1,000 models · refreshed nightly
Models that run on RTX 4090 · 24 GB
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 | On RTX 4090 · 24 GB |
|---|---|---|---|---|---|---|
| 501 | pythia-160m-deduped | 210 M | 2 K | ✓ apache-2.0 | 191 K | 0.9 GB |
| 502 | Qwen2.5-Coder-7B-Instruct-GGUF | — | — | ✓ apache-2.0 | 189 K | 3.8 GB |
| 503 | Llama-3.2-3B-Instruct | 3.2 B | 131 K | ⚠ llama3.2 | 188 K | 8.0 GB |
| 504 | gemma4-e4b-claims-comparison | 7.9 B | — | ⚠ gemma | 188 K | 19.2 GB |
| 505 | Phi-mini-MoE-instruct | 7.7 B | 4 K | ✓ mit | 186 K | 18.5 GB |
| 506 | Qwen3-0.6B-GGUF | — | — | unknown | 186 K | 0.9 GB |
| 507 | Sugoi-14B-Ultra-GGUF | — | — | ✓ apache-2.0 | 185 K | 6.8 GB |
| 508 | llava-onevision-qwen2-7b-ov | 8.0 B | 33 K | ✓ apache-2.0 | 185 K | 19.4 GB |
| 509 | Qwen2.5-3B-Instruct-GGUF | — | — | other | 185 K | 2.0 GB |
| 510 | Qwen3-14B-GGUF | — | — | unknown | 184 K | 6.8 GB |
| 511 | Qwen3-8B | 8.2 B | 41 K | ✓ apache-2.0 | 183 K | 19.7 GB |
| 512 | openai-gpt | 120 M | — | ✓ mit | 183 K | 1.0 GB |
| 513 | novaAnimeXL_ilV140 | 2.6 B | — | unknown | 183 K | 16.1 GB |
| 514 | Qwen3-4B-unsloth-bnb-4bit | 4.1 B | 41 K | ✓ apache-2.0 | 183 K | 5.0 GB |
| 515 | Qwen3-14B-unsloth-bnb-4bit | 15.2 B | 41 K | ✓ apache-2.0 | 181 K | 15.0 GB |
| 516 | Qwen2.5-7B-Instruct-GGUF | — | — | ✓ apache-2.0 | 180 K | 3.6 GB |
| 517 | Qwen3-8B-GGUF | — | — | unknown | 180 K | 4.1 GB |
| 518 | LLaMmlein_1B_prerelease | 1.1 B | 2 K | other | 179 K | 5.5 GB |
| 519 | Pony_Diffusion_V6_XL | — | — | cdla-permissive-2.0 | 179 K | 8.5 GB |
| 520 | Qwen3-1.7B-GGUF | — | — | unknown | 178 K | 1.5 GB |
| 521 | Phi-3-mini-4k-instruct-gptq-4bit | 3.8 B | 4 K | unknown | 178 K | 3.6 GB |
| 522 | Qwen3-32B-GGUF | — | — | unknown | 177 K | 14.1 GB |
| 523 | Qwen3-30B-A3B-GGUF | — | — | unknown | 177 K | 12.9 GB |
| 524 | Juggernaut-XL-v9 | — | — | ⚠ creativeml-openrail-m | 176 K | 15.9 GB |
| 525 | starcoder2-3b | 3.0 B | 16 K | bigcode-openrail-m | 176 K | 14.3 GB |
| 526 | Qwen3-30B-A3B-Thinking-2507-AWQ-4bit | 5.3 B | 262 K | ✓ apache-2.0 | 173 K | 21.2 GB |
| 527 | avibe | 7.9 B | 33 K | ✓ apache-2.0 | 173 K | 19.1 GB |
| 528 | llama-3-8b-instruct-awq | 8.0 B | 8 K | unknown | 173 K | 8.0 GB |
| 529 | Qwen2.5-0.5B-Instruct-GGUF | — | — | ✓ apache-2.0 | 172 K | 1.0 GB |
| 530 | NVIDIA-Nemotron-Nano-9B-v2-FP8 | 8.9 B | 131 K | other | 171 K | 13.1 GB |
| 531 | granite-4.1-3b-GGUF | — | — | ✓ apache-2.0 | 170 K | 2.0 GB |
| 532 | Qwen3-14B-GPTQ-Int4 | 14.8 B | 41 K | ✓ apache-2.0 | 170 K | 13.7 GB |
| 533 | LFM2.5-8B-A1B | 8.5 B | 128 K | other | 170 K | 20.4 GB |
| 534 | falcon-mamba-7b | 7.3 B | — | other | 170 K | 17.6 GB |
| 535 | Qwen2.5-7B-Instruct-bnb-4bit | 7.8 B | 33 K | ✓ apache-2.0 | 170 K | 7.8 GB |
| 536 | TinyLlama-1.1B-Chat-v0.3-AWQ | 1.1 B | 2 K | ✓ apache-2.0 | 169 K | 1.5 GB |
| 537 | Meta-Llama-3-8B-Instruct | 8.0 B | 8 K | other | 169 K | 19.4 GB |
| 538 | Gemma-4-26B-A4B-it-NVFP4 | 15.1 B | — | ✓ apache-2.0 | 168 K | 20.8 GB |
| 539 | Meta-Llama-3.1-8B-Instruct-AWQ-INT4 | 8.0 B | 131 K | ⚠ llama3.1 | 167 K | 8.0 GB |
| 540 | Qwen3-30B-A3B-GPTQ-Int4 | 30.5 B | 41 K | ✓ apache-2.0 | 167 K | 23.7 GB |
| 541 | Agents-A1-4B | 4.5 B | — | ✓ apache-2.0 | 167 K | 11.2 GB |
| 542 | Qwen2.5-Math-1.5B-Instruct | 1.5 B | 4 K | ✓ apache-2.0 | 167 K | 4.1 GB |
| 543 | RnJ-1-Instruct-FP8 | 8.8 B | 33 K | ⚠ gemma | 164 K | 15.0 GB |
| 544 | Llama-3.2-1B-Instruct-GGUF | — | — | ⚠ llama3.2 | 162 K | 1.2 GB |
| 545 | Qwen3-4B-Instruct-2507-NVFP4 | 2.8 B | 262 K | ✓ apache-2.0 | 161 K | 4.9 GB |
| 546 | stable-diffusion-xl-1.0-inpainting-0.1 | 2.6 B | — | ⚠ openrail++ | 155 K | 23.8 GB |
| 547 | opus-mt-tc-big-tr-en | 230 M | 1 K | ✓ cc-by-4.0 | 154 K | 1.1 GB |
| 548 | animagine-xl-3.1 | 2.6 B | — | ⚠ openrail++ | 153 K | 16.1 GB |
| 549 | nova-furry-xl-il-v120-sdxl | 2.6 B | — | other | 151 K | 8.5 GB |
| 550 | financial-summarization-pegasus | 570 M | 512 | unknown | 148 K | 3.1 GB |
VRAM figures are estimates for the smallest available quantization at 8K context — see /methodology. Downloads refresh nightly from the Hugging Face API.