AI models that fit on a 8 GB GPU
Open models that fit in 8 GB of VRAM: 506 as published, 646 at FP8 and 975 at INT4. Each model is listed on the smallest tier it fits at that precision.
GPUs with 8 GB
Cards whose datasheet VRAM puts them in this tier, up to the next tier at 12 GB. Prices are the lowest live data-center on-demand rate per GPU.
Fits as published
Models whose published weights, plus the flat overhead, fit this much memory with no quantization.
Text models
The 40 most downloaded of 235.
Vision-language models
The 40 most downloaded of 53.
Image generation models
The 40 most downloaded of 46.
Video generation models
10 models.
| Model | Parameters | Published as | VRAM needed |
|---|---|---|---|
| Wan2.1-T2V-1.3B-Diffusers | 1.4B | F32 | 6.3 GB |
| stable-video-diffusion-img2vid-xt | 1.5B | F32 | 6.8 GB |
| TurboWan2.1-T2V-1.3B-Diffusers | 1.4B | BF16 | 3.2 GB |
| stable-video-diffusion-img2vid | 1.5B | F32 | 6.8 GB |
| i2vgen-xl | 1.4B | F32 | 6.3 GB |
| Wan2.1-T2V-1.3B | 1.4B | F32 | 6.3 GB |
| CogVideoX-2b | 1.7B | F16 | 3.8 GB |
| text-to-video-ms-1.7b | 1.4B | F32 | 6.3 GB |
| LTX-Video-0.9.5 | 1.9B | BF16 | 4.3 GB |
| stable-virtual-camera | 1.3B | F32 | 5.7 GB |
Speech models
The 40 most downloaded of 117.
Embedding models
9 models.
| Model | Parameters | Published as | VRAM needed |
|---|---|---|---|
| Qwen3-Embedding-0.6B | 596M | BF16 | 1.3 GB |
| multilingual-e5-large-instruct | 560M | F16 | 1.3 GB |
| Qwen3-VL-Embedding-2B | 2.1B | BF16 | 4.8 GB |
| gte-Qwen2-1.5B-instruct | 1.8B | F32 | 7.9 GB |
| voyage-4-nano | 346M | BF16 | 0.8 GB |
| jina-code-embeddings-0.5b | 494M | BF16 | 1.1 GB |
| stella_en_1.5B_v5 | 1.5B | F32 | 6.9 GB |
| jina-code-embeddings-1.5b | 1.5B | BF16 | 3.5 GB |
| WeMM-Embedding-2B | 2.7B | BF16 | 6.1 GB |
Other models
36 models.
Fits at FP8
Models that fit only after quantizing the weights to 8 bits (1 byte per parameter). Needs an FP8 checkpoint or an engine that quantizes on load, and a GPU with FP8 support.
Text models
The 40 most downloaded of 293.
Vision-language models
The 40 most downloaded of 83.
Image generation models
The 40 most downloaded of 65.
Video generation models
17 models.
| Model | Parameters | Published as | VRAM needed |
|---|---|---|---|
| LTX-Video | 1.9B | F32 | 2.1 GB |
| Wan2.1-T2V-1.3B-Diffusers | 1.4B | F32 | 1.6 GB |
| stable-video-diffusion-img2vid-xt | 1.5B | F32 | 1.7 GB |
| Wan2.2-TI2V-5B-Diffusers | 5.0B | F32 | 5.6 GB |
| FastWan2.2-TI2V-5B-FullAttn-Diffusers | 5.0B | BF16 | 5.6 GB |
| TurboWan2.1-T2V-1.3B-Diffusers | 1.4B | BF16 | 1.6 GB |
| stable-video-diffusion-img2vid | 1.5B | F32 | 1.7 GB |
| i2vgen-xl | 1.4B | F32 | 1.6 GB |
| Wan2.1-T2V-1.3B | 1.4B | F32 | 1.6 GB |
| CogVideoX-2b | 1.7B | F16 | 1.9 GB |
| text-to-video-ms-1.7b | 1.4B | F32 | 1.6 GB |
| LTX-Video-0.9.5 | 1.9B | BF16 | 2.1 GB |
| CogVideoX-5b | 5.6B | BF16 | 6.2 GB |
| LongLive-2.0-5B-Diffusers | 5.0B | BF16 | 5.6 GB |
| CogVideoX-5b-I2V | 5.6B | BF16 | 6.3 GB |
| Wan2.1-VACE-1.3B-diffusers | 2.2B | F32 | 2.4 GB |
| stable-virtual-camera | 1.3B | F32 | 1.4 GB |
Speech models
The 40 most downloaded of 132.
Embedding models
10 models.
| Model | Parameters | Published as | VRAM needed |
|---|---|---|---|
| Qwen3-Embedding-0.6B | 596M | BF16 | 0.7 GB |
| Qwen3-Embedding-4B | 4.0B | BF16 | 4.5 GB |
| multilingual-e5-large-instruct | 560M | F16 | 0.6 GB |
| Qwen3-VL-Embedding-2B | 2.1B | BF16 | 2.4 GB |
| gte-Qwen2-1.5B-instruct | 1.8B | F32 | 2.0 GB |
| voyage-4-nano | 346M | BF16 | 0.4 GB |
| jina-code-embeddings-0.5b | 494M | BF16 | 0.6 GB |
| stella_en_1.5B_v5 | 1.5B | F32 | 1.7 GB |
| jina-code-embeddings-1.5b | 1.5B | BF16 | 1.7 GB |
| WeMM-Embedding-2B | 2.7B | BF16 | 3.0 GB |
Other models
The 40 most downloaded of 46.
Fits at INT4
Models that fit only after quantizing to 4 bits (0.5 byte per parameter). Needs a quantized checkpoint actually published for the model; check its Hugging Face page before relying on a row.
Text models
The 40 most downloaded of 521.
Vision-language models
The 40 most downloaded of 134.
Image generation models
The 40 most downloaded of 77.
Video generation models
23 models.
| Model | Parameters | Published as | VRAM needed |
|---|---|---|---|
| LTX-Video | 1.9B | F32 | 1.1 GB |
| Wan2.1-T2V-1.3B-Diffusers | 1.4B | F32 | 0.8 GB |
| stable-video-diffusion-img2vid-xt | 1.5B | F32 | 0.9 GB |
| Wan2.2-TI2V-5B-Diffusers | 5.0B | F32 | 2.8 GB |
| Wan2.2-T2V-A14B-Diffusers | 14.3B | F32 | 8.0 GB |
| Wan2.2-I2V-A14B-Diffusers | 14.3B | F32 | 8.0 GB |
| FastWan2.2-TI2V-5B-FullAttn-Diffusers | 5.0B | BF16 | 2.8 GB |
| Wan2.1-T2V-14B-Diffusers | 14.3B | F32 | 8.0 GB |
| TurboWan2.1-T2V-1.3B-Diffusers | 1.4B | BF16 | 0.8 GB |
| stable-video-diffusion-img2vid | 1.5B | F32 | 0.9 GB |
| Wan2.2-I2V-A14B-Lightning-Diffusers | 14.3B | BF16 | 8.0 GB |
| i2vgen-xl | 1.4B | F32 | 0.8 GB |
| Wan2.1-T2V-14B | 14.3B | F32 | 8.0 GB |
| Wan2.1-T2V-1.3B | 1.4B | F32 | 0.8 GB |
| CogVideoX-2b | 1.7B | F16 | 0.9 GB |
| text-to-video-ms-1.7b | 1.4B | F32 | 0.8 GB |
| LTX-Video-0.9.5 | 1.9B | BF16 | 1.1 GB |
| CogVideoX-5b | 5.6B | BF16 | 3.1 GB |
| LongLive-2.0-5B-Diffusers | 5.0B | BF16 | 2.8 GB |
| CogVideoX-5b-I2V | 5.6B | BF16 | 3.1 GB |
| Wan2.1-VACE-1.3B-diffusers | 2.2B | F32 | 1.2 GB |
| stable-virtual-camera | 1.3B | F32 | 0.7 GB |
| mochi-1-preview | 10.0B | F32 | 5.6 GB |
Speech models
The 40 most downloaded of 136.
Embedding models
16 models.
| Model | Parameters | Published as | VRAM needed |
|---|---|---|---|
| Qwen3-Embedding-0.6B | 596M | BF16 | 0.3 GB |
| Qwen3-Embedding-4B | 4.0B | BF16 | 2.2 GB |
| Qwen3-Embedding-8B | 7.6B | BF16 | 4.2 GB |
| multilingual-e5-large-instruct | 560M | F16 | 0.3 GB |
| Qwen3-VL-Embedding-2B | 2.1B | BF16 | 1.2 GB |
| Qwen3-VL-Embedding-8B | 8.1B | BF16 | 4.6 GB |
| gte-Qwen2-1.5B-instruct | 1.8B | F32 | 1.0 GB |
| Qwen3-VL-Embedding-8B-FP8 | 8.8B | F8_E4M3 | 4.9 GB |
| voyage-4-nano | 346M | BF16 | 0.2 GB |
| gte-Qwen2-7B-instruct | 7.6B | F32 | 4.3 GB |
| jina-code-embeddings-0.5b | 494M | BF16 | 0.3 GB |
| stella_en_1.5B_v5 | 1.5B | F32 | 0.9 GB |
| jina-code-embeddings-1.5b | 1.5B | BF16 | 0.9 GB |
| WeMM-Embedding-2B | 2.7B | BF16 | 1.5 GB |
| WeMM-Embedding-9B | 9.4B | BF16 | 5.3 GB |
| pplx-embed-v2-context-9b-preview | 8.4B | F32 | 4.7 GB |
Other models
The 40 most downloaded of 68.
How these numbers are computed
Required VRAM is the weight size at each precision times a flat 1.2 overhead, the same figure every model page shows. It does not include a long context: the KV cache grows with every token, so a model near the top of a tier can need the next one at long context. Read how much VRAM you need for LLMs for the method, the VRAM and quantization glossary entries for the terms, and the VRAM calculator to size a model that is not listed.
Looking for a model by job rather than by memory? Start with coding, reasoning, chat and assistants, vision-language or see the full models directory.
