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Can I run this LLM?

Can a MacBook Air / Mac mini M4 (24GB) run AesCode 32B (text-only)?

AesCode · Apache 2.0 · estimated for a 24.0 GB machine at 4K context.

Yes, but it's tight.

Tight / slow

Best fit: AesCode 32B (text-only) at Q2_K · 13.0 GB weights · 6–8 tok/s on a MacBook Air / Mac mini M4 (24GB).

Pack & allocation notes: Text-only estimates exclude the vision projector and image-input runtime memory. The FP16 label uses supplied BF16 weights.

Arena Text Overall · style-controlled

UnratedNo exact match

No reviewed exact Arena match

No reviewed exact model/configuration match in the Arena Text Overall style-controlled snapshot. No family or editorial score is substituted. Local quantization quality is unmeasured.

Snapshot published 2026-10-08 · snapshot imported 2026-10-11 UTC · validated last-good data · manual refresh

Arena leaderboard dataset · Arena / lmarena-ai, Arena Leaderboard Dataset (CC BY 4.0). Selected Text Overall style-controlled rows; field names adapted, ratings unchanged. · dataset CC BY 4.0 · revision e16f90232986

Total memory at 4K context
14.9 GB
Weights + KV cache + runtime overhead
Estimated generation
6–8 tok/s
Estimated first token
~93s

Every quantization on this machine

On small screens, each quant lists every metric below its name. On wider screens, scroll sideways for total memory, speed and fit. Keyboard: focus the table, then use the arrow keys. Quant names stay visible.

AesCode 32B (text-only) quantizations on MacBook Air / Mac mini M4 (24GB), estimated at 4K context. Weights and total memory are shown separately.
QuantWeightsTotal memorySpeedFit
Q2_K13.0 GB14.9 GB6–8 tok/sTight / slow
Q3_K_M16.5 GB18.4 GB— not residentWon't fit
Q4_K_M20.5 GB22.4 GB— not residentWon't fit
Q5_K_M23.8 GB25.7 GB— not residentWon't fit
Q6_K28.0 GB29.9 GB— not residentWon't fit
Q8_034.8 GB36.7 GB— not residentWon't fit
FP1665.5 GB67.4 GB— not residentWon't fit

Ran AesCode 32B (text-only) on a MacBook Air / Mac mini M4 (24GB)? Add your real numbers →