Best local AI models for 6GB VRAM
Ranked by what actually fits at 32K context, computed from real file bytes.
A 6GB card gives you about 5.58 GiB to work with after driver overhead. 3 indexed models fit at 32K context — the largest being HunyuanVideo-1.5 at 8.3B parameters in Q4_K_S.
From the file· fit from summed bytesFrom the file· KV per layer
Fits in 6GB at 32K context
largest quantization that fits, per model
| Model | Modality | Best quant | Params○ | Total◐ | Headroom◐ |
|---|---|---|---|---|---|
| Wan2.2-TI2V-5B | video generation | Q6_K | 5.0B | 4.76 GiB | 0.82 GiB |
| HunyuanVideo-1.5 | video generation | Q4_K_S | 8.3B | 5.43 GiB | 0.15 GiB |
| Wan2.2-TI2V-5B-Turbo | video generation | Q6_K | 5.0B | 4.76 GiB | 0.82 GiB |
This page models a generic 6GB accelerator, so it answers what fits rather than how fast it runs. For tokens per second you need a specific card — pick one from hardware, where bandwidth is known.