Can I Run Qwen3-Coder on MacBook Pro 16" (M4 Max, 128 GB)?
Autor: Jakub Rusinowski · Ostatnia aktualizacja: 29 września 2026
Yes
Yes — Qwen3-Coder-Next (80B-A3B MoE) at Q8_0 needs about 86.1 GB of the 96 GB usable on MacBook Pro 16" (M4 Max, 128 GB) (~9.9 GB spare), at ~70.2 tok/s (estimated), with room for about 262,144 tokens of context.
Confidence: high · Recommended quantization: Q8_0 · Estimated speed: ~70.2 tok/s
See what else this hardware can run →
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MacBook Pro 16" (M4 Max, 128 GB) — what it gives a model
| Usable memory for models | 96 GB |
| Memory bandwidth | 546 GB/s |
| Form factor | Laptop |
| Operating system | macOS |
| Memory upgradeable | No — soldered |
Qwen3-Coder on MacBook Pro 16" (M4 Max, 128 GB): memory by quantization
| Quant | Memory needed | Fits 96 GB? | Max context | Est. speed | Download |
|---|---|---|---|---|---|
| F16 | 161.1 GB | ✗ No | — | — | 160 GB |
| Q8_0 | 86.1 GB | ✓ Yes | 256K | ~70.2 tok/s | 85 GB |
| Q6_K | 66.7 GB | ✓ Yes | 256K | ~84.6 tok/s | 65.6 GB |
| Q5_K_M | 57.8 GB | ✓ Yes | 256K | ~93.4 tok/s | 56.7 GB |
| Q4_K_M | 49.4 GB | ✓ Yes | 256K | ~103.6 tok/s | 48.3 GB |
| Q3_K_M | 35.2 GB | ✓ Yes | 256K | ~127 tok/s | 34.1 GB |
| Q2_K | 27.4 GB | ✓ Yes | 256K | ~145 tok/s | 26.3 GB |
Which Qwen3-Coder sizes fit
| Variant | Needs at Q4_K_M | Fits? | Est. speed |
|---|---|---|---|
| Qwen3-Coder 480B-A35B (MoE) | 291.6 GB | ✗ Too large | — |
| Qwen3-Coder-Next (80B-A3B MoE) | 49.4 GB | ✓ Fits | ~103.6 tok/s |
| Qwen3-Coder 30B-A3B (MoE) | 20 GB | ✓ Fits | ~90.9 tok/s |
What to watch out for
- 1 larger variant of Qwen3-Coder does not fit and would need CPU offload or different hardware.
- Memory on this machine is not upgradeable, so the configuration you buy is the ceiling for every model you will ever run on it.
MacBook Pro M4 Max 128 GB limitations
- Unified memory is soldered — the 128 GB decision is permanent and cannot be upgraded later.
- Sustained decode speed on battery is materially below the plugged-in figures quoted here.
Recommended setup
Ollama or LM Studio (Metal) — MLX for the fastest Apple-native throughput
How these numbers are calculated
- Memory need = quantized weights + KV cache at 8,192 tokens (f16) + 0.8 GB runtime overhead.
- 128 GB unified memory at 546 GB/s, shared between CPU and GPU.
- macOS reserves a share of unified memory for the system, so not all of it is available to a model.
- Throughput is a memory-bandwidth roofline estimate, not a measurement. It is labelled "estimated" everywhere it appears.
- KV cache is computed from this model's published attention configuration.
FAQ
Can I run Qwen3-Coder on MacBook Pro 16" (M4 Max, 128 GB)?
Yes — Qwen3-Coder-Next (80B-A3B MoE) at Q8_0 needs about 86.1 GB of the 96 GB usable on MacBook Pro 16" (M4 Max, 128 GB) (~9.9 GB spare), at ~70.2 tok/s (estimated), with room for about 262,144 tokens of context.
Which quantization of Qwen3-Coder should I use on MacBook Pro 16" (M4 Max, 128 GB)?
Q8_0 — it needs about 86.1 GB of the 96 GB available, downloads as roughly 85 GB, and runs at an estimated 70.2 tokens/sec with up to 256K of context.
What limits Qwen3-Coder on MacBook Pro 16" (M4 Max, 128 GB)?
Nothing binding — the model fits with headroom and generates at a usable speed on this hardware.
Which runtime should I use?
Ollama or LM Studio (Metal) — MLX for the fastest Apple-native throughput
Other Computers
- Qwen3-Coder on MacBook Pro M4 Max 48 GB
- Qwen3-Coder on MacBook Pro M4 Pro 24 GB
- Qwen3-Coder on MacBook Air M4 16 GB
Other Models on MacBook Pro 16" (M4 Max, 128 GB)
- SmolLM2 on MacBook Pro 16" (M4 Max, 128 GB)
- SmolLM3 on MacBook Pro 16" (M4 Max, 128 GB)
- StarCoder 2 on MacBook Pro 16" (M4 Max, 128 GB)
- Aya 3B (Tiny Aya) on MacBook Pro 16" (M4 Max, 128 GB)
- VibeThinker on MacBook Pro 16" (M4 Max, 128 GB)
Qwen3-Coder on GPUs
- Qwen3-Coder on NVIDIA GeForce RTX 5070
- Qwen3-Coder on NVIDIA GeForce RTX 5060 Ti 8GB
- Qwen3-Coder on NVIDIA GeForce RTX 5060
- Qwen3-Coder on NVIDIA GeForce RTX 4070 Ti
What This Model Is Good At
Model & Tools
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