MacBook Pro M4 Max 36GBBudget pick
36 GB Unified (+4)410 GB/s (+210)
B
Raises estimated decode speed by about 116%.55.8 tok/s decode
Raises estimated decode speed by about 116%.
~$2,499 MSRP
Yi Coder 9B needs ~11.3 GB VRAM. MacBook Pro M1 Pro 32GB has 23.0 GB. With Q4_K_M quantization, expect ~26 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
25.8 tok/s
TTFT
7518 ms
Safe context
131K
Memory
11.3 GB / 23.0 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 | B | Runs well | 25.8 tok/s | 4101 ms | 131K |
| Coding | B | Runs well | 25.8 tok/s | 7518 ms | 131K |
| Agentic Coding | B | Runs well | 25.8 tok/s | 10935 ms | 131K |
| Reasoning | B | Runs well | 25.8 tok/s | 8885 ms | 131K |
| RAG | B | Runs well | 25.8 tok/s | 13669 ms | 131K |
How Yi Coder 9B (9B params) fits at each quantization level on MacBook Pro M1 Pro 32GB (23.0 GB usable).
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 3.5 GB | Low | B57 |
Q3_K_S | 3 | 4.4 GB | Low | B58 |
NVFP4 | 4 | 5.0 GB | Medium | B58 |
Q4_K_M | 4 | 5.5 GB | Medium | B58 |
Q5_K_M | 5 | 6.5 GB | High | B59 |
Q6_K | 6 | 7.4 GB | High | B59 |
Q8_0 | 8 | 9.6 GB | Very High | B61 |
F16Best for your GPU | 16 | 18.5 GB | Maximum | B62 |
Copy-paste commands to run Yi Coder 9B on your machine.
Run
lms load Yi-Coder-9B-Chat && lms server startUpgrade options
Raises estimated decode speed by about 116%.
~$2,499 MSRP
Raises estimated decode speed by about 188%.
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, MacBook Pro M1 Pro 32GB can run Yi Coder 9B with a B grade (Runs well). Expected decode speed: 25.8 tok/s.
Yi Coder 9B (9B parameters) requires approximately 11.3 GB of memory with Q4_K_M quantization.
The recommended quantization for Yi Coder 9B is Q4_K_M, which balances quality and memory efficiency.
On MacBook Pro M1 Pro 32GB, Yi Coder 9B achieves approximately 25.8 tokens per second decode speed with a time-to-first-token of 7518ms using Q4_K_M quantization.
For coding workloads, Yi Coder 9B on MacBook Pro M1 Pro 32GB receives a B grade with 25.8 tok/s and 131K context.
On MacBook Pro M1 Pro 32GB, Yi Coder 9B can safely use up to 131K tokens of context. The model's official context limit is 131K, but available memory constrains the safe maximum.
Not always. MacBook Pro M1 Pro 32GB 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/yi-coder-9b-on-m1-pro-32gb" 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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