Command R 35B needs ~31.6 GB VRAM. Mac Studio M2 Ultra 64GB has 46.1 GB. With Q4_K_M quantization, expect ~24 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
23.6 tok/s
TTFT
8191 ms
Safe context
111K
Memory
31.6 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 | A | Runs well | 23.6 tok/s | 4468 ms | 111K |
| Coding | A | Runs well | 23.6 tok/s | 8191 ms | 111K |
| Agentic Coding | A | Runs well | 23.6 tok/s | 11915 ms | 111K |
| Reasoning | A | Runs well | 23.6 tok/s | 9681 ms | 111K |
| RAG | A | Runs well | 23.6 tok/s | 14893 ms | 111K |
How Command R 35B (35B params) fits at each quantization level on Mac Studio M2 Ultra 64GB (46.1 GB usable).
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 13.7 GB | Low | A71 |
Q3_K_S | 3 | 17.2 GB | Low | A72 |
NVFP4 | 4 | 19.6 GB | Medium | A73 |
Q4_K_M | 4 | 21.3 GB | Medium | A74 |
Q5_K_M | 5 | 25.2 GB | High | A75 |
Q6_K | 6 | 28.7 GB | High | A74 |
Q8_0Best for your GPU | 8 | 37.5 GB | Very High | A74 |
F16 | 16 | 71.8 GB | Maximum | F0 |
Copy-paste commands to run Command R 35B on your machine.
Run
ollama run command-rYour hardware
| Model | Params | Grade | Decode | Capabilities |
|---|---|---|---|---|
 Kimi Linear 48B A3B | 48B | A | 15.8 tok/s |
Yes, Mac Studio M2 Ultra 64GB can run Command R 35B with a A grade (Runs well). Expected decode speed: 23.6 tok/s.
Command R 35B (35B parameters) requires approximately 31.6 GB of memory with Q4_K_M quantization.
The recommended quantization for Command R 35B is Q4_K_M, which balances quality and memory efficiency.
On Mac Studio M2 Ultra 64GB, Command R 35B achieves approximately 23.6 tokens per second decode speed with a time-to-first-token of 8191ms using Q4_K_M quantization.
For coding workloads, Command R 35B on Mac Studio M2 Ultra 64GB receives a A grade with 23.6 tok/s and 111K context.
On Mac Studio M2 Ultra 64GB, Command R 35B can safely use up to 111K tokens of context. The model's official context limit is 131K, but available memory constrains the safe maximum.
Not always. Mac Studio M2 Ultra 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/command-r-35b-on-m2-ultra-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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