Can I Run Mistral Family on RTX 4060 Laptop (8 GB VRAM, 16 GB RAM)?
Superseded model. Mistral Family has been superseded by Mistral Small 4. This page is kept for reference; the newer family is a better starting point.
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Written by Jakub Rusinowski · Last updated January 28, 2025
Yes, but it is tight
Yes, but it is tight — Mistral NeMo 12B at Q3_K_M needs about 7.3 GB of the 8 GB usable on RTX 4060 Laptop (8 GB VRAM, 16 GB RAM), leaving only ~0.7 GB before the runtime starts swapping. Expect ~32.7 tok/s (estimated), with room for about 8,192 tokens of context.
Confidence: medium · Recommended quantization: Q3_K_M · Estimated speed: ~32.7 tok/s
RTX 4060 Laptop (8 GB VRAM, 16 GB RAM) — what it gives a model
| Usable memory for models | 8 GB |
| Memory bandwidth | 272 GB/s |
| Form factor | Laptop |
| Operating system | Windows or Linux |
| Memory upgradeable | Yes |
| Price | $1,099 (lib/data/laptops.ts (street price), checked 2026-07-06) |
Mistral Family on RTX 4060 Laptop (8 GB VRAM, 16 GB RAM): memory by quantization
| Quant | Memory needed | Fits 8 GB? | Max context | Est. speed | Download |
|---|
| F16 | 26.1 GB | ✗ No | — | — | 24 GB |
| Q8_0 | 14.9 GB | ✗ No | — | — | 12.8 GB |
| Q6_K | 12 GB | ✗ No | — | — | 9.8 GB |
| Q5_K_M | 10.6 GB | ✗ No | — | — | 8.5 GB |
| Q4_K_M | 9.4 GB | ✗ No | — | — | 7.2 GB |
| Q3_K_M | 7.3 GB | ✓ Yes | 8K | ~32.7 tok/s | 5.1 GB |
| Q2_K | 6.1 GB | ✓ Yes | 16K | ~40.2 tok/s | 3.9 GB |
Which Mistral Family sizes fit
| Variant | Needs at Q4_K_M | Fits? | Est. speed |
|---|
| Mistral Small 3 (24B) | 17.2 GB | ✗ Too large | — |
| Mistral NeMo 12B | 9.4 GB | ✗ Too large | — |
What to watch out for
- Only ~0.7 GB of headroom at Q3_K_M: a longer context or a second application can push this into swapping.
- Q3_K_M is the only quantization that fits, and it is a heavily degraded one — expect noticeably worse output than the same model at Q4_K_M. A smaller model at Q4 is usually the better trade.
- 2 larger variants of Mistral Family do not fit and would need CPU offload or different hardware.
RTX 4060 laptop limitations
- 8 GB VRAM limits you to 7–8B models at Q4 with a short context.
- System RAM is usually upgradeable on this class of laptop even though VRAM is not.
Recommended setup
Ollama or llama.cpp (CUDA/ROCm) — vLLM if you need concurrent serving
How these numbers are calculated
- Memory need = quantized weights + KV cache at 8,192 tokens (f16) + 0.8 GB runtime overhead.
- 8 GB of VRAM on the NVIDIA GeForce RTX 4060 at 272 GB/s.
- 16 GB of system RAM available for CPU offload when a model exceeds VRAM.
- Throughput is a memory-bandwidth roofline estimate, not a measurement. It is labelled "estimated" everywhere it appears.
- KV cache is computed from this model's published attention configuration.
FAQ
Can I run Mistral Family on RTX 4060 Laptop (8 GB VRAM, 16 GB RAM)?
Yes, but it is tight — Mistral NeMo 12B at Q3_K_M needs about 7.3 GB of the 8 GB usable on RTX 4060 Laptop (8 GB VRAM, 16 GB RAM), leaving only ~0.7 GB before the runtime starts swapping. Expect ~32.7 tok/s (estimated), with room for about 8,192 tokens of context.
Which quantization of Mistral Family should I use on RTX 4060 Laptop (8 GB VRAM, 16 GB RAM)?
Q3_K_M — it needs about 7.3 GB of the 8 GB available, downloads as roughly 5.1 GB, and runs at an estimated 32.7 tokens/sec with up to 8K of context.
What limits Mistral Family on RTX 4060 Laptop (8 GB VRAM, 16 GB RAM)?
Nothing binding — the model fits with headroom and generates at a usable speed on this hardware.
Which runtime should I use?
Ollama or llama.cpp (CUDA/ROCm) — vLLM if you need concurrent serving
Other Computers
Other Models on RTX 4060 Laptop (8 GB VRAM, 16 GB RAM)
Mistral Family on GPUs
What This Model Is Good At
Model & Tools
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