Home / Models / Mistral 7B Instruct v0.3 / NVIDIA RTX 6000 24 GB
Can Mistral 7B Instruct v0.3 run on NVIDIA RTX 6000 24 GB?
Yes. Calculated memory fit: Mistral 7B Instruct v0.3 can run entirely in this GPU’s usable VRAM at one or more supported quantizations.
Can it run?
- Can it run?
- Yes, full GPU fit (calculated estimate).
- Full GPU fit?
- Yes
- Model
- Mistral 7B Instruct v0.3 · 7.3B
- GPU
- NVIDIA RTX 6000 24 GB · 24 GB advertised
Memory calculation
Breakdown for Q4 at 8K context, batch size 1. Calculator v1.0.0.
| Model weights | 4.3 GB |
|---|---|
| KV cache | 1.0 GB |
| Runtime reserve | 0.7 GB |
| Safety margin | 0.4 GB |
| Required (estimated) | 6.3 GB |
| GPU usable VRAM | 21.6 GB |
Result: FITS IN VRAM
Quantization table
| Quantization | 2K | 4K | 8K | 16K | 32K |
|---|---|---|---|---|---|
| BF16 | Fits | Fits | Fits | Fits | Fits |
| FP16 | Fits | Fits | Fits | Fits | Fits |
| Q3 | Fits | Fits | Fits | Fits | Fits |
| Q4 | Fits | Fits | Fits | Fits | Fits |
| Q5 | Fits | Fits | Fits | Fits | Fits |
| Q6 | Fits | Fits | Fits | Fits | Fits |
| Q8 | Fits | Fits | Fits | Fits | Fits |
What fits entirely in VRAM?
- BF16 at 16K context
- BF16 at 2K context
- BF16 at 32K context
- BF16 at 4K context
- BF16 at 8K context
- FP16 at 16K context
- FP16 at 2K context
- FP16 at 32K context
- FP16 at 4K context
- FP16 at 8K context
- Q3 at 16K context
- Q3 at 2K context
What requires RAM offload?
Offload is shown only when the model does not fully fit in usable VRAM but stays within the modeled offload allowance.
Available graphics cards
These SKUs use this GPU chip. Amazon CTAs appear only for EXACT/HIGH matches. Absence of a price does not change the compatibility result above.
HP 5JH80AA graphics card NVIDIA Quadro RTX 6000 24 GB GDDR6
24 GB · Amazon unmatched
Sources
Model: official config mistralai/Mistral-7B-Instruct-v0.3 (main). GPU/product specs: Icecat. Compatibility: RigForAI calculator v1.0.0 estimated VRAM · Q8 at 8K: FITS_IN_VRAM. Amazon: affiliate commerce match, not a spec source.