Can I Run Codestral on Apple M5?

Written by Jakub Rusinowski · Last updated July 12, 2026

Yes, comfortably — Codestral 22B at Q4_K_M needs 16.1 GB at 8K context (13.4 GB weights + 2.7 GB KV cache/overhead), leaving ~7.9 GB of the Apple M5's 24 GB usable memory, at ~6 tok/s (est.), with room for up to 32K context.

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Apple MacBook Air M5
24 GB unified memory · 153 GB/s
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Apple M5 Specs

VRAM32 GB unified memory
Memory Bandwidth153 GB/s

Codestral 22B on the Apple M5: VRAM by quantization

QuantVRAM neededFits 32 GB?Max contextWhole PC
F1647.1 GB✗ No——
Q8_026.3 GB✗ No——
Q6_K20.9 GB✓ Yes16K—
Q5_K_M18.4 GB✓ Yes16K—
Q4_K_M16.1 GB✓ Yes32K—
Q3_K_M12.1 GB✓ Yes32K—
Q2_K10 GB✓ Yes32K—

Assumes an 8K-token context with an f16 KV cache. A longer window needs more; a quantized KV cache needs less. “Max context” is the largest window that still fits in 32 GB of unified memory. Figures are estimates from parameter count, quantization and memory bandwidth — the analyzer lets you tune KV-cache quant and context.

Superseded model. Codestral has been superseded by Devstral. This page is kept for reference; the newer family is a better starting point. Can I run Devstral on Apple M5? →

Context costs VRAM too. At Q4_K_M on the Apple M5: 8K 16.1 GB · 32K 21.7 GB. Every window this model publishes still fits 32 GB.

No compatible GPU? Codestral 22B on 16 GB of system RAM, CPU only: runs, but it is tight.

Codestral Sizes That Fit the Apple M5 (at 8K context)

Codestral 22BQ4_K_M · 16.1 GB at 8K context · ~6 tok/s (est.)
Won't fit — rent Codestral instead

Codestral needs ~16 GB but this GPU has 32 GB. Rent a RTX 4090 (24 GB)-class GPU by the hour instead of buying one:

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FAQ

Can I run Codestral on the Apple M5?

Yes, comfortably — Codestral 22B at Q4_K_M needs 16.1 GB at 8K context (13.4 GB weights + 2.7 GB KV cache/overhead), leaving ~7.9 GB of the Apple M5's 24 GB usable memory, at ~6 tok/s (est.), with room for up to 32K context.

What's the best Codestral size for the Apple M5?

Codestral 22B at Q4_K_M quantization needs 16.1 GB at 8K context (13.4 GB weights + 2.7 GB KV cache/overhead), estimated ~6 tokens/sec, up to 32K context.

Codestral on Other GPUs

Popular Models on the Apple M5

VRAM Tier

Troubleshooting

Buying Guide

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