Written by Jakub Rusinowski · Last updated May 13, 2024
Yes, but it is tight
Yes, but it is tight — Yi 1.5 34B Chat at Q4_K_M needs about 23.6 GB of the 24 GB usable on RTX 4090 Desktop (24 GB VRAM, 64 GB RAM), leaving only ~0.4 GB before the runtime starts swapping. Expect ~32.2 tok/s (estimated), with room for about 8,192 tokens of context.
Confidence: medium · Recommended quantization: Q4_K_M · Estimated speed: ~32.2 tok/s
| Usable memory for models | 24 GB |
| Memory bandwidth | 1008 GB/s |
| Form factor | Desktop |
| Operating system | Windows or Linux |
| Memory upgradeable | Yes |
| Quant | Memory needed | Fits 24 GB? | Max context | Est. speed | Download |
|---|---|---|---|---|---|
| F16 | 71.6 GB | ✗ No | — | — | 68.8 GB |
| Q8_0 | 39.4 GB | ✗ No | — | — | 36.6 GB |
| Q6_K | 31 GB | ✗ No | — | — | 28.2 GB |
| Q5_K_M | 27.2 GB | ✗ No | — | — | 24.4 GB |
| Q4_K_M | 23.6 GB | ✓ Yes | 8K | ~32.2 tok/s | 20.8 GB |
| Q3_K_M | 17.5 GB | ✓ Yes | 16K | ~43.5 tok/s | 14.7 GB |
| Q2_K | 14.1 GB | ✓ Yes | 16K | ~53.9 tok/s | 11.3 GB |
| Variant | Needs at Q4_K_M | Fits? | Est. speed |
|---|---|---|---|
| Yi 1.5 34B Chat | 23.6 GB | ✓ Fits | ~32.2 tok/s |
| Yi 1.5 9B Chat | 6.9 GB | ✓ Fits | ~101.7 tok/s |
Ollama or llama.cpp (CUDA/ROCm) — vLLM if you need concurrent serving
Yes, but it is tight — Yi 1.5 34B Chat at Q4_K_M needs about 23.6 GB of the 24 GB usable on RTX 4090 Desktop (24 GB VRAM, 64 GB RAM), leaving only ~0.4 GB before the runtime starts swapping. Expect ~32.2 tok/s (estimated), with room for about 8,192 tokens of context.
Q4_K_M — it needs about 23.6 GB of the 24 GB available, downloads as roughly 20.8 GB, and runs at an estimated 32.2 tokens/sec with up to 8K of context.
Nothing binding — the model fits with headroom and generates at a usable speed on this hardware.
Ollama or llama.cpp (CUDA/ROCm) — vLLM if you need concurrent serving
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