MistralCodestral 22B on NVIDIA RTX 4080 Laptop (120-150W)
RTX 4080 Laptop (120-150W) runs Codestral 22B at Q3_K_M — 8 tok/s due to limited memory bandwidth. Slow but functional — see all options below.
Model Size
22.2B
Device VRAM
12 GB
Bandwidth
384 GB/s
Quantization
Q3_K_M
Performance by Quantization
OwnRig currently has one published compatibility entry for Codestral 22B on NVIDIA RTX 4080 Laptop (120-150W) at Q3_K_M. This is the best supported pairing we can stand behind today.
| Quantization | Speed | TTFT | Fits in VRAM | Rating | Confidence |
|---|---|---|---|---|---|
| Q3_K_M | 8 tok/s | 929ms | ✓ Yes | Marginal | estimated |
Notes
Q3_K_M
Sustained post-thermal-throttle performance. TDP-capped laptop variant.
About Codestral 22B
Codestral 22B (22.2B) is a coding, ai coding, ai building model. Mistral's dedicated coding model. Built for code completion and generation across 80+ languages. Fits on a single 16 GB GPU at Q3/Q4. Non-production license limits commercial use.
View all Codestral 22B hardware options →About NVIDIA RTX 4080 Laptop (120-150W)
NVIDIA RTX 4080 Laptop (120-150W) has 12 GB at 384 GB/s. Street price: $0.
See all models NVIDIA RTX 4080 Laptop (120-150W) can run →Estimate method: Community laptop benchmarks and thermal throttle reports. Reference hardware source: reddit.com (2026-03-14)
Performance varies by driver version, inference engine, quantization method, context length, and system configuration. Figures shown are estimates based on community benchmarks and may not reflect your exact setup. Product names are trademarks of their respective owners. OwnRig is independent and not affiliated with any hardware or AI model provider.