Best local AI models for 8GB VRAM
Ranked by what actually fits at 32K context, computed from real file bytes.
A 8GB card gives you about 7.44 GiB to work with after driver overhead. 1 indexed models fit at 32K context — the largest being HunyuanImage-2.1 at 17.5B parameters in Q2_K_S.
From the file· fit from summed bytesFrom the file· KV per layer
Fits in 8GB at 32K context
largest quantization that fits, per model
| Model | Modality | Best quant | Params○ | Total◐ | Headroom◐ |
|---|---|---|---|---|---|
| HunyuanImage-2.1 | image generation | Q2_K_S | 17.5B | 6.91 GiB | 0.53 GiB |
This page models a generic 8GB 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.