Autor: Jakub Rusinowski · Ostatnia aktualizacja: 29 maja 2024
Yes, comfortably — you'll have ~19 GB of headroom running Codestral 22B at Q4_K_M (13 GB, ~138 tok/s (est.)) with room for up to 32K context.
Sprawdź cenę na Amazon — NVIDIA GeForce RTX 5090 32GB
| VRAM | 32 GB |
| Memory Bandwidth | 1792 GB/s |
| Quant | VRAM needed | Fits 32 GB? | Max context |
|---|---|---|---|
| F16 | 46.1 GB | ✗ No | — |
| Q8_0 | 25.3 GB | ✓ Yes | 32K |
| Q6_K | 19.9 GB | ✓ Yes | 32K |
| Q5_K_M | 17.5 GB | ✓ Yes | 32K |
| Q4_K_M | 15.1 GB | ✓ Yes | 32K |
| Q3_K_M | 11.2 GB | ✓ Yes | 32K |
| Q2_K | 9 GB | ✓ Yes | 32K |
VRAM needed assumes a 4K-token context with an f16 KV cache; “Max context” is the largest window that still fits in 32 GB. Figures are estimates from parameter count, quantization and memory bandwidth — the analyzer lets you tune KV-cache quant and context.
| Codestral 22B | Q4_K_M · 13 GB · ~138 tok/s (est.) |
At 2 hrs/day, buying (~$1,999) beats renting at $0.34/hr after about 8.2 years.
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Cloud rates verified 2026-07 — estimates, and marketplace prices vary. Buying price is GPU MSRP only, not a full PC.
Yes, comfortably — you'll have ~19 GB of headroom running Codestral 22B at Q4_K_M (13 GB, ~138 tok/s (est.)) with room for up to 32K context.
Codestral 22B at Q4_K_M quantization (13 GB), estimated ~138 tokens/sec, up to 32K context.
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