MistralMistral Large 2 123B on NVIDIA GeForce RTX 5090
RTX 5090 cannot run Mistral Large 2 123B. 32 GB VRAM is insufficient at any quantization level.
Model Size
123B
Device VRAM
32 GB
Bandwidth
1792 GB/s
Quantization
Q3_K_M
Performance by Quantization
OwnRig currently has one published compatibility entry for Mistral Large 2 123B on NVIDIA GeForce RTX 5090 at Q3_K_M. This pairing has limitations — check the rating and notes below.
| Quantization | Speed | TTFT | Fits in VRAM | Rating | Confidence |
|---|---|---|---|---|---|
| Q3_K_M | 4 tok/s | 2500ms | ✗ Offload | Marginal | estimated |
Notes
Q3_K_M
32GB cannot hold 123B at Q3. CPU offloading needed. Marginally usable.
About Mistral Large 2 123B
Mistral Large 2 123B (123B) is a chat, coding, ai coding, reasoning, multi-purpose model. Mistral's flagship 123B parameter model. Wide multilingual performance and code generation. 128K context window. Requires multi-GPU or high-memory Apple Silicon for home use. At Q3/Q2, fits on 2x RTX 4090 or 64 GB+ Apple Silicon.
View all Mistral Large 2 123B hardware options →About NVIDIA GeForce RTX 5090
NVIDIA GeForce RTX 5090 has 32 GB at 1792 GB/s. Street price: $2,199.
See all models NVIDIA GeForce RTX 5090 can run →Builds with NVIDIA GeForce RTX 5090
Estimate method: Community benchmarks. Reference hardware source: github.com (2026-01-15)
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.