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Can I run Mistral 7B v0.3 on Apple M3 Max (64GB)?

Yes: Mistral 7B v0.3 runs on Apple M3 Max (64GB) with F16 at roughly 17 tokens/s. Estimated memory 15.3 GiB at 8,192 tokens of context.

With F16 you can push the context to about 32,768 tokens before memory runs out (F16 KV cache).

Memory by quantisation (8,192-token context)

QuantisationMemoryVerdictEst. speed
F16Unquantized reference15.3 GiBFits~17 tok/s
Q8_0Near-lossless9.0 GiBFits~30 tok/s
Q6_KVery close to F167.3 GiBFits~37 tok/s
Q5_K_MGreat quality/size6.6 GiBFits~42 tok/s
Q4_K_MBest default for most5.9 GiBFits~48 tok/s
IQ4_XSSmaller 4-bit (imatrix)5.4 GiBFits~53 tok/s
Q3_K_MNoticeable loss5.1 GiBFits~56 tok/s
Q2_KLast resort; big loss4.6 GiBFits~63 tok/s

Apple M3 Max (64GB) offers about 64 GiB of memory (75% usable for a model) at 400 GB/s. Speed is a bandwidth-bound estimate of single-stream generation at 65% efficiency; real results vary by runtime, drivers and settings, so measure on your machine.

How this is calculated

Weights โ‰ˆ parameters ร— bits per weight รท 8. KV cache โ‰ˆ 2 ร— 32 layers ร— 8 KV heads ร— 128 head dim ร— 2 bytes per token. Decode speed โ‰ˆ efficiency ร— memory bandwidth รท bytes read per token. Learn the maths in VRAM math and memory bandwidth, or try the VRAM calculator.

Running slowly or out of memory? See CUDA out of memory and the quantisation lesson.