DeepSeek R1 Distill 8B needs ~14.6 GB VRAM. Mac Studio M2 Ultra 64GB has 46.1 GB. With Q4_K_M quantization, expect ~102 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
102.2 tok/s
TTFT
1894 ms
Safe context
33K
Memory
14.6 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 | B | Runs well | 102.2 tok/s | 1033 ms | 33K |
| Coding | B | Runs well | 102.2 tok/s | 1894 ms | 33K |
| Agentic Coding | B | Runs well | 95.1 tok/s | 2962 ms | 33K |
| Reasoning | B | Runs well | 102.2 tok/s | 2238 ms | 33K |
| RAG | B | Runs well | 102.2 tok/s | 3444 ms | 33K |
How DeepSeek R1 Distill 8B (8B params) fits at each quantization level on Mac Studio M2 Ultra 64GB (46.1 GB usable).
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 3.1 GB | Low | B58 |
Q3_K_S | 3 | 3.9 GB | Low | B58 |
NVFP4 | 4 |
Copy-paste commands to run DeepSeek R1 Distill 8B on your machine.
Run
ollama run deepseek-r1:8bYes, Mac Studio M2 Ultra 64GB can run DeepSeek R1 Distill 8B with a B grade (Runs well). Expected decode speed: 102.2 tok/s.
DeepSeek R1 Distill 8B (8B parameters) requires approximately 14.6 GB of memory with Q4_K_M quantization.
The recommended quantization for DeepSeek R1 Distill 8B is Q4_K_M, which balances quality and memory efficiency.
On Mac Studio M2 Ultra 64GB, DeepSeek R1 Distill 8B achieves approximately 102.2 tokens per second decode speed with a time-to-first-token of 1894ms using Q4_K_M quantization.
For coding workloads, DeepSeek R1 Distill 8B on Mac Studio M2 Ultra 64GB receives a B grade with 102.2 tok/s and 33K context.
On Mac Studio M2 Ultra 64GB, DeepSeek R1 Distill 8B can safely use up to 33K tokens of context. The model's official context limit is 33K, 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/deepseek-r1-distill-8b-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>
Preview:
4.5 GB |
| Medium |
| B58 |
Q4_K_M | 4 | 4.9 GB | Medium | B58 |
Q5_K_M | 5 | 5.8 GB | High | B59 |
Q6_K | 6 | 6.6 GB | High | B59 |
Q8_0 | 8 | 8.6 GB | Very High | B59 |
F16Best for your GPU | 16 | 16.4 GB | Maximum | B62 |
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.