Aya Expanse 32B needs ~29.8 GB VRAM. Mac mini M4 64GB has 46.1 GB. With Q4_K_M quantization, expect ~9 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
Fit status
Runs well
Decode
8.7 tok/s
TTFT
22344 ms
Safe context
8K
Memory
29.8 GB / 46.1 GB
This setup is broadly balanced for this model.
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.
| Workload | Grade | Fit | Decode | TTFT | Context |
|---|---|---|---|---|---|
| Chat | C | Runs well | 8.7 tok/s | 12188 ms | 8K |
| Coding | C | Runs well | 8.7 tok/s | 22344 ms | 8K |
| Agentic Coding | C | Runs well | 8.7 tok/s | 32501 ms | 8K |
| Reasoning | C | Runs well | 8.7 tok/s | 26407 ms | 8K |
| RAG | C | Runs well | 8.7 tok/s | 40626 ms | 8K |
How Aya Expanse 32B (32B params) fits at each quantization level on Mac mini M4 64GB (46.1 GB usable).
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 12.5 GB | Low | C50 |
Q3_K_S | 3 | 15.7 GB | Low | C51 |
NVFP4 | 4 | 17.9 GB | Medium | C51 |
Q4_K_M | 4 | 19.5 GB | Medium | C52 |
Q5_K_M | 5 | 23.0 GB | High | C53 |
Q6_K | 6 | 26.2 GB | High | C54 |
Q8_0Best for your GPU | 8 | 34.2 GB | Very High | C53 |
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
Raises estimated decode speed by about 285%.
Adds memory headroom for longer context windows and future model growth.
~$2,499 MSRP
Raises estimated decode speed by about 256%.
Adds memory headroom for longer context windows and future model growth.
~$3,999 MSRP
Yes, Mac mini M4 64GB can run Aya Expanse 32B with a C grade (Runs well). Expected decode speed: 8.7 tok/s.
Aya Expanse 32B (32B parameters) requires approximately 29.8 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 Mac mini M4 64GB, Aya Expanse 32B achieves approximately 8.7 tokens per second decode speed with a time-to-first-token of 22344ms using Q4_K_M quantization.
For coding workloads, Aya Expanse 32B on Mac mini M4 64GB receives a C grade with 8.7 tok/s and 8K context.
On Mac mini M4 64GB, 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.
Not always. Mac mini M4 64GB 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-mini-64gb" 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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