05M | 45.3 | $0.75 | $2.25 | 40.2 | — |
| 19 | Xiaomi [MiMo-V2.5-Pro](https://noometry.com/models/mimo-v2-5-pro) | [Xiaomi](https://noometry.com/providers/xiaomi) | Open | 1.05M | 45.2 | $0.43 | $0.87 | 83.2 | — |
| 20 |  ![](/logos/deepseek.svg) DeepSeek [DeepSeek-V3.2-Exp](https://noometry.com/models/deepseek-v3-2-exp) | [DeepSeek](https://noometry.com/providers/deepseek) | Open | 164K | 44.3 | $0.26 | $0.38 | 153 | 16 |
| 21 |  ![](/logos/tencent.svg) Tencent [Hy3](https://noometry.com/models/hy3) | [Tencent](https://noometry.com/providers/tencent) | Open | 262K | 44.2 | $0.0825 | $0.33 | 306 | — |
| 22 | T Thinking Machines Lab [Inkling](https://noometry.com/models/inkling) | [Thinking Machines Lab](https://noometry.com/providers/thinking-machines) | Open | 66K | 44.1 | $1.87 | $4.68 | 17.1 | — |
| 23 |  ![](/logos/minimax.svg) MiniMax [MiniMax-M3](https://noometry.com/models/minimax-m3) | [MiniMax](https://noometry.com/providers/minimax) | Open | 1M | 43.8 | $0.30 | $1.20 | 83.4 | — |
| 24 | Moonshot AI [Kimi K2.5 Instant](https://noometry.com/models/kimi-k2-5-instant) | [Moonshot AI](https://noometry.com/providers/moonshot) | Open | — | 43.6 | — | — | — | — |
| 25 |  ![](/logos/google.svg) Google [Gemma 4 31B IT](https://noometry.com/models/gemma-4-31b-it) | [Google](https://noometry.com/providers/google) | Open | 262K | 43.5 | $0.09 | $0.34 | 286 | 3 |
| 26 |  ![](/logos/alibaba.svg) Alibaba (Qwen) [Qwen3 235B-A22B](https://noometry.com/models/qwen3-235b-a22b) | [Alibaba (Qwen)](https://noometry.com/providers/alibaba) | Open | 131K | 43.5 | $0.70 | $2.80 | 35.5 | 85 |
| 27 |  ![](/logos/google.svg) Google [Gemma 4 26B A4B IT](https://noometry.com/models/gemma-4-26b-a4b-it) | [Google](https://noometry.com/providers/google) | Open | 262K | 43.5 | $0.0675 | $0.23 | 407 | — |
| 28 | Xiaomi [MiMo-V2.5](https://noometry.com/models/mimo-v2-5) | [Xiaomi](https://noometry.com/providers/xiaomi) | Open | 1.05M | 43.4 | $0.14 | $0.28 | 248 | — |
| 29 | Moonshot AI [Kimi K2.7 Code](https://noometry.com/models/kimi-k2-7-code) | [Moonshot AI](https://noometry.com/providers/moonshot) | Open | 262K | 43.3 | $0.95 | $4 | 25.3 | — |
| 30 |  ![](/logos/alibaba.svg) Alibaba (Qwen) [Qwen3-VL 235B-A22B](https://noometry.com/models/qwen3-vl-235b-a22b) | [Alibaba (Qwen)](https://noometry.com/providers/alibaba) | Open | 131K | 43.2 | $0.70 | $2.80 | 35.3 | — |
| 31 |  ![](/logos/deepseek.svg) DeepSeek [DeepSeek-V3.1-Terminus](https://noometry.com/models/deepseek-v3-1-terminus) | [DeepSeek](https://noometry.com/providers/deepseek) | Open | 164K | 43.1 | $0.27 | $1 | 95.4 | 30 |
| 32 |  ![](/logos/alibaba.svg) Alibaba (Qwen) [Qwen3-Next 80B-A3B Instruct](https://noometry.com/models/qwen3-next-80b-a3b-instruct) | [Alibaba (Qwen)](https://noometry.com/providers/alibaba) | Open | 131K | 43.0 | $0.50 | $2 | 49.2 | 111 |
| 33 |  ![](/logos/deepseek.svg) DeepSeek [DeepSeek-V3.1](https://noometry.com/models/deepseek-v3-1) | [DeepSeek](https://noometry.com/providers/deepseek) | Open | 164K | 42.8 | $0.25 | $0.95 | 101 | 328 |
| 34 |  ![](/logos/nvidia.svg) NVIDIA [Nemotron 3 Ultra](https://noometry.com/models/nemotron-3-ultra) | [NVIDIA](https://noometry.com/providers/nvidia) | Open | 262K | 42.5 | $0.50 | $2.20 | 45.9 | — |
| 35 |  ![](/logos/stepfun.svg) StepFun [Step 3.5 Flash](https://noometry.com/models/step-3-5-flash) | [StepFun](https://noometry.com/providers/stepfun) | Open | 256K | 42.3 | $0.10 | $0.30 | 282 | — |
| 36 |  ![](/logos/alibaba.svg) Alibaba (Qwen) [Qwen3.6 27B](https://noometry.com/models/qwen3-6-27b) | [Alibaba (Qwen)](https://noometry.com/providers/alibaba) | Open | 262K | 42.2 | $0.60 | $3.60 | 31.3 | — |
| 37 |  ![](/logos/alibaba.svg) Alibaba (Qwen) [Qwen3.5 122B-A10B](https://noometry.com/models/qwen3-5-122b-a10b) | [Alibaba (Qwen)](https://noometry.com/providers/alibaba) | Open | 262K | 42.1 | $0.40 | $3.20 | 38.3 | — |
| 38 | Meituan [Longcat Flash Chat](https://noometry.com/models/longcat-flash-chat) | [Meituan](https://noometry.com/providers/meituan) | Open | — | 42.1 | — | — | — | 69 |
| 39 | Z.ai (Zhipu) [GLM-4.5](https://noometry.com/models/glm-4-5) | [Z.ai (Zhipu)](https://noometry.com/providers/zai) | Open | 131K | 42.0 | $0.60 | $2.20 | 42 | 32 |
| 40 |  ![](/logos/alibaba.svg) Alibaba (Qwen) [Qwen3.5 35B-A3B](https://noometry.com/models/qwen3-5-35b-a3b) | [Alibaba (Qwen)](https://noometry.com/providers/alibaba) | Open | 262K | 42.0 | $0.25 | $2 | 61 | — |
| 41 | Z.ai (Zhipu) [GLM-4.7](https://noometry.com/models/glm-4-7) | [Z.ai (Zhipu)](https://noometry.com/providers/zai) | Open | 205K | 42.0 | $0.60 | $2.20 | 42 | — |
| 42 |  ![](/logos/alibaba.svg) Alibaba (Qwen) [Qwen3.5 27B](https://noometry.com/models/qwen3-5-27b) | [Alibaba (Qwen)](https://noometry.com/providers/alibaba) | Open | 262K | 41.9 | $0.30 | $2.40 | 50.7 | — |
| 43 | IBM [Granite 4.2 30b](https://noometry.com/models/granite-4-2-30b) | [IBM](https://noometry.com/providers/ibm) | Open | — | 41.8 | — | — | — | — |
| 44 |  ![](/logos/meta.svg) Meta [Muse Glimmer](https://noometry.com/models/muse-glimmer) | [Meta](https://noometry.com/providers/meta) | Open | — | 41.7 | — | — | — | — |
| 45 | Z.ai (Zhipu) [GLM-4.6](https://noometry.com/models/glm-4-6) | [Z.ai (Zhipu)](https://noometry.com/providers/zai) | Open | 205K | 41.4 | $0.60 | $2.20 | 41.4 | 12 |
| 46 | Z.ai (Zhipu) [GLM-4.6V](https://noometry.com/models/glm-4-6v) | [Z.ai (Zhipu)](https://noometry.com/providers/zai) | Open | 128K | 41.3 | $0.30 | $0.90 | 91.8 | — |
| 47 | Xiaomi [MiMo-V2-Flash](https://noometry.com/models/mimo-v2-flash) | [Xiaomi](https://noometry.com/providers/xiaomi) | Open | 262K | 41.3 | $0.14 | $0.28 | 236 | — |
| 48 | Moonshot AI [Kimi K2 (Jul 2025)](https://noometry.com/models/kimi-k2) | [Moonshot AI](https://noometry.com/providers/moonshot) | Open | 262K | 41.2 | $0.57 | $2.30 | 41.1 | 201 |
| 49 |  ![](/logos/nvidia.svg) NVIDIA [Nemotron 3 Nano 30B A3B](https://noometry.com/models/nemotron-3-nano-30b-a3b) | [NVIDIA](https://noometry.com/providers/nvidia) | Open | 262K | 40.6 | $0.05 | $0.20 | 464 | — |
| 50 | IBM [Granite 4.2 8B](https://noometry.com/models/granite-4-2-8b) | [IBM](https://noometry.com/providers/ibm) | Open | 131K | 40.5 | $0.06 | $0.25 | 377 | — |
| 51 |  ![](/logos/stepfun.svg) StepFun [Step 3](https://noometry.com/models/step-3) | [StepFun](https://noometry.com/providers/stepfun) | Open | — | 40.5 | — | — | — | 7 |
| 52 |  ![](/logos/minimax.svg) MiniMax [MiniMax M1](https://noometry.com/models/minimax-m1) | [MiniMax](https://noometry.com/providers/minimax) | Open | 1M | 40.3 | $0.55 | $2.20 | 41.9 | — |
| 53 |  ![](/logos/nvidia.svg) NVIDIA [Nvidia Llama 3.3 Nemotron Super 49b v1.5](https://noometry.com/models/nvidia-llama-3-3-nemotron-super-49b-v1-5) | [NVIDIA](https://noometry.com/providers/nvidia) | Open | 131K | 40.3 | $0.40 | $0.40 | 101 | — |
| 54 |  ![](/logos/mistral.svg) Mistral AI [Mistral Medium 3.5](https://noometry.com/models/mistral-medium-3-5) | [Mistral AI](https://noometry.com/providers/mistral) | Open | 262K | 40.2 | $1.50 | $7.50 | 13.4 | 50 |
| 55 |  ![](/logos/nvidia.svg) NVIDIA [Nemotron 3 Super](https://noometry.com/models/nemotron-3-super) | [NVIDIA](https://noometry.com/providers/nvidia) | Open | 262K | 40.1 | $0.08 | $0.45 | 233 | — |
| 56 |  ![](/logos/nvidia.svg) NVIDIA [Llama 3.3 Nemotron 49b Super v1](https://noometry.com/models/llama-3-3-nemotron-49b-super-v1) | [NVIDIA](https://noometry.com/providers/nvidia) | Open | — | 40.1 | — | — | — | — |
| 57 |  ![](/logos/nvidia.svg) NVIDIA [Nemotron 3.5 Lightning](https://noometry.com/models/nemotron-3-5-lightning) | [NVIDIA](https://noometry.com/providers/nvidia) | Open | 262K | 40.0 | $0.05 | $0.20 | 457 | — |
| 58 | Z.ai (Zhipu) [GLM-4.5V](https://noometry.com/models/glm-4-5v) | [Z.ai (Zhipu)](https://noometry.com/providers/zai) | Open | 64K | 39.8 | $0.60 | $1.80 | 44.2 | 34 |
| 59 |  ![](/logos/alibaba.svg) Alibaba (Qwen) [QwQ-32B](https://noometry.com/models/qwq-32b) | [Alibaba (Qwen)](https://noometry.com/providers/alibaba) | Open | — | 39.8 | — | — | — | — |
| 60 |  ![](/logos/deepseek.svg) DeepSeek [DeepSeek-V3.2-Speciale](https://noometry.com/models/deepseek-v3-2-speciale) | [DeepSeek](https://noometry.com/providers/deepseek) | Open | 128K | 39.7 | $0.58 | $1.68 | 46.4 | — |
| 61 |  ![](/logos/deepseek.svg) DeepSeek [DeepSeek-V3](https://noometry.com/models/deepseek-v3) | [DeepSeek](https://noometry.com/providers/deepseek) | Open | 164K | 39.5 | $0.24 | $0.90 | 97.5 | 73 |
| 62 |  ![](/logos/ai2.svg) Allen Institute for AI (Ai2) [Olmo 3.1 32b Instruct](https://noometry.com/models/olmo-3-1-32b-instruct) | [Allen Institute for AI (Ai2)](https://noometry.com/providers/ai2) | Open | — | 39.4 | — | — | — | — |
| 63 | IBM [Granite 4.2 3b](https://noometry.com/models/granite-4-2-3b) | [IBM](https://noometry.com/providers/ibm) | Open | — | 39.4 | — | — | — | — |
| 64 |  ![](/logos/alibaba.svg) Alibaba (Qwen) [Qwen3 32B](https://noometry.com/models/qwen3-32b) | [Alibaba (Qwen)](https://noometry.com/providers/alibaba) | Open | 131K | 39.2 | $0.70 | $2.80 | 32 | 86 |
| 65 |  ![](/logos/ai2.svg) Allen Institute for AI (Ai2) [Molmo 2 8b](https://noometry.com/models/molmo-2-8b) | [Allen Institute for AI (Ai2)](https://noometry.com/providers/ai2) | Open | — | 39.1 | — | — | — | — |
| 66 |  ![](/logos/mistral.svg) Mistral AI [Mistral Large 3](https://noometry.com/models/mistral-large-3) | [Mistral AI](https://noometry.com/providers/mistral) | Open | 262K | 39.1 | $0.25 | $0.75 | 104 | 7 |
| 67 | Z.ai (Zhipu) [GLM-4.5-Air](https://noometry.com/models/glm-4-5-air) | [Z.ai (Zhipu)](https://noometry.com/providers/zai) | Open | 131K | 38.9 | $0.20 | $1.10 | 91.6 | 160 |
| 68 |  ![](/logos/minimax.svg) MiniMax [MiniMax-M2.1](https://noometry.com/models/minimax-m2-1) | [MiniMax](https://noometry.com/providers/minimax) | Open | 205K | 38.9 | $0.30 | $1.20 | 74.2 | — |
| 69 |  ![](/logos/alibaba.svg) Alibaba (Qwen) [Qwen3-30B-A3B](https://noometry.com/models/qwen3-30b-a3b) | [Alibaba (Qwen)](https://noometry.com/providers/alibaba) | Open | 41K | 38.9 | $0.12 | $0.50 | 181 | 42 |
| 70 | Z.ai (Zhipu) [GLM-4.7-Flash](https://noometry.com/models/glm-4-7-flash) | [Z.ai (Zhipu)](https://noometry.com/providers/zai) | Open | 200K | 38.8 | $0.06 | $0.40 | 268 | — |
| 71 |  ![](/logos/ai2.svg) Allen Institute for AI (Ai2) [Olmo 3 32b Think](https://noometry.com/models/olmo-3-32b-think) | [Allen Institute for AI (Ai2)](https://noometry.com/providers/ai2) | Open | — | 38.7 | — | — | — | — |
| 72 |  ![](/logos/arcee.svg) Arcee AI [Trinity Large Thinking](https://noometry.com/models/trinity-large-thinking) | [Arcee AI](https://noometry.com/providers/arcee) | Open | 262K | 38.6 | $0.25 | $0.80 | 99.7 | — |
| 73 |  ![](/logos/minimax.svg) MiniMax [MiniMax-M2.5](https://noometry.com/models/minimax-m2-5) | [MiniMax](https://noometry.com/providers/minimax) | Open | 205K | 38.3 | $0.30 | $1.20 | 73 | 49 |
| 74 |  ![](/logos/alibaba.svg) Alibaba (Qwen) [Qwen3-Coder 480B-A35B Instruct](https://noometry.com/models/qwen3-coder-480b-a35b-instruct) | [Alibaba (Qwen)](https://noometry.com/providers/alibaba) | Open | 262K | 38.1 | $1.50 | $7.50 | 12.7 | 67 |
| 75 |  ![](/logos/ai2.svg) Allen Institute for AI (Ai2) [Olmo 3.1 32b Think](https://noometry.com/models/olmo-3-1-32b-think) | [Allen Institute for AI (Ai2)](https://noometry.com/providers/ai2) | Open | — | 37.9 | — | — | — | — |
| 76 |  ![](/logos/deepseek.svg) DeepSeek [DeepSeek-R1-Distill-Llama-70B](https://noometry.com/models/deepseek-r1-distill-llama-70b) | [DeepSeek](https://noometry.com/providers/deepseek) | Open | — | 37.8 | — | — | — | 18 |
| 77 |  ![](/logos/minimax.svg) MiniMax [MiniMax-M2.7](https://noometry.com/models/minimax-m2-7) | [MiniMax](https://noometry.com/providers/minimax) | Open | 205K | 37.7 | $0.30 | $1.20 | 71.9 | — |
| 78 |  ![](/logos/deepseek.svg) DeepSeek [DeepSeek-V2.5 (Sep 2024)](https://noometry.com/models/deepseek-v2-5) | [DeepSeek](https://noometry.com/providers/deepseek) | Open | — | 37.6 | — | — | — | — |
| 79 |  ![](/logos/alibaba.svg) Alibaba (Qwen) [Qwen3.6 35B-A3B](https://noometry.com/models/qwen3-6-35b-a3b) | [Alibaba (Qwen)](https://noometry.com/providers/alibaba) | Open | 262K | 37.6 | $0.25 | $1.49 | 67.5 | — |
| 80 |  ![](/logos/nvidia.svg) NVIDIA [Llama 3.1 Nemotron 70b Instruct](https://noometry.com/models/llama-3-1-nemotron-70b-instruct) | [NVIDIA](https://noometry.com/providers/nvidia) | Open | — | 37.6 | — | — | — | — |
| 81 |  ![](/logos/minimax.svg) MiniMax [MiniMax-M2](https://noometry.com/models/minimax-m2) | [MiniMax](https://noometry.com/providers/minimax) | Open | 205K | 37.4 | $0.30 | $1.20 | 71.2 | 17 |
| 82 | IBM [Granite 4.1 8b](https://noometry.com/models/granite-4-1-8b) | [IBM](https://noometry.com/providers/ibm) | Open | — | 37.4 | — | — | — | — |
| 83 |  ![](/logos/google.svg) Google [Gemma 3n E4b IT](https://noometry.com/models/gemma-3n-e4b-it) | [Google](https://noometry.com/providers/google) | Open | — | 37.3 | — | — | — | 13 |
| 84 |  ![](/logos/stepfun.svg) StepFun [Step 3.7 Flash](https://noometry.com/models/step-3-7-flash) | [StepFun](https://noometry.com/providers/stepfun) | Open | 256K | 37.3 | $0.18 | $1.11 | 89.6 | — |
| 85 |  ![](/logos/nvidia.svg) NVIDIA [Llama 3.1 Nemotron Ultra 253b v1](https://noometry.com/models/llama-3-1-nemotron-ultra-253b-v1) | [NVIDIA](https://noometry.com/providers/nvidia) | Open | — | 36.7 | — | — | — | — |
| 86 | IBM [Granite 4.0 H Small](https://noometry.com/models/ibm-granite-h-small) | [IBM](https://noometry.com/providers/ibm) | Open | — | 36.5 | — | — | — | — |
| 87 |  ![](/logos/cohere.svg) Cohere [Command A](https://noometry.com/models/command-a) | [Cohere](https://noometry.com/providers/cohere) | Open | 256K | 36.5 | $2.50 | $10 | 8.33 | 28 |
| 88 | OpenAI [gpt-oss-120b](https://noometry.com/models/gpt-oss-120b) | [OpenAI](https://noometry.com/providers/openai) | Open | 131K | 36.3 | $0.037 | $0.17 | 517 | 55 |
| 89 |  ![](/logos/mistral.svg) Mistral AI [Mistral Medium](https://noometry.com/models/mistral-medium) | [Mistral AI](https://noometry.com/providers/mistral) | Open | 262K | 36.3 | $1.50 | $7.50 | 12.1 | 68 |
| 90 |  ![](/logos/deepseek.svg) DeepSeek [Deepseek Coder v2](https://noometry.com/models/deepseek-coder-v2) | [DeepSeek](https://noometry.com/providers/deepseek) | Open | — | 35.9 | — | — | — | — |
| 91 |  ![](/logos/cohere.svg) Cohere [C4ai Aya Expanse 32b](https://noometry.com/models/c4ai-aya-expanse-32b) | [Cohere](https://noometry.com/providers/cohere) | Open | 128K | 35.9 | — | — | — | — |
| 92 |  ![](/logos/nvidia.svg) NVIDIA [Llama 3.1 Nemotron 51b Instruct](https://noometry.com/models/llama-3-1-nemotron-51b-instruct) | [NVIDIA](https://noometry.com/providers/nvidia) | Open | — | 35.9 | — | — | — | — |
| 93 |  ![](/logos/nvidia.svg) NVIDIA [Nemotron 4 340b Instruct](https://noometry.com/models/nemotron-4-340b-instruct) | [NVIDIA](https://noometry.com/providers/nvidia) | Open | — | 35.9 | — | — | — | — |
| 94 |  ![](/logos/ai2.svg) Allen Institute for AI (Ai2) [Llama 3.1 Tulu 3 8b](https://noometry.com/models/llama-3-1-tulu-3-8b) | [Allen Institute for AI (Ai2)](https://noometry.com/providers/ai2) | Open | — | 35.7 | — | — | — | — |
| 95 |  ![](/logos/alibaba.svg) Alibaba (Qwen) [Qwen3 14B](https://noometry.com/models/qwen3-14b) | [Alibaba (Qwen)](https://noometry.com/providers/alibaba) | Open | 131K | 35.5 | $0.35 | $1.40 | 57.9 | 79 |
| 96 |  ![](/logos/deepseek.svg) DeepSeek [DeepSeek-R1-Distill-Qwen-32B](https://noometry.com/models/deepseek-r1-distill-qwen-32b) | [DeepSeek](https://noometry.com/providers/deepseek) | Open | — | 35.5 | — | — | — | — |
| 97 |  ![](/logos/mistral.svg) Mistral AI [Magistral Medium](https://noometry.com/models/magistral-medium) | [Mistral AI](https://noometry.com/providers/mistral) | Open | 262K | 35.2 | $2 | $5 | 12.8 | 0 |
| 98 |  ![](/logos/cohere.svg) Cohere [C4ai Aya Expanse 8b](https://noometry.com/models/c4ai-aya-expanse-8b) | [Cohere](https://noometry.com/providers/cohere) | Open | — | 34.9 | — | — | — | — |
| 99 |  ![](/logos/alibaba.svg) Alibaba (Qwen) [Qwen3 Coder Next](https://noometry.com/models/qwen3-coder-next) | [Alibaba (Qwen)](https://noometry.com/providers/alibaba) | Open | 262K | 34.3 | $0.12 | $0.80 | 118 | — |
| 100 |  ![](/logos/mistral.svg) Mistral AI [Devstral Small 2505](https://noometry.com/models/devstral-small) | [Mistral AI](https://noometry.com/providers/mistral) | Open | 128K | 34.3 | $0.10 | $0.30 | 229 | 88 |
| 101 |  ![](/logos/alibaba.svg) Alibaba (Qwen) [Qwen1.5-110B](https://noometry.com/models/qwen1-5-110b) | [Alibaba (Qwen)](https://noometry.com/providers/alibaba) | Open | — | 34.2 | — | — | — | — |
| 102 |  ![](/logos/alibaba.svg) Alibaba (Qwen) [Qwen3.5-9B](https://noometry.com/models/qwen3-5-9b) | [Alibaba (Qwen)](https://noometry.com/providers/alibaba) | Open | 262K | 33.8 | $0.10 | $0.15 | 300 | — |
| 103 |  ![](/logos/meta.svg) Meta [Codellama 70b Instruct](https://noometry.com/models/codellama-70b-instruct) | [Meta](https://noometry.com/providers/meta) | Open | — | 33.7 | — | — | — | — |
| 104 |  ![](/logos/alibaba.svg) Alibaba (Qwen) [Qwen3 8B](https://noometry.com/models/qwen3-8b) | [Alibaba (Qwen)](https://noometry.com/providers/alibaba) | Open | 131K | 33.7 | $0.18 | $0.70 | 109 | — |
| 105 |  ![](/logos/mistral.svg) Mistral AI [Mistral Small](https://noometry.com/models/mistral-small) | [Mistral AI](https://noometry.com/providers/mistral) | Open | 262K | 33.4 | $0.15 | $0.60 | 127 | 120 |
| 106 |  ![](/logos/alibaba.svg) Alibaba (Qwen) [Qwen2.5-Coder-32B](https://noometry.com/models/qwen2-5-coder-32b) | [Alibaba (Qwen)](https://noometry.com/providers/alibaba) | Open | 33K | 33.4 | $0.66 | $1 | 44.8 | — |
| 107 | IBM [Granite 3.1 2b Instruct](https://noometry.com/models/granite-3-1-2b-instruct) | [IBM](https://noometry.com/providers/ibm) | Open | — | 33.2 | — | — | — | — |
| 108 |  ![](/logos/google.svg) Google [Gemma 2 2b IT](https://noometry.com/models/gemma-2-2b-it) | [Google](https://noometry.com/providers/google) | Open | — | 33.1 | — | — | — | — |
| 109 |  ![](/logos/microsoft.svg) Microsoft [Wizardlm 70b](https://noometry.com/models/wizardlm-70b) | [Microsoft](https://noometry.com/providers/microsoft) | Open | — | 33.0 | — | — | — | — |
| 110 |  ![](/logos/microsoft.svg) Microsoft [Phi 3 Medium 4k Instruct](https://noometry.com/models/phi-3-medium-4k-instruct) | [Microsoft](https://noometry.com/providers/microsoft) | Open | — | 33.0 | — | — | — | — |
| 111 |  ![](/logos/ai2.svg) Allen Institute for AI (Ai2) [Tulu 3 (Tülu 3) 70B](https://noometry.com/models/tulu-3-70b) | [Allen Institute for AI (Ai2)](https://noometry.com/providers/ai2) | Open | — | 33.0 | — | — | — | — |
| 112 |  ![](/logos/deepseek.svg) DeepSeek [DeepSeek-R1-Distill-Qwen-14B](https://noometry.com/models/deepseek-r1-distill-qwen-14b) | [DeepSeek](https://noometry.com/providers/deepseek) | Open | — | 32.7 | — | — | — | — |
| 113 |  ![](/logos/alibaba.svg) Alibaba (Qwen) [Qwen1.5-14B](https://noometry.com/models/qwen1-5-14b) | [Alibaba (Qwen)](https://noometry.com/providers/alibaba) | Open | — | 32.7 | — | — | — | — |
| 114 |  ![](/logos/ai2.svg) Allen Institute for AI (Ai2) [Olmo 2 0325 32b Instruct](https://noometry.com/models/olmo-2-0325-32b-instruct) | [Allen Institute for AI (Ai2)](https://noometry.com/providers/ai2) | Open | — | 32.7 | — | — | — | — |
| 115 | OpenAI [gpt-oss-20b](https://noometry.com/models/gpt-oss-20b) | [OpenAI](https://noometry.com/providers/openai) | Open | 131K | 32.5 | $0.018 | $0.09 | 903 | 96 |
| 116 |  ![](/logos/poolside.svg) Poolside [Laguna M.1](https://noometry.com/models/laguna-m-1) | [Poolside](https://noometry.com/providers/poolside) | Open | 262K | 32.5 | — | — | — | — |
| 117 |  ![](/logos/cohere.svg) Cohere [Command R+](https://noometry.com/models/command-r-plus) | [Cohere](https://noometry.com/providers/cohere) | Open | 128K | 32.4 | $2.50 | $10 | 7.41 | — |
| 118 | IBM [Granite 3.1 8b Instruct](https://noometry.com/models/granite-3-1-8b-instruct) | [IBM](https://noometry.com/providers/ibm) | Open | — | 32.4 | — | — | — | — |
| 119 |  ![](/logos/mistral.svg) Mistral AI [Pixtral Large](https://noometry.com/models/pixtral-large) | [Mistral AI](https://noometry.com/providers/mistral) | Open | 128K | 32.2 | $2 | $6 | 10.7 | — |
| 120 |  ![](/logos/tii.svg) Technology Innovation Institute [Falcon-180B](https://noometry.com/models/falcon-180b) | [Technology Innovation Institute](https://noometry.com/providers/tii) | Open | — | 32.2 | — | — | — | — |
| 121 |  ![](/logos/google.svg) Google [Gemma 3 12B](https://noometry.com/models/gemma-3-12b) | [Google](https://noometry.com/providers/google) | Open | 131K | 32.1 | $0.05 | $0.15 | 428 | — |
| 122 |  ![](/logos/mistral.svg) Mistral AI [Mistral Large](https://noometry.com/models/mistral-large) | [Mistral AI](https://noometry.com/providers/mistral) | Open | 131K | 31.9 | $2 | $6 | 10.6 | — |
| 123 |  ![](/logos/alibaba.svg) Alibaba (Qwen) [Qwen3-4B](https://noometry.com/models/qwen3-4b) | [Alibaba (Qwen)](https://noometry.com/providers/alibaba) | Open | — | 31.9 | — | — | — | — |
| 124 |  ![](/logos/alibaba.svg) Alibaba (Qwen) [Qwen2.5 72B Instruct](https://noometry.com/models/qwen2-5-72b-instruct) | [Alibaba (Qwen)](https://noometry.com/providers/alibaba) | Open | 131K | 31.9 | $1.40 | $5.60 | 13 | — |
| 125 |  ![](/logos/nvidia.svg) NVIDIA [Llama2 70b Steerlm Chat](https://noometry.com/models/llama2-70b-steerlm-chat) | [NVIDIA](https://noometry.com/providers/nvidia) | Open | — | 31.8 | — | — | — | — |
| 126 |  ![](/logos/mistral.svg) Mistral AI [Mistral Small 3.1](https://noometry.com/models/mistral-small-3-1) | [Mistral AI](https://noometry.com/providers/mistral) | Open | 128K | 31.7 | $0.35 | $0.56 | 78.8 | — |
| 127 | IBM [Granite 3.0 8b Instruct](https://noometry.com/models/granite-3-0-8b-instruct) | [IBM](https://noometry.com/providers/ibm) | Open | — | 31.6 | — | — | — | — |
| 128 |  ![](/logos/cohere.svg) Cohere [Command R](https://noometry.com/models/command-r) | [Cohere](https://noometry.com/providers/cohere) | Open | 128K | 31.4 | $0.15 | $0.60 | 120 | — |
| 129 |  ![](/logos/alibaba.svg) Alibaba (Qwen) [Qwen1.5-7B](https://noometry.com/models/qwen1-5-7b) | [Alibaba (Qwen)](https://noometry.com/providers/alibaba) | Open | — | 31.4 | — | — | — | — |
| 130 |  ![](/logos/microsoft.svg) Microsoft [Wizardlm 13b](https://noometry.com/models/wizardlm-13b) | [Microsoft](https://noometry.com/providers/microsoft) | Open | — | 31.4 | — | — | — | — |
| 131 |  ![](/logos/alibaba.svg) Alibaba (Qwen) [Qwen-14B](https://noometry.com/models/qwen-14b) | [Alibaba (Qwen)](https://noometry.com/providers/alibaba) | Open | — | 31.4 | — | — | — | — |
| 132 |  ![](/logos/microsoft.svg) Microsoft [Phi 3 Mini 4k Instruct June 2024](https://noometry.com/models/phi-3-mini-4k-instruct-june) | [Microsoft](https://noometry.com/providers/microsoft) | Open | — | 31.3 | — | — | — | — |
| 133 |  ![](/logos/google.svg) Google [Gemma 1.1 7b IT](https://noometry.com/models/gemma-1-1-7b-it) | [Google](https://noometry.com/providers/google) | Open | — | 31.3 | — | — | — | — |
| 134 |  ![](/logos/mistral.svg) Mistral AI [Mistral Small 3](https://noometry.com/models/mistral-small-3) | [Mistral AI](https://noometry.com/providers/mistral) | Open | 33K | 31.2 | $0.05 | $0.08 | 543 | — |
| 135 |  ![](/logos/microsoft.svg) Microsoft [Phi-4](https://noometry.com/models/phi-4) | [Microsoft](https://noometry.com/providers/microsoft) | Open | 128K | 31.2 | $0.07 | $0.14 | 357 | — |
| 136 |  ![](/logos/mistral.svg) Mistral AI [Mistral Small 3.2](https://noometry.com/models/mistral-small-3-2) | [Mistral AI](https://noometry.com/providers/mistral) | Open | 256K | 31.2 | $0.0938 | $0.25 | 235 | 68 |
| 137 |  ![](/logos/meta.svg) Meta [Llama 4 Maverick](https://noometry.com/models/llama-4-maverick) | [Meta](https://noometry.com/providers/meta) | Open | 128K | 30.9 | $0.19 | $0.65 | 102 | 456 |
| 138 |  ![](/logos/microsoft.svg) Microsoft [Phi-4 Mini](https://noometry.com/models/phi-4-mini) | [Microsoft](https://noometry.com/providers/microsoft) | Open | 128K | 30.9 | $0.075 | $0.30 | 235 | — |
| 139 |  ![](/logos/google.svg) Google [Gemma 3 27B](https://noometry.com/models/gemma-3-27b) | [Google](https://noometry.com/providers/google) | Open | 131K | 30.8 | $0.08 | $0.16 | 308 | 62 |
| 140 |  ![](/logos/alibaba.svg) Alibaba (Qwen) [Qwen1.5-72B](https://noometry.com/models/qwen1-5-72b) | [Alibaba (Qwen)](https://noometry.com/providers/alibaba) | Open | — | 30.8 | — | — | — | — |
| 141 | IBM [Granite 3.0 2b Instruct](https://noometry.com/models/granite-3-0-2b-instruct) | [IBM](https://noometry.com/providers/ibm) | Open | — | 30.8 | — | — | — | — |
| 142 |  ![](/logos/meta.svg) Meta [Codellama 34b Instruct](https://noometry.com/models/codellama-34b-instruct) | [Meta](https://noometry.com/providers/meta) | Open | — | 30.8 | — | — | — | — |
| 143 |  ![](/logos/meta.svg) Meta [Llama 3.1-405B](https://noometry.com/models/llama-3-1-405b) | [Meta](https://noometry.com/providers/meta) | Open | — | 30.7 | — | — | — | 78 |
| 144 | 01.AI [Yi-1.5-34B](https://noometry.com/models/yi-1-5-34b) | [01.AI](https://noometry.com/providers/01-ai) | Open | — | 30.6 | — | — | — | — |
| 145 |  ![](/logos/meta.svg) Meta [Llama-3.3-70B-Instruct](https://noometry.com/models/llama-3-3-70b-instruct) | [Meta](https://noometry.com/providers/meta) | Open | 128K | 30.6 | $0.10 | $0.32 | 197 | — |
| 146 |  ![](/logos/alibaba.svg) Alibaba (Qwen) [Qwen1.5-32B](https://noometry.com/models/qwen1-5-32b) | [Alibaba (Qwen)](https://noometry.com/providers/alibaba) | Open | — | 30.5 | — | — | — | — |
| 147 |  ![](/logos/ai2.svg) Allen Institute for AI (Ai2) [Olmo 7b Instruct](https://noometry.com/models/olmo-7b-instruct) | [Allen Institute for AI (Ai2)](https://noometry.com/providers/ai2) | Open | — | 30.3 | — | — | — | — |
| 148 |  ![](/logos/mistral.svg) Mistral AI [Magistral Small](https://noometry.com/models/magistral-small) | [Mistral AI](https://noometry.com/providers/mistral) | Open | 128K | 30.2 | $0.50 | $1.50 | 40.3 | 0 |
| 149 |  ![](/logos/alibaba.svg) Alibaba (Qwen) [Qwen2.5 32B Instruct](https://noometry.com/models/qwen2-5-32b-instruct) | [Alibaba (Qwen)](https://noometry.com/providers/alibaba) | Open | 131K | 30.1 | $0.70 | $2.80 | 24.6 | — |
| 150 |  ![](/logos/google.svg) Google [Gemma 7B](https://noometry.com/models/gemma-7b) | [Google](https://noometry.com/providers/google) | Open | — | 30.0 | — | — | — | — |
| 151 |  ![](/logos/alibaba.svg) Alibaba (Qwen) [Qwen2-72B](https://noometry.com/models/qwen2-72b) | [Alibaba (Qwen)](https://noometry.com/providers/alibaba) | Open | — | 30.0 | — | — | — | — |
| 152 |  ![](/logos/alibaba.svg) Alibaba (Qwen) [Qwen2.5-VL 72B Instruct](https://noometry.com/models/qwen2-5-vl-72b-instruct) | [Alibaba (Qwen)](https://noometry.com/providers/alibaba) | Open | 131K | 29.9 | $2.80 | $8.40 | 7.13 | 43 |
| 153 |  ![](/logos/ai2.svg) Allen Institute for AI (Ai2) [OLMo 2 Furious 13B](https://noometry.com/models/olmo-2-furious-13b) | [Allen Institute for AI (Ai2)](https://noometry.com/providers/ai2) | Open | — | 29.7 | — | — | — | — |
| 154 |  ![](/logos/microsoft.svg) Microsoft [Phi 3 Mini 128k Instruct](https://noometry.com/models/phi-3-mini-128k-instruct) | [Microsoft](https://noometry.com/providers/microsoft) | Open | — | 29.7 | — | — | — | — |
| 155 |  ![](/logos/microsoft.svg) Microsoft [phi-3-medium 14B](https://noometry.com/models/phi-3-medium-14b) | [Microsoft](https://noometry.com/providers/microsoft) | Open | — | 29.7 | — | — | — | — |
| 156 |  ![](/logos/google.svg) Google [Gemma 2B](https://noometry.com/models/gemma-2b) | [Google](https://noometry.com/providers/google) | Open | — | 29.6 | — | — | — | — |
| 157 |  ![](/logos/meta.svg) Meta [Llama 3.1-70B](https://noometry.com/models/llama-3-1-70b) | [Meta](https://noometry.com/providers/meta) | Open | 128K | 29.6 | $0.40 | $0.40 | 74.1 | — |
| 158 |  ![](/logos/meta.svg) Meta [Llama 2-13B](https://noometry.com/models/llama-2-13b) | [Meta](https://noometry.com/providers/meta) | Open | — | 29.6 | — | — | — | — |
| 159 |  ![](/logos/databricks.svg) Databricks [DBRX](https://noometry.com/models/dbrx) | [Databricks](https://noometry.com/providers/databricks) | Open | — | 29.4 | — | — | — | — |
| 160 |  ![](/logos/google.svg) Google [Gemma 2 27B](https://noometry.com/models/gemma-2-27b) | [Google](https://noometry.com/providers/google) | Open | 8K | 29.4 | $0.65 | $0.65 | 45.2 | — |
| 161 |  ![](/logos/google.svg) Google [Gemma 1.1 2b IT](https://noometry.com/models/gemma-1-1-2b-it) | [Google](https://noometry.com/providers/google) | Open | — | 29.3 | — | — | — | — |
| 162 |  ![](/logos/microsoft.svg) Microsoft [Phi 3 Small 8k Instruct](https://noometry.com/models/phi-3-small-8k-instruct) | [Microsoft](https://noometry.com/providers/microsoft) | Open | — | 29.3 | — | — | — | — |
| 163 |  ![](/logos/meta.svg) Meta [Llama 2-7B](https://noometry.com/models/llama-2-7b) | [Meta](https://noometry.com/providers/meta) | Open | — | 29.1 | — | — | — | — |
| 164 | IBM [Granite 4.0 Micro](https://noometry.com/models/granite-4-0-micro) | [IBM](https://noometry.com/providers/ibm) | Open | 131K | 29.0 | $0.017 | $0.11 | 713 | — |
| 165 |  ![](/logos/alibaba.svg) Alibaba (Qwen) [Qwen2.5 7B Instruct](https://noometry.com/models/qwen2-5-7b-instruct) | [Alibaba (Qwen)](https://noometry.com/providers/alibaba) | Open | 131K | 29.0 | $0.17 | $0.70 | 94.6 | — |
| 166 |  ![](/logos/meta.svg) Meta [Llama 3.2 3B](https://noometry.com/models/llama-3-2-3b) | [Meta](https://noometry.com/providers/meta) | Open | 131K | 28.9 | $0.05 | $0.33 | 241 | — |
| 167 |  ![](/logos/alibaba.svg) Alibaba (Qwen) [Qwen1.5 4b Chat](https://noometry.com/models/qwen1-5-4b-chat) | [Alibaba (Qwen)](https://noometry.com/providers/alibaba) | Open | — | 28.8 | — | — | — | — |
| 168 |  ![](/logos/meta.svg) Meta [Llama 3-70B](https://noometry.com/models/llama-3-70b) | [Meta](https://noometry.com/providers/meta) | Open | — | 28.8 | — | — | — | 104 |
| 169 |  ![](/logos/mistral.svg) Mistral AI [Ministral 8B](https://noometry.com/models/ministral-8b) | [Mistral AI](https://noometry.com/providers/mistral) | Open | 262K | 28.2 | $0.15 | $0.15 | 188 | — |
| 170 |  ![](/logos/google.svg) Google [Gemma 3 4B](https://noometry.com/models/gemma-3-4b) | [Google](https://noometry.com/providers/google) | Open | 131K | 28.1 | $0.04 | $0.08 | 563 | 72 |
| 171 |  ![](/logos/microsoft.svg) Microsoft [Phi 3 Mini 4k Instruct](https://noometry.com/models/phi-3-mini-4k-instruct) | [Microsoft](https://noometry.com/providers/microsoft) | Open | — | 27.9 | — | — | — | — |
| 172 | 01.AI [Yi-34B](https://noometry.com/models/yi-34b) | [01.AI](https://noometry.com/providers/01-ai) | Open | — | 27.8 | — | — | — | — |
| 173 |  ![](/logos/meta.svg) Meta [Llama 4 Scout](https://noometry.com/models/llama-4-scout) | [Meta](https://noometry.com/providers/meta) | Open | 128K | 27.7 | $0.10 | $0.30 | 184 | 272 |
| 174 |  ![](/logos/meta.svg) Meta [Llama 3.2 90B](https://noometry.com/models/llama-3-2-90b) | [Meta](https://noometry.com/providers/meta) | Open | — | 27.5 | — | — | — | — |
| 175 |  ![](/logos/mistral.svg) Mistral AI [Mixtral 8x22B](https://noometry.com/models/mixtral-8x22b) | [Mistral AI](https://noometry.com/providers/mistral) | Open | 64K | 27.1 | $2 | $6 | 9.05 | — |
| 176 |  ![](/logos/mistral.svg) Mistral AI [Mixtral 8x7B](https://noometry.com/models/mixtral-8x7b) | [Mistral AI](https://noometry.com/providers/mistral) | Open | 32K | 27.1 | $0.70 | $0.70 | 38.8 | — |
| 177 |  ![](/logos/alibaba.svg) Alibaba (Qwen) [Qwen3-1.7B](https://noometry.com/models/qwen3-1-7b) | [Alibaba (Qwen)](https://noometry.com/providers/alibaba) | Open | — | 26.6 | — | — | — | — |
| 178 |  ![](/logos/mistral.svg) Mistral AI [Mistral Nemo](https://noometry.com/models/mistral-nemo) | [Mistral AI](https://noometry.com/providers/mistral) | Open | 128K | 26.4 | $0.15 | $0.15 | 176 | — |
| 179 |  ![](/logos/mistral.svg) Mistral AI [Ministral 3B](https://noometry.com/models/ministral-3b) | [Mistral AI](https://noometry.com/providers/mistral) | Open | 131K | 26.2 | $0.10 | $0.10 | 262 | — |
| 180 |  ![](/logos/deepseek.svg) DeepSeek [DeepSeek-R1-Distill-Qwen-1.5B](https://noometry.com/models/deepseek-r1-distill-qwen-1-5b) | [DeepSeek](https://noometry.com/providers/deepseek) | Open | — | 26.1 | — | — | — | — |
| 181 |  ![](/logos/google.svg) Google [Gemma 2 9B](https://noometry.com/models/gemma-2-9b) | [Google](https://noometry.com/providers/google) | Open | — | 25.9 | — | — | — | — |
| 182 |  ![](/logos/databricks.svg) Databricks [Dolly 2.0-12b](https://noometry.com/models/dolly-2-0-12b) | [Databricks](https://noometry.com/providers/databricks) | Open | — | 25.5 | — | — | — | — |
| 183 |  ![](/logos/meta.svg) Meta [Llama 3-8B](https://noometry.com/models/llama-3-8b) | [Meta](https://noometry.com/providers/meta) | Open | — | 25.5 | — | — | — | — |
| 184 |  ![](/logos/deepseek.svg) DeepSeek [DeepSeek LLM 67B](https://noometry.com/models/deepseek-llm-67b) | [DeepSeek](https://noometry.com/providers/deepseek) | Open | — | 24.9 | — | — | — | — |
| 185 |  ![](/logos/meta.svg) Meta [Llama 13b](https://noometry.com/models/llama-13b) | [Meta](https://noometry.com/providers/meta) | Open | — | 24.4 | — | — | — | — |
| 186 |  ![](/logos/meta.svg) Meta [Llama 2-70B](https://noometry.com/models/llama-2-70b) | [Meta](https://noometry.com/providers/meta) | Open | — | 24.4 | — | — | — | — |
| 187 |  ![](/logos/mistral.svg) Mistral AI [Mistral 7B](https://noometry.com/models/mistral-7b) | [Mistral AI](https://noometry.com/providers/mistral) | Open | 8K | 23.0 | $0.25 | $0.25 | 92.2 | — |
| 188 |  ![](/logos/meta.svg) Meta [Llama 3.1-8B](https://noometry.com/models/llama-3-1-8b) | [Meta](https://noometry.com/providers/meta) | Open | 128K | 23.0 | $0.05 | $0.08 | 400 | — |
| 189 |  ![](/logos/google.svg) Google [Gemma 3 1B](https://noometry.com/models/gemma-3-1b) | [Google](https://noometry.com/providers/google) | Open | — | 21.1 | — | — | — | — |
| 190 |  ![](/logos/meta.svg) Meta [Llama 3.2 1B](https://noometry.com/models/llama-3-2-1b) | [Meta](https://noometry.com/providers/meta) | Open | 60K | 20.1 | $0.027 | $0.20 | 286 | — |

Sponsored placements are available on pages like this one. [Advertise on Noometry](https://noometry.com/advertise)

## Compare the leaders

-   [Kimi K3 vs GLM-5.3](https://noometry.com/compare/glm-5-3-vs-kimi-k3)
-   [Kimi K3 vs DeepSeek V4 Pro](https://noometry.com/compare/deepseek-v4-pro-vs-kimi-k3)
-   [Kimi K3 vs DeepSeek V4 Flash](https://noometry.com/compare/deepseek-v4-flash-vs-kimi-k3)
-   [GLM-5.3 vs DeepSeek V4 Pro](https://noometry.com/compare/deepseek-v4-pro-vs-glm-5-3)
-   [GLM-5.3 vs DeepSeek V4 Flash](https://noometry.com/compare/deepseek-v4-flash-vs-glm-5-3)
-   [DeepSeek V4 Pro vs DeepSeek V4 Flash](https://noometry.com/compare/deepseek-v4-flash-vs-deepseek-v4-pro)

## Related rankings

-   [Best AI Models Overall](https://noometry.com/best/overall)
-   [Best Proprietary LLMs](https://noometry.com/best/proprietary)
-   [Best Reasoning Models](https://noometry.com/best/reasoning-models)
-   [Best Non-Reasoning LLMs](https://noometry.com/best/non-reasoning-models)
-   [Best New AI Models](https://noometry.com/best/newest)

## Frequently asked questions

### What is the best open-source LLM?

As of October 2026, Kimi K3 leads the Noometry Index with a score of 59.5, ahead of GLM-5.3 at 54.8.

### What are the top 5 in this ranking?

Kimi K3, GLM-5.3, DeepSeek V4 Pro, DeepSeek V4 Flash, DeepSeek V4.1 Flash, in that order, as of October 2026.

### How is this list ranked?

By the Noometry Index, which is fitted from every public benchmark result and adjusted for how hard each benchmark is. Models need several independent results to be ranked.

### Cite this page

Noometry. (2026). Best Open-Source LLMs. Retrieved October 10, 2026, from https://noometry.com/best/open-source

Quote Noometry with a link back to this page. It is also available in [Markdown](https://noometry.com/md/best/open-source.md).