Written by Jakub Rusinowski · Last updated October 16, 2024
Yes — comfortably
Yes, comfortably — Ministral 8B at Q8_0 needs about 10.5 GB of the 16 GB usable on RTX 5060 Ti 16 GB Desktop (16 GB VRAM, 32 GB RAM), leaving ~5.5 GB spare and running at ~34 tok/s (estimated), with room for about 32,768 tokens of context.
Confidence: high · Recommended quantization: Q8_0 · Estimated speed: ~34 tok/s
| Usable memory for models | 16 GB |
| Memory bandwidth | 448 GB/s |
| Form factor | Desktop |
| Operating system | Windows or Linux |
| Memory upgradeable | Yes |
| Quant | Memory needed | Fits 16 GB? | Max context | Est. speed | Download |
|---|---|---|---|---|---|
| F16 | 18 GB | ✗ No | — | — | 16 GB |
| Q8_0 | 10.5 GB | ✓ Yes | 32K | ~34 tok/s | 8.5 GB |
| Q6_K | 8.6 GB | ✓ Yes | 32K | ~42.3 tok/s | 6.6 GB |
| Q5_K_M | 7.7 GB | ✓ Yes | 32K | ~47.7 tok/s | 5.7 GB |
| Q4_K_M | 6.9 GB | ✓ Yes | 32K | ~54.2 tok/s | 4.8 GB |
| Q3_K_M | 5.4 GB | ✓ Yes | 32K | ~70.3 tok/s | 3.4 GB |
| Q2_K | 4.6 GB | ✓ Yes | 32K | ~84.1 tok/s | 2.6 GB |
| Variant | Needs at Q4_K_M | Fits? | Est. speed |
|---|---|---|---|
| Ministral 8B | 6.9 GB | ✓ Fits | ~54.2 tok/s |
| Ministral 3B | 3.8 GB | ✓ Fits | ~99.9 tok/s |
Ollama or llama.cpp (CUDA/ROCm) — vLLM if you need concurrent serving
Yes, comfortably — Ministral 8B at Q8_0 needs about 10.5 GB of the 16 GB usable on RTX 5060 Ti 16 GB Desktop (16 GB VRAM, 32 GB RAM), leaving ~5.5 GB spare and running at ~34 tok/s (estimated), with room for about 32,768 tokens of context.
Q8_0 — it needs about 10.5 GB of the 16 GB available, downloads as roughly 8.5 GB, and runs at an estimated 34 tokens/sec with up to 32K 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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