Autor: Jakub Rusinowski · Ostatnia aktualizacja: 11 września 2026
No. Devstral-2 123B needs 74.3 GB at Q4_K_M and the NVIDIA GeForce RTX 4060 has only 8 GB. No quantization we publish closes a gap that size.
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| Model | Devstral-2 123B |
| Parameters | 123B |
| Quantization | Q4_K_M |
| VRAM needed | 74.3 GB |
| NVIDIA GeForce RTX 4060 VRAM | 8 GB |
| Verdict | Does not fit |
| Quant | VRAM needed | Fits 8 GB? | Max context | Whole PC |
|---|---|---|---|---|
| F16 | 248.2 GB | ✗ No | — | — |
| Q8_0 | 132.9 GB | ✗ No | — | — |
| Q6_K | 103.1 GB | ✗ No | — | — |
| Q5_K_M | 89.4 GB | ✗ No | — | — |
| Q4_K_M | 76.5 GB | ✗ No | — | — |
| Q3_K_M | 54.7 GB | ✗ No | — | — |
| Q2_K | 42.7 GB | ✗ No | — | — |
Assumes a 4K-token context with an f16 KV cache, on an estimated architecture — this model publishes no config we can read. A longer window needs more; a quantized KV cache needs less. “Max context” is the largest window that still fits in 8 GB. Figures are estimates from parameter count, quantization and memory bandwidth — the analyzer lets you tune KV-cache quant and context.
Context costs VRAM too. At Q4_K_M on the NVIDIA GeForce RTX 4060: 8K 77.9 GB ✗ · 32K 86.6 GB ✗ · 128K 121.2 GB ✗. Past 8K it no longer fits 8 GB — a q8_0 KV cache buys roughly half of that back, which the calculator will price for you.
Either step down to a smaller size in this family, or move to a NVIDIA A100 80GB (80 GB), the cheapest card we track with enough VRAM.
No compatible GPU? Devstral on 16 GB of system RAM, CPU only: runs, but it is tight.
Cheapest card we track with enough VRAM for Devstral-2 123B:
Devstral-2 123B needs ~74 GB but this GPU has 8 GB. Rent a A100 (80 GB)-class GPU by the hour instead of buying one:
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Cloud rates verified 2026-07 — estimates, and marketplace prices vary. Buying price is GPU MSRP only, not a full PC.
All Devstral sizes on the NVIDIA GeForce RTX 4060 | Devstral-2 123B model page | NVIDIA GeForce RTX 4060 GPU page | Check your hardware