1,423 models · 1,213 open weights · 210 API-only · refreshed nightly
Models that run on 2 × 24 GB
Every model in the catalog — open weights you can self-host and API-only models — with licence or API price, estimated VRAM and daily-tracked downloads. Filters update the URL — share any view.
| # | Model | Params | Context | Commercial use | 30d | On 2 × 24 GB |
|---|---|---|---|---|---|---|
| 51 | Qwen3-4B | 4.0 B | 41 K | ✓ apache-2.0 | 4.0 M | 10.0 GB |
| 52 | Qwen3.6-35B-A3B-NVFP4 | 18.7 B | — | ✓ apache-2.0 | 4.0 M | 29.1 GB |
| 53 | Qwen3.6-35B-A3B-FP8 | 36.0 B | — | ✓ apache-2.0 | 4.0 M | 47.1 GB |
| 54 | Huihui-Qwen3.8-27B-abliterated-GGUF | 27.0 B | — | ✓ apache-2.0 | 3.9 M | 16.5 GB |
| 55 | Ornith-1.0-35B-GGUF | — | — | ✓ mit | 3.8 M | 23.8 GB |
| 56 | Qwen3-VL-4B-Instruct | 4.4 B | — | ✓ apache-2.0 | 3.7 M | 10.9 GB |
| 57 | Qwen3.5-2B | 2.3 B | — | ✓ apache-2.0 | 3.7 M | 5.8 GB |
| 58 | Qwen3-1.7B | 2.0 B | 41 K | ✓ apache-2.0 | 3.7 M | 5.3 GB |
| 59 | tf_efficientnetv2_s.in21k_ft_in1k | 20 M | — | ✓ apache-2.0 | 3.6 M | 0.6 GB |
| 60 | indonesian-roberta-base-posp-tagger | 120 M | 512 | ✓ mit | 3.6 M | 1.1 GB |
| 61 | snowflake-arctic-embed-l-v2.0 | 570 M | 8 K | ✓ apache-2.0 | 3.6 M | 3.1 GB |
| 62 | Qwen3.5-0.8B | 870 M | — | ✓ apache-2.0 | 3.5 M | 2.6 GB |
| 63 | OmniVoice | 610 M | — | unknown | 3.5 M | 4.2 GB |
| 64 | whisper-large-v3 | 1.5 B | — | ✓ apache-2.0 | 3.5 M | 10.9 GB |
| 65 | pythia-160m | 210 M | 2 K | ✓ apache-2.0 | 3.5 M | 0.9 GB |
| 66 | Bangla-twoclass-Sentiment-Analyzer | 280 M | 512 | ✓ mit | 3.4 M | 1.8 GB |
| 67 | Qwen3.8-27B-iMatrix-NVFP4-MTP-GGUF | — | — | ✓ apache-2.0 | 3.3 M | 19.3 GB |
| 68 | finbert | 110 M | 512 | ✗ cc-by-nc-sa-4.0 | 3.3 M | 1.0 GB |
| 69 | OTel-2.0-Decision-26B-A4B-4bit | 25.8 B | — | ✓ apache-2.0 | 3.2 M | 22.8 GB |
| 70 | bge-small-zh-v1.5 | 20 M | 512 | ✓ mit | 3.1 M | 0.6 GB |
| 71 | Tiel-Coder-35B-A3B-GGUF-MTP | 35.0 B | — | ✓ mit | 3.1 M | 19.7 GB |
| 72 | Qwen3.8-27B-MLX-4bit | 4.7 B | — | ✓ apache-2.0 | 3.0 M | 18.9 GB |
| 73 | distilbert-base-uncased-finetuned-sst-2-english | 70 M | 512 | ✓ apache-2.0 | 2.9 M | 0.8 GB |
| 74 | bge-base-en-v1.5-course-recommender-v5 | 110 M | 512 | unknown | 2.9 M | 1.0 GB |
| 75 | Qwen3.8-27B-MLX-8bit | 8.0 B | — | ✓ apache-2.0 | 2.9 M | 34.2 GB |
| 76 | Qwen3.8-27B-MLX-6bit | 6.4 B | — | ✓ apache-2.0 | 2.9 M | 26.5 GB |
| 77 | Qwen3.8-27B-MLX-5bit | 5.5 B | — | ✓ apache-2.0 | 2.9 M | 22.7 GB |
| 78 | t5-base | 220 M | — | ✓ apache-2.0 | 2.8 M | 1.5 GB |
| 79 | parakeet-tdt-0.6b-v3 | 630 M | — | ✓ cc-by-4.0 | 2.7 M | 3.4 GB |
| 80 | bge-base-en | 110 M | 512 | ✓ mit | 2.7 M | 1.0 GB |
| 81 | Qwen2.5-3B-Instruct | 3.1 B | 33 K | other | 2.6 M | 7.8 GB |
| 82 | Qwen3-4B-Instruct-2507 | 4.0 B | 262 K | ✓ apache-2.0 | 2.6 M | 10.0 GB |
| 83 | SmolLM2-135M | 130 M | 8 K | ✓ apache-2.0 | 2.5 M | 0.8 GB |
| 84 | bge-base-en-v1.5 | 110 M | 512 | ✓ mit | 2.5 M | 0.8 GB |
| 85 | Qwen-Image-2.1-Uncensored-Quantized | 7.1 B | — | other | 2.5 M | 6.1 GB |
| 86 | Qwen3-Embedding-4B | 4.0 B | 41 K | ✓ apache-2.0 | 2.5 M | 10.0 GB |
| 87 | all-distilroberta-v1 | 80 M | 512 | ✓ apache-2.0 | 2.5 M | 0.9 GB |
| 88 | Qwen3.8-27B-Uncensored-GGUF | — | — | ✓ apache-2.0 | 2.5 M | 1.5 GB |
| 89 | gemma-4-12b-it-GGUF | 12.0 B | — | ✓ apache-2.0 | 2.5 M | 7.9 GB |
| 90 | all-MiniLM-L12-v2 | 30 M | 512 | ✓ apache-2.0 | 2.5 M | 0.7 GB |
| 91 | mms-300m-1130-forced-aligner | 320 M | — | ✗ cc-by-nc-4.0 | 2.4 M | 1.9 GB |
| 92 | chatterbox | — | — | ✓ mit | 2.4 M | 12.2 GB |
| 93 | Ornith-1.0-9B | <0.1 M | — | ✓ mit | 2.4 M | 21.2 GB |
| 94 | Ornith-1.0-9B-GGUF | — | — | ✓ mit | 2.4 M | 6.7 GB |
| 95 | bge-reranker-base | 280 M | 512 | ✓ mit | 2.4 M | 1.8 GB |
| 96 | wav2vec2-large-robust-24-ft-age-gender | 320 M | — | ✗ cc-by-nc-sa-4.0 | 2.4 M | 1.9 GB |
| 97 | Qwen3-Embedding-8B | 7.6 B | 41 K | ✓ apache-2.0 | 2.4 M | 18.3 GB |
| 98 | parakeet-unified-en-0.6b-gguf | 600 M | — | other | 2.4 M | 1.1 GB |
| 99 | gte-small | 30 M | 512 | ✓ mit | 2.3 M | 0.6 GB |
| 100 | moondream2 | 1.9 B | — | ✓ apache-2.0 | 2.3 M | 5.0 GB |
VRAM figures are estimates for the smallest available quantization at 8K context — see /methodology. Downloads refresh nightly from the Hugging Face API; API prices (blended 3:1 input:output per 1M tokens) and Artificial Analysis indices from OpenRouter.