1,011 models · refreshed nightly
Text generation models
Every model in the catalog with its licence, estimated VRAM and daily-tracked downloads. Filters update the URL — share any view.
| # | Model | Params | Context | Commercial use | 30d | Min VRAM |
|---|---|---|---|---|---|---|
| 01 | Qwen3-0.6B | 750 M | 41 K | ✓ apache-2.0 | 29.7 M | from 2.3 GB |
| 02 | opt-125m | — | 2 K | other | 18.5 M | — |
| 03 | Qwen3-8B | 8.2 B | 41 K | ✓ apache-2.0 | 16.3 M | from 19.7 GB |
| 04 | Qwen2.5-1.5B-Instruct | 1.5 B | 33 K | ✓ apache-2.0 | 14.0 M | from 4.1 GB |
| 05 | gpt2 | 140 M | — | ✓ mit | 13.7 M | from 1.1 GB |
| 06 | Qwen2.5-7B-Instruct | 7.6 B | 33 K | ✓ apache-2.0 | 12.1 M | from 18.4 GB |
| 07 | Qwen3.6-35B-A3B-NVFP4 | 18.7 B | — | ✓ apache-2.0 | 11.3 M | from 29.1 GB |
| 08 | Llama-3.2-1B-Instruct | 1.2 B | — | ⚠ llama3.2 | 10.4 M | from 3.4 GB |
| 09 | DeepSeek-R1 | 684.5 B | 164 K | ✓ mit | 9.9 M | from 860.6 GB |
| 10 | gpt-oss-20b | 21.5 B | 131 K | ✓ apache-2.0 | 8.6 M | from 34.0 GB |
| 11 | Qwen3-32B | 32.8 B | 41 K | ✓ apache-2.0 | 8.3 M | from 77.5 GB |
| 12 | Llama-3.1-8B-Instruct | 8.0 B | — | ⚠ llama3.1 | 8.0 M | from 19.4 GB |
| 13 | Qwen3-1.7B | 2.0 B | 41 K | ✓ apache-2.0 | 7.8 M | from 5.3 GB |
| 14 | Qwen2.5-0.5B-Instruct | 490 M | 33 K | ✓ apache-2.0 | 6.6 M | from 1.7 GB |
| 15 | Qwen2.5-3B-Instruct | 3.1 B | 33 K | other | 6.0 M | from 7.8 GB |
| 16 | Ornith-1.0-9B-GGUF | — | — | ✓ mit | 4.9 M | from 6.7 GB |
| 17 | Ornith-1.0-9B-GGUF | — | — | ✓ mit | 4.9 M | from 6.7 GB |
| 18 | gemma-3-1b-it | 1.0 B | — | ⚠ gemma | 4.7 M | from 2.8 GB |
| 19 | Qwen3-Coder-30B-A3B-Instruct-GGUF | — | — | ✓ apache-2.0 | 4.7 M | from 12.9 GB |
| 20 | OTel-LLM-E4B-IT | — | — | ✓ apache-2.0 | 4.7 M | — |
| 21 | Qwen2.5-7B-Instruct-AWQ | 7.6 B | 33 K | ✓ apache-2.0 | 4.6 M | from 7.8 GB |
| 22 | dolphin-2.9.1-yi-1.5-34b | 34.4 B | 8 K | ✓ apache-2.0 | 4.6 M | from 81.3 GB |
| 23 | Qwen3-4B | 4.0 B | 41 K | ✓ apache-2.0 | 4.6 M | from 10.0 GB |
| 24 | gpt-oss-120b | 120.4 B | 131 K | ✓ apache-2.0 | 4.2 M | from 162.1 GB |
| 25 | granite-4.1-8b | 8.8 B | 131 K | ✓ apache-2.0 | 4.2 M | from 21.2 GB |
| 26 | Ornith-1.0-35B-GGUF | — | — | ✓ mit | 3.8 M | from 23.8 GB |
| 27 | Ornith-1.0-35B-GGUF | — | — | ✓ mit | 3.8 M | from 23.8 GB |
| 28 | Qwen2.5-14B-Instruct | 14.8 B | 33 K | ✓ apache-2.0 | 3.3 M | from 35.2 GB |
| 29 | OTel-2.0-LLM-31B-IT | 32.1 B | 262 K | ✓ apache-2.0 | 3.3 M | from 76.0 GB |
| 30 | Qwen3-4B-Instruct-2507 | 4.0 B | 262 K | ✓ apache-2.0 | 3.2 M | from 10.0 GB |
| 31 | Qwen2-1.5B-Instruct | 1.5 B | 33 K | ✓ apache-2.0 | 3.2 M | from 4.1 GB |
| 32 | Qwen3-30B-A3B | 30.5 B | 41 K | ✓ apache-2.0 | 3.1 M | from 72.3 GB |
| 33 | Qwen2.5-Coder-14B-Instruct | 14.8 B | 33 K | ✓ apache-2.0 | 3.0 M | from 35.2 GB |
| 34 | Qwen3-14B | 14.8 B | 41 K | ✓ apache-2.0 | 2.8 M | from 35.2 GB |
| 35 | Ornith-1.0-35B | 0 M | — | ✓ mit | 2.8 M | from 77.7 GB |
| 36 | Ornith-1.0-35B | 0 M | — | ✓ mit | 2.8 M | from 77.7 GB |
| 37 | NVIDIA-Nemotron-3-Super-120B-A12B-NVFP4 | 67.2 B | 262 K | other | 2.8 M | from 98.9 GB |
| 38 | Gemma-4-31B-IT-NVFP4 | 20.9 B | — | other | 2.8 M | from 39.5 GB |
| 39 | DeepSeek-V4-Flash | 158.1 B | 1.0 M | ✓ mit | 2.7 M | from 199.8 GB |
| 40 | GLM-5.2-FP8 | 753.4 B | 1.0 M | ✓ mit | 2.7 M | from 944.7 GB |
| 41 | distilgpt2 | 90 M | — | ✓ apache-2.0 | 2.6 M | from 0.9 GB |
| 42 | Bonsai-27B-gguf | — | — | ✓ apache-2.0 | 2.6 M | from 1.2 GB |
| 43 | Qwen2.5-0.5B | 490 M | 33 K | ✓ apache-2.0 | 2.6 M | from 1.7 GB |
| 44 | TinyLlama-1.1B-Chat-v1.0 | 1.1 B | 2 K | ✓ apache-2.0 | 2.5 M | from 3.1 GB |
| 45 | Qwen2.5-14B-Instruct-AWQ | 14.8 B | 33 K | ✓ apache-2.0 | 2.5 M | from 13.7 GB |
| 46 | pythia-160m | 210 M | 2 K | ✓ apache-2.0 | 2.5 M | from 0.9 GB |
| 47 | Qwen3-14B-AWQ | 14.8 B | 41 K | ✓ apache-2.0 | 2.4 M | from 13.7 GB |
| 48 | Ornith-1.0-9B | 0 M | — | ✓ mit | 2.4 M | from 21.2 GB |
| 49 | Ornith-1.0-9B | 0 M | — | ✓ mit | 2.4 M | from 21.2 GB |
| 50 | GLM-5.2 | 753.3 B | 1.0 M | ✓ mit | 2.2 M | from 1,770.8 GB |
VRAM figures are estimates for the smallest available quantization at 8K context — see /methodology. Downloads refresh nightly from the Hugging Face API.