Mistral on NVIDIA Ampere

Can I run Mistral 7B v0.3 on an A100 80GB?

Yes. Mistral 7B v0.3 at Q4_K_M uses 5.9 GB of the 74.4 GB available on a A100 80GB, and runs at about 263 tokens per second. You can push the context to 32K.

Runs comfortably

5.9 GB of 74.4 GB · 8%
074 GB
Weights 4.1 GB
KV cache 1.0 GB
Runtime overhead 0.8 GB

Mistral 7B v0.3 at Q4_K_M leaves 68.5 GB spare on a A100 80GB. There is room to raise the context length or move up a quantisation level.

Generation263tok/s
Prompt processing9037tok/s
Max context32Ktokens
KV per 1K tokens0GB

Every quantisation of Mistral 7B v0.3 on a A100 80GB

Highlighted row is the highest quality that still fits at 8K context.

QuantisationbpwWeights TotalVerdictMax ctxtok/s
FP16 / BF16 16.00 13.5 GB 15.3 GB Runs comfortably 32K 89.6
INT8 / W8A8 8.50 7.1 GB 8.9 GB Runs comfortably 32K 162
Q8_0 (GGUF) 8.50 7.1 GB 8.9 GB Runs comfortably 32K 162
FP8 (E4M3) 8.00 6.8 GB 8.6 GB Runs comfortably 32K 170
Q6_K 6.56 5.5 GB 7.4 GB Runs comfortably 32K 203
Q5_K_M 5.67 4.8 GB 6.6 GB Runs comfortably 32K 231
Q5_K_S 5.52 4.7 GB 6.5 GB Runs comfortably 32K 236
Q4_K_M 4.85 4.1 GB 5.9 GB Runs comfortably 32K 263
AWQ 4-bit 4.25 4.0 GB 5.8 GB Runs comfortably 32K 272
GPTQ 4-bit 4.25 4.0 GB 5.8 GB Runs comfortably 32K 272
MXFP4 4.25 4.0 GB 5.8 GB Runs comfortably 32K 272
Q4_K_S 4.58 3.9 GB 5.7 GB Runs comfortably 32K 275
Q4_0 4.55 3.9 GB 5.7 GB Runs comfortably 32K 277
IQ4_XS 4.25 3.6 GB 5.4 GB Runs comfortably 32K 292
Q3_K_M 3.91 3.3 GB 5.2 GB Runs comfortably 32K 312
IQ3_M 3.70 3.2 GB 5.0 GB Runs comfortably 32K 325
IQ3_XXS 3.06 2.7 GB 4.5 GB Runs comfortably 32K 375
Q2_K 2.63 2.3 GB 4.1 GB Runs comfortably 32K 418
IQ2_XXS 2.06 1.8 GB 3.7 GB Runs comfortably 32K 493
IQ1_M 1.75 1.6 GB 3.4 GB Runs comfortably 32K 546

Also worth checking

Mistral 7B v0.3 on every GPU
Full hardware tableEverything that runs on a A100 80GB
Full model tableWhy the KV cache is the part that bites
Guide