~/can-i-run/mistral-7b
Mistral provider

Can I run Mistral 7B v0.3?

Short answer: yes, on a RTX 3090 (24GB) at FP16/BF16. Long answer below.

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The math, in one paragraph.

$ ./vrambudget --explain mistral-7b

Mistral 7B v0.3 has 7.2B parameters. At FP16 that's 14 GB of raw weights. Quantization shrinks that, but you also need budget for the KV cache (definition), framework overhead, and safety headroom. The rule of thumb: real usable budget on a card is roughly its nameplate VRAM minus 25%. That's how the table below was computed.

What hardware actually fits.

$ grep "fits" gpus.json
FP16/BF16
14GB
27 GPUs fit
RTX 309024GBRTX 3090 Ti24GBRTX 409024GBRX 7900 XTX24GB+ 23 more
Q8_0
7.7GB
39 GPUs fit
RTX 3060 12GB12GBRTX 3080 Ti12GBRTX 407012GBRTX 4070 Super12GB+ 35 more
Q5_K_M
5.0GB
42 GPUs fit
RTX 30708GBRTX 40608GBRTX 308010GBRTX 3060 12GB12GB+ 38 more
Q4_K_M
4.0GB
42 GPUs fit
RTX 30708GBRTX 40608GBRTX 308010GBRTX 3060 12GB12GB+ 38 more
Q3_K_M
3.1GB
42 GPUs fit
RTX 30708GBRTX 40608GBRTX 308010GBRTX 3060 12GB12GB+ 38 more

Pick your path.

$ ls strategies/
Tightest budget

Smallest GPU that fits Mistral 7B v0.3 at any quant: RTX 3090 at FP16/BF16.

Reference quality (FP16)

Lossless inference needs 14 GB. Pick from 27 cards.

Best quality on a 24GB card

FP16/BF16 fits comfortably (14 GB weights).

Tune the math yourself

Open the calculator pre-tuned for Mistral 7B v0.3: ↗ /calc?model=mistral-7b

See the full model page.

$ ./open
$ openMistral 7B v0.37.2BMistral · ctx 32K$ rankBest GPU for Mistral 7B v0.3see the ranking →ranked by fit quality

Discussion.

$ gh discussion list

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