Best local AI models for 24GB VRAM
Ranked by what actually fits at 32K context, computed from real file bytes.
A 24GB card gives you about 22.32 GiB to work with after driver overhead. 2 indexed models fit at 32K context — the largest being HunyuanImage-2.1 at 17.5B parameters in Q4_K_S.
From the file· fit from summed bytesFrom the file· KV per layer
Fits in 24GB at 32K context
largest quantization that fits, per model
| Model | Modality | Best quant | Params○ | Total◐ | Headroom◐ |
|---|---|---|---|---|---|
| HunyuanImage-2.1 | image generation | Q4_K_S | 17.5B | 20.99 GiB | 1.33 GiB |
| Janus-Pro-7B | image generation | I1-Q6_K | 7.4B | 21.11 GiB | 1.21 GiB |
This page models a generic 24GB 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.