Yi 1.5 9B needs ~35.5 GB VRAM. Mac Studio M3 Ultra 256GB has 184.3 GB. With Q4_K_M quantization, expect ~110 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
110.3 tok/s
TTFT
1755 ms
Safe context
4K
Memory
35.5 GB / 184.3 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 | 110.3 tok/s | 957 ms | 4K |
| Coding | C | Runs well | 110.3 tok/s | 1755 ms | 4K |
| Agentic Coding | C | Runs well | 110.3 tok/s | 2553 ms | 4K |
| Reasoning | C | Runs well | 110.3 tok/s | 2074 ms | 4K |
| RAG | C | Runs well | 110.3 tok/s | 3191 ms | 4K |
How Yi 1.5 9B (9B params) fits at each quantization level on Mac Studio M3 Ultra 256GB (184.3 GB usable).
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 3.5 GB | Low | C42 |
Q3_K_S | 3 | 4.4 GB | Low | C41 |
NVFP4 | 4 |
Copy-paste commands to run Yi 1.5 9B on your machine.
Run
lms load Yi-1.5-9B-Chat && lms server startYes, Mac Studio M3 Ultra 256GB can run Yi 1.5 9B with a C grade (Runs well). Expected decode speed: 110.3 tok/s.
Yi 1.5 9B (9B parameters) requires approximately 35.5 GB of memory with Q4_K_M quantization.
The recommended quantization for Yi 1.5 9B is Q4_K_M, which balances quality and memory efficiency.
On Mac Studio M3 Ultra 256GB, Yi 1.5 9B achieves approximately 110.3 tokens per second decode speed with a time-to-first-token of 1755ms using Q4_K_M quantization.
For coding workloads, Yi 1.5 9B on Mac Studio M3 Ultra 256GB receives a C grade with 110.3 tok/s and 4K context.
On Mac Studio M3 Ultra 256GB, Yi 1.5 9B can safely use up to 4K tokens of context. The model's official context limit is 4K, but available memory constrains the safe maximum.
Paste this snippet into any page to show a live fit card.
<iframe src="https://willitrunai.com/embed/yi-1.5-9b-on-m3-ultra-256gb" width="400" height="180" frameborder="0" style="border:none;border-radius:12px;overflow:hidden;" title="Will It Run AI — fit result"></iframe>
Preview:
5.0 GB |
| Medium |
| C41 |
Q4_K_M | 4 | 5.5 GB | Medium | C41 |
Q5_K_M | 5 | 6.5 GB | High | C42 |
Q6_K | 6 | 7.4 GB | High | C42 |
Q8_0 | 8 | 9.6 GB | Very High | C42 |
F16Best for your GPU | 16 | 18.5 GB | Maximum | C42 |
Not always. Mac Studio M3 Ultra 256GB 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.