MacBook Pro M4 Pro 64GBBudget pick
64 GB Unified (+28)
B
Adds memory headroom for longer context windows and future model growth.21.1 tok/s decode
Adds memory headroom for longer context windows and future model growth.
~$1,599 MSRP
Aya Expanse 32B needs ~26.7 GB VRAM. MacBook Pro M4 Max 36GB has 25.9 GB. With Q4_K_M quantization, expect ~25 tok/s.
Operating mode
Interactive favors responsiveness, while light API and scale-out lean harder on serving readiness. The fit stays the same, but the recommendation lens changes.
Current mode
Balanced
Balanced for general local use. Keeps the ranking neutral across personal and serving workflows.
Select quantization to explore
0.8 GB over capacity — needs offload or smaller quantization
Fit status
Runs with offload (needs ~0.6 GB host RAM)
Decode
25.0 tok/s
TTFT
7737 ms
Safe context
8K
Memory
26.7 GB / 25.9 GB
This setup is broadly balanced for this model.
Very little memory headroom
You can run the model, but there is not much room left for longer context, bigger batches, extra apps, or future model updates.
Shared-memory contention still exists
The OS, browser, and inference runtime all compete for the same physical memory pool, so real-world headroom is less forgiving than raw capacity suggests.
Buy headroom, not only minimum fit
A slightly larger memory tier gives you safer context growth and makes the recommendation more future-proof.
| Workload | Grade | Fit | Decode | TTFT | Context |
|---|---|---|---|---|---|
| Chat | B | Runs with offload | 26.7 tok/s | 3958 ms | 8K |
| Coding | B | Runs with offload (needs ~0.6 GB host RAM) | 25.0 tok/s | 7737 ms | 8K |
| Agentic Coding | C | Very compromised (needs ~2.2 GB host RAM) | 22.0 tok/s | 12772 ms | 8K |
| Reasoning | B | Runs with offload (needs ~0.6 GB host RAM) | 25.0 tok/s | 9144 ms | 8K |
| RAG | C | Very compromised (needs ~2.2 GB host RAM) | 22.0 tok/s | 15965 ms | 8K |
How Aya Expanse 32B (32B params) fits at each quantization level on MacBook Pro M4 Max 36GB (25.9 GB usable).
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 12.5 GB | Low | B55 |
Q3_K_S | 3 | 15.7 GB | Low | B55 |
NVFP4 | 4 | 17.9 GB | Medium | C55 |
Q4_K_MBest for your GPU | 4 | 19.5 GB | Medium | C55 |
Q5_K_M | 5 | 23.0 GB | High | F0 |
Q6_K | 6 | 26.2 GB | High | F0 |
Q8_0 | 8 | 34.2 GB | Very High | F0 |
F16 | 16 | 65.6 GB | Maximum | F0 |
Copy-paste commands to run Aya Expanse 32B on your machine.
Run
ollama run aya-expanse:32bUpgrade options
Adds memory headroom for longer context windows and future model growth.
~$1,599 MSRP
Raises estimated decode speed by about 34%.
Adds memory headroom for longer context windows and future model growth.
~$2,499 MSRP
Adds memory headroom for longer context windows and future model growth.
~$2,499 MSRP
Yes, MacBook Pro M4 Max 36GB can run Aya Expanse 32B with a B grade (Runs with offload (needs ~0.6 GB host RAM)). Expected decode speed: 25.0 tok/s.
Aya Expanse 32B (32B parameters) requires approximately 26.7 GB of memory with Q4_K_M quantization.
The recommended quantization for Aya Expanse 32B is Q4_K_M, which balances quality and memory efficiency.
On MacBook Pro M4 Max 36GB, Aya Expanse 32B achieves approximately 25.0 tokens per second decode speed with a time-to-first-token of 7737ms using Q4_K_M quantization.
For coding workloads, Aya Expanse 32B on MacBook Pro M4 Max 36GB receives a B grade with 25.0 tok/s and 8K context.
On MacBook Pro M4 Max 36GB, Aya Expanse 32B can safely use up to 8K tokens of context. The model's official context limit is 8K, but available memory constrains the safe maximum.
Buy headroom, not only minimum fit. A slightly larger memory tier gives you safer context growth and makes the recommendation more future-proof.
Not always. MacBook Pro M4 Max 36GB can often fit larger models thanks to unified memory, but a discrete GPU with dedicated high-bandwidth VRAM may still decode faster once the model fits. For this combination, the important distinction is capacity versus sustained throughput.
Paste this snippet into any page to show a live fit card.
<iframe src="https://willitrunai.com/embed/aya-expanse-32b-on-m4-max-36gb" width="400" height="180" frameborder="0" style="border:none;border-radius:12px;overflow:hidden;" title="Will It Run AI — fit result"></iframe>
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