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Text generation models

Every model in the catalog with its licence, estimated VRAM and daily-tracked downloads. Filters update the URL — share any view.

Task
All text-generation 400 text-to-image 150 ASR 88 image-text-to-text 80 sentence-similarity 55 feature-extraction 45 translation 43 text-classification 39 image-classification 32 token-classification 21 text-to-speech 12 audio-classification 10 object-detection 10 image-segmentation 8 summarization 7
Runs on
Any RTX 3060 · 12 GB RTX 4070 · 16 GB RTX 4090 · 24 GB 2 × 24 GB Mac M3 · 24 GB Mac M4 Max · 64 GB
Licence
Size
$
400 models
#ModelParamsContextCommercial use30dMin VRAM
151 Qwen2.5-Coder-3B-Instruct Qwen · text-generation 3.1 B 33 K other 604 K from 7.8 GB
152 Qwen2-1.5B-Instruct Qwen · text-generation 1.5 B 33 K ✓ apache-2.0 601 K from 4.1 GB
153 LFM2.5-230M-GGUF LiquidAI · text-generation — — other 586 K from 0.7 GB
154 Parable-Qwen3-8B-Claude-Fable-5-GGUF AnkitAI · text-generation — — ✓ apache-2.0 583 K from 6.0 GB
155 Qwen3-14B-Base Qwen · text-generation 14.8 B 33 K ✓ apache-2.0 582 K from 35.2 GB
156 japanese-gpt-neox-small rinna · text-generation 200 M 2 K ✓ mit 575 K from 1.3 GB
157 SmolLM-1.7B-Instruct-quantized.w4a16 nm-testing · text-generation 1.8 B 2 K ✓ apache-2.0 571 K from 2.7 GB
158 LFM2.5-8B-A1B-GGUF LiquidAI · text-generation — — other 571 K from 5.8 GB
159 NVIDIA-Nemotron-3.5-Lightning-30B-A3B-BF16 nvidia · text-generation 31.6 B 262 K other 570 K from 77.6 GB
160 DeepSeek-V4-Pro deepseek-ai · text-generation 1,598.8 B 1.0 M ✓ mit 569 K from 1,191.5 GB
161 Qwen2.5-Coder-1.5B-Instruct Qwen · text-generation 1.5 B 33 K ✓ apache-2.0 567 K from 4.1 GB
162 Qwen3-Coder-30B-A3B-Instruct Qwen · text-generation 30.5 B 262 K ✓ apache-2.0 565 K from 72.3 GB
163 bge-reranker-v2.5-gemma2-lightweight-gptq boboliu · text-generation 9.2 B 8 K unknown 563 K from 8.7 GB
164 gemma-4-31B-it-NVFP4-turbo LilaRest · text-generation 32.5 B — ✓ apache-2.0 561 K from 26.6 GB
165 phi-2 microsoft · text-generation 2.8 B 2 K ✓ mit 556 K from 7.0 GB
166 Ornith-1.5-9B ornith-ai · text-generation 9.7 B — ✓ mit 546 K from 23.2 GB
167 macbert4csc-base-chinese shibing624 · text-generation 100 M 512 ✓ apache-2.0 543 K from 1.0 GB
168 gpt-oss-20b-GGUF unsloth · text-generation — 131 K ✓ apache-2.0 543 K from 13.1 GB
169 gpt-neo-125m EleutherAI · text-generation 150 M 2 K ✓ mit 538 K from 1.1 GB
170 Llama-3.1-8B meta-llama · text-generation · gated 8.0 B — ⚠ llama3.1 534 K from 19.4 GB
171 Huihui-DeepSeek-V4-Flash-0731-abliterated-GGUF huihui-ai · text-generation — — ✓ mit 526 K from 12.5 GB
172 Qwen2.5-32B-Instruct-GPTQ-Int4 Qwen · text-generation 32.8 B 33 K ✓ apache-2.0 522 K from 26.7 GB
173 Qwen3-Coder-Next Qwen · text-generation 79.7 B 262 K ✓ apache-2.0 521 K from 187.7 GB
174 Ornith-1.0-9B-GGUF unsloth · text-generation — — ✓ mit 520 K from 5.3 GB
175 qwen3-4b-base-dapo-v4 ReliquaryForge · text-generation 4.0 B 33 K ✓ apache-2.0 515 K from 10.0 GB
176 Qwen2.5-Coder-7B-Instruct-GPTQ-Int4 Qwen · text-generation 7.6 B 33 K ✓ apache-2.0 515 K from 7.8 GB
177 Qwen3.6-27B-Text-NVFP4-MTP sakamakismile · text-generation 16.7 B — ✓ apache-2.0 514 K from 24.6 GB
178 llama-3.3-70b-instruct-awq casperhansen · text-generation 70.6 B 131 K ⚠ llama3.3 507 K from 54.8 GB
179 GLM-5.3-GGUF unsloth · text-generation — — other 506 K from 52.0 GB
180 bloom-560m bigscience · text-generation 560 M — ⚠ bigscience-bloom-rail-1.0 502 K from 1.8 GB
181 Ornith-1.5-397B-NVFP4 ornith-ai · text-generation 202.6 B — ✓ mit 498 K from 296.8 GB
182 Qwen3-30B-A3B-Instruct-2507-FP8 Qwen · text-generation 30.5 B 262 K ✓ apache-2.0 498 K from 39.4 GB
183 pythia-160m-deduped EleutherAI · text-generation 210 M 2 K ✓ apache-2.0 492 K from 0.9 GB
184 Ornith-1.5-35B-A3B-FP8 ornith-ai · text-generation 36.0 B — ✓ mit 489 K from 49.2 GB
185 gemma-4-12B-coder-fable5-composer2.5-v1-GGUF yuxinlu1 · text-generation — — ✓ apache-2.0 483 K from 5.8 GB
186 SmolLM2-360M HuggingFaceTB · text-generation 360 M 8 K ✓ apache-2.0 481 K from 1.4 GB
187 DeepSeek-R1-Distill-Qwen-32B deepseek-ai · text-generation 32.8 B 131 K ✓ mit 479 K from 77.5 GB
188 Parable-Qwen3-4B-Claude-Fable-5-GGUF AnkitAI · text-generation — — ✓ apache-2.0 479 K from 3.2 GB
189 Qwen3-Coder-Next-NVFP4-GB10 ucbye · text-generation — 262 K ✓ apache-2.0 477 K from 50.9 GB
190 Qwen2.5-72B-Instruct-AWQ Qwen · text-generation 73.0 B 33 K other 475 K from 57.2 GB
191 Qwen3-4B-GGUF unsloth · text-generation — 41 K ✓ apache-2.0 474 K from 2.3 GB
192 Apertus-8B-Instruct-2509 swiss-ai · text-generation 8.1 B 66 K ✓ apache-2.0 472 K from 19.4 GB
193 Llama-3.1-405B-FP8 meta-llama · text-generation · gated 405.9 B — ⚠ llama3.1 465 K from 597.3 GB
194 Ornith-1.0-35B-FP8 ornith-ai · text-generation 35.1 B — ✓ mit 465 K from 47.2 GB
195 DeepSeek-Coder-V2-Lite-Instruct-GGUF bartowski · text-generation — — other 461 K from 7.1 GB
196 gemma4-e4b-claims-comparison k-chirkunov · text-generation · gated 7.9 B — ⚠ gemma 450 K from 19.2 GB
197 Qwen3-8B-Base Qwen · text-generation 8.2 B 33 K ✓ apache-2.0 447 K from 19.7 GB
198 Llama-2-7b-chat-hf meta-llama · text-generation · gated 6.7 B — ⚠ llama2 447 K from 16.3 GB
199 zeta-2.1-autoround-W4A16 LeaderboardModel1 · text-generation 2.2 B 33 K unknown 444 K from 7.6 GB
200 Bonsai-27B-gguf prism-ml · text-generation — — ✓ apache-2.0 440 K from 1.2 GB
VRAM figures are estimates for the smallest available quantization at 8K context — see /methodology. Downloads refresh nightly from the Hugging Face API.