1,000 models · refreshed nightly
Models that run on RTX 4070 · 16 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 4070 · 16 GB |
|---|---|---|---|---|---|---|
| 401 | Qwen2.5-14B-bnb-4bit | 15.2 B | 131 K | ✓ apache-2.0 | 224 K | 13.7 GB |
| 402 | Qwen3.6-35B-A3B-DFlash | 390 M | 262 K | ✓ apache-2.0 | 224 K | 1.4 GB |
| 403 | Qwen3-4B-GGUF | — | — | unknown | 223 K | 2.3 GB |
| 404 | vlt5-base-keywords | 280 M | — | ✓ cc-by-4.0 | 223 K | 1.8 GB |
| 405 | gemma-4-12b-heretic-abliterated-GGUF | — | — | ✓ apache-2.0 | 219 K | 0.7 GB |
| 406 | Gemma-4-E4B-DECKARD-HERETIC-NVFP4 | 6.2 B | — | ⚠ gemma | 217 K | 12.6 GB |
| 407 | Meta-Llama-3.1-8B-FP8 | 8.0 B | 131 K | ⚠ llama3.1 | 216 K | 11.7 GB |
| 408 | dvine82-xl | 2.6 B | — | unknown | 213 K | 8.5 GB |
| 409 | SmolLM2-1.7B-Instruct | 1.7 B | 8 K | ✓ apache-2.0 | 213 K | 4.5 GB |
| 410 | Mistral-7B-Instruct-v0.3-AWQ | 7.3 B | 33 K | ✓ apache-2.0 | 212 K | 6.2 GB |
| 411 | IP-Adapter-FaceID | — | — | unknown | 210 K | 1.5 GB |
| 412 | t5-large | 740 M | — | ✓ apache-2.0 | 210 K | 3.9 GB |
| 413 | Ornith-1.0-35B-GGUF | — | — | ✓ mit | 203 K | 12.1 GB |
| 414 | xflux_text_encoders | 4.8 B | — | ✓ apache-2.0 | 203 K | 11.7 GB |
| 415 | Qwen2.5-Coder-1.5B | 1.5 B | 33 K | ✓ apache-2.0 | 200 K | 4.1 GB |
| 416 | gemma-1.1-2b-it | 2.5 B | — | ⚠ gemma | 200 K | 6.4 GB |
| 417 | Qwen2.5-1.5B-Instruct-GGUF | — | — | ✓ apache-2.0 | 199 K | 1.3 GB |
| 418 | Qwen1.5-0.5B-Chat | 620 M | 33 K | other | 199 K | 2.0 GB |
| 419 | aya-expanse-8b-AWQ | 9.1 B | 8 K | gpl-3.0 | 198 K | 10.5 GB |
| 420 | Qwen3-4B-Thinking-2507-FP8 | 4.4 B | 262 K | ✓ apache-2.0 | 197 K | 6.9 GB |
| 421 | Qwen2.5-Coder-32B-Instruct-GGUF | — | — | ✓ apache-2.0 | 197 K | 9.1 GB |
| 422 | pythia-160m-deduped | 210 M | 2 K | ✓ apache-2.0 | 191 K | 0.9 GB |
| 423 | Qwen2.5-Coder-7B-Instruct-GGUF | — | — | ✓ apache-2.0 | 189 K | 3.8 GB |
| 424 | Llama-3.2-3B-Instruct | 3.2 B | 131 K | ⚠ llama3.2 | 188 K | 8.0 GB |
| 425 | Qwen3-0.6B-GGUF | — | — | unknown | 186 K | 0.9 GB |
| 426 | Sugoi-14B-Ultra-GGUF | — | — | ✓ apache-2.0 | 185 K | 6.8 GB |
| 427 | Qwen2.5-3B-Instruct-GGUF | — | — | other | 185 K | 2.0 GB |
| 428 | Qwen3-14B-GGUF | — | — | unknown | 184 K | 6.8 GB |
| 429 | openai-gpt | 120 M | — | ✓ mit | 183 K | 1.0 GB |
| 430 | Qwen3-4B-unsloth-bnb-4bit | 4.1 B | 41 K | ✓ apache-2.0 | 183 K | 5.0 GB |
| 431 | Qwen3-14B-unsloth-bnb-4bit | 15.2 B | 41 K | ✓ apache-2.0 | 181 K | 15.0 GB |
| 432 | Qwen2.5-7B-Instruct-GGUF | — | — | ✓ apache-2.0 | 180 K | 3.6 GB |
| 433 | Qwen3-8B-GGUF | — | — | unknown | 180 K | 4.1 GB |
| 434 | LLaMmlein_1B_prerelease | 1.1 B | 2 K | other | 179 K | 5.5 GB |
| 435 | Pony_Diffusion_V6_XL | — | — | cdla-permissive-2.0 | 179 K | 8.5 GB |
| 436 | Qwen3-1.7B-GGUF | — | — | unknown | 178 K | 1.5 GB |
| 437 | Phi-3-mini-4k-instruct-gptq-4bit | 3.8 B | 4 K | unknown | 178 K | 3.6 GB |
| 438 | Qwen3-32B-GGUF | — | — | unknown | 177 K | 14.1 GB |
| 439 | Qwen3-30B-A3B-GGUF | — | — | unknown | 177 K | 12.9 GB |
| 440 | Juggernaut-XL-v9 | — | — | ⚠ creativeml-openrail-m | 176 K | 15.9 GB |
| 441 | starcoder2-3b | 3.0 B | 16 K | bigcode-openrail-m | 176 K | 14.3 GB |
| 442 | llama-3-8b-instruct-awq | 8.0 B | 8 K | unknown | 173 K | 8.0 GB |
| 443 | Qwen2.5-0.5B-Instruct-GGUF | — | — | ✓ apache-2.0 | 172 K | 1.0 GB |
| 444 | NVIDIA-Nemotron-Nano-9B-v2-FP8 | 8.9 B | 131 K | other | 171 K | 13.1 GB |
| 445 | granite-4.1-3b-GGUF | — | — | ✓ apache-2.0 | 170 K | 2.0 GB |
| 446 | Qwen3-14B-GPTQ-Int4 | 14.8 B | 41 K | ✓ apache-2.0 | 170 K | 13.7 GB |
| 447 | Qwen2.5-7B-Instruct-bnb-4bit | 7.8 B | 33 K | ✓ apache-2.0 | 170 K | 7.8 GB |
| 448 | TinyLlama-1.1B-Chat-v0.3-AWQ | 1.1 B | 2 K | ✓ apache-2.0 | 169 K | 1.5 GB |
| 449 | Meta-Llama-3.1-8B-Instruct-AWQ-INT4 | 8.0 B | 131 K | ⚠ llama3.1 | 167 K | 8.0 GB |
| 450 | Agents-A1-4B | 4.5 B | — | ✓ apache-2.0 | 167 K | 11.2 GB |
VRAM figures are estimates for the smallest available quantization at 8K context — see /methodology. Downloads refresh nightly from the Hugging Face API.