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Can MacBook Pro M1 Max 32GB run Llama-4-Scout-17B-16E-Instruct?

Apple · 32 GB LPDDR5 · 400 GB/s bandwidth · Meta · 109.0B (active 17.0B) · MoE · model ctx up to 10240K

FF · No FitComposite score: VRAM headroom × 0.5 + tok/s speed × 0.5. Q4 @ 8K context.
METAL

No — Llama-4-Scout-17B-16E-Instruct at Q4 needs ≈ 62.65 GB even at 4K context, beyond the MacBook Pro M1 Max 32GB's 32 GB LPDDR5. It would only run with heavy CPU/disk offload. Decode at Q4/8K: ≈ 10.6 tok/s (estimated, batch 1). FP16 needs ≈ 222.4 GB — does not fit on this card. Estimates come from memory-bandwidth math; rows tagged measured override estimates. Relative ranking is more reliable than absolute tok/s. Methodology.

Cheapest GPU that can: H100 80GB SXM5 See fit details →or☁️ Rent on RunPod from ~$0.50/hr

Fit & speed by quant and context

QuantContextVRAM neededFits?tok/s (decode)
Q44K62.65 GBNo11.1 ± est.
Q48K default64.35 GBNo10.6 ± est.
Q432K74.55 GBNo7.9 ± est.
FP164K220.7 GBNo
FP168K default222.4 GBNo
FP1632K232.6 GBNo

Fits = weights + KV(ctx) + 1 GB overhead ≤ 95% of VRAM. Measured anchors are context-agnostic; the fit verdict is recomputed per context. A missing tok/s means the model is far beyond this card (offload-only territory).

VRAM breakdown at 8K context

QuantWeightsKV cacheOverheadTotal neededMacBook Pro M1 Max 32GB VRAM
Q459.95 GB3.4 GB1 GB64.35 GB32 GB
FP16218.0 GB3.4 GB1 GB222.4 GB32 GB

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