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Can the Apple M3 Pro (36GB) run Mistral 7B v0.3?

Apple M3 Pro (36GB) × Mistral 7B v0.38K context
YesRuns fully on the GPU
Memory at FP1616.2 GB of 24.1 GB
Weights 14.5 GBKV cache 1.1 GBRuntime 0.6 GB
QuantFP16Full quality
Speed~6tokens per second
Max context32Kthe model's full window
  1. FP16
  2. Q8_0
  3. Q6_K
  4. Q5_K_M
  5. Q4_K_M
  6. Q3_K_M
  7. Q2_K

Yes. The Apple M3 Pro (36GB) can run Mistral 7B v0.3 fully in unified memory at FP16 (full quality), using about 16.2 GB of the 24.1 GB available, at roughly 6 tokens/second.

Try other context lengths

Run it with Ollama

With Ollama installed, one command downloads and starts Mistral 7B v0.3:

ollama run mistral:7b

Ollama's default download is Q4_K_M (about 6.1 GB here). You have room for FP16, which is full quality: pick that GGUF in LM Studio or from Hugging Face.

New to this? Step-by-step setup for the Apple M3 Pro (36GB)

Run it in the cloud

No Apple M3 Pro (36GB)? Run Mistral 7B v0.3 in the cloud.

Rent a cloud GPU by the hour. No upfront cost, stop any time.

Rent a GPU on RunPodRent a GPU on Vast.ai

Memory needed by quantization

At 8,192 tokens of context. The black line marks the 24.1 GB the Apple M3 Pro (36GB) can use. macOS lets the GPU use about 24.1 GB of the 36 GB unified memory by default.

QuantQualityMemoryFits?Speed
FP16Full quality16.2 GBFits~6 tok/s
Q8_0Near-lossless9.4 GBFits~12 tok/s
Q6_KExcellent7.6 GBFits~15 tok/s
Q5_K_MVery good6.8 GBFits~17 tok/s
Q4_K_MGood, most popular6.1 GBFits~20 tok/s
Q3_K_MNoticeably degraded5.2 GBFits~25 tok/s
Q2_KHeavily degraded4.4 GBFits~33 tok/s

Measured speed from real Apple M3 Pro (36GB) owners

Tokens per second that people measured on their own Apple M3 Pro (36GB), next to our estimate.

No one has measured Mistral 7B v0.3 on the Apple M3 Pro (36GB) yet. The speeds above are estimates. Run the benchmark and yours becomes the first real number on this page.

Have an Apple M3 Pro (36GB)? Add your real speed

One command times Mistral 7B v0.3 in your own Ollama, shows you exactly what it would send, and asks before sending anything. No sign-up, no personal data.

macOS and Linux

curl -fsSL https://gpufit.dev/bench.sh | sh -s -- mistral:7b

Windows (PowerShell)

$env:GPUFIT_MODEL="mistral:7b"; irm https://gpufit.dev/bench.ps1 | iex

How the benchmark works

GPUs that run Mistral 7B v0.3 comfortably

Models that run well on the Apple M3 Pro (36GB)

Frequently asked questions

Can Apple M3 Pro (36GB) run Mistral 7B v0.3?

Yes. The Apple M3 Pro (36GB) can run Mistral 7B v0.3 fully in unified memory at FP16 (full quality), using about 16.2 GB of the 24.1 GB available, at roughly 6 tokens/second.

How much VRAM does Mistral 7B v0.3 need?

About 6.1 GB at Q4_K_M with 8,192 tokens of context, and about 16.2 GB at full FP16 precision.

How fast is Mistral 7B v0.3 on the Apple M3 Pro (36GB)?

Roughly 6 tokens per second at FP16, estimated from the Apple M3 Pro (36GB)'s 150 GB/s memory bandwidth.