Intel Arc A770 16GBBudget pick560 GB/s (+410)
B
Raises estimated decode speed by about 130%.55.5 tok/s decode
Raises estimated decode speed by about 130%.
Adds memory headroom for longer context windows and future model growth.
~$349 MSRP
DeepSeek R1 Distill 8B needs ~9.7 GB VRAM. MacBook Pro M3 Pro 18GB has 13.0 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
24.1 tok/s
TTFT
8026 ms
Safe context
33K
Memory
9.7 GB / 13.0 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 | 24.1 tok/s | 4378 ms | 33K |
| Coding | B | Runs well | 24.1 tok/s | 8026 ms | 33K |
| Agentic Coding | B | Tight fit | 24.1 tok/s | 11674 ms | 33K |
| Reasoning | B | Runs well | 24.1 tok/s | 9485 ms | 33K |
| RAG | B | Tight fit | 24.1 tok/s | 14593 ms | 33K |
How DeepSeek R1 Distill 8B (8B params) fits at each quantization level on MacBook Pro M3 Pro 18GB (13.0 GB usable).
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 3.1 GB | Low | B65 |
Q3_K_S | 3 | 3.9 GB | Low | B66 |
NVFP4 | 4 |
Copy-paste commands to run DeepSeek R1 Distill 8B on your machine.
Run
ollama run deepseek-r1:8bUpgrade options
Intel Arc A770 16GBBudget pickRaises estimated decode speed by about 130%.
Adds memory headroom for longer context windows and future model growth.
~$349 MSRP
RTX 5060 Ti 16GBBest valueRaises estimated decode speed by about 154%.
Adds memory headroom for longer context windows and future model growth.
~$449 MSRP
Yes, MacBook Pro M3 Pro 18GB can run DeepSeek R1 Distill 8B with a B grade (Runs well). Expected decode speed: 24.1 tok/s.
DeepSeek R1 Distill 8B (8B parameters) requires approximately 9.7 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 MacBook Pro M3 Pro 18GB, DeepSeek R1 Distill 8B achieves approximately 24.1 tokens per second decode speed with a time-to-first-token of 8026ms using Q4_K_M quantization.
For coding workloads, DeepSeek R1 Distill 8B on MacBook Pro M3 Pro 18GB receives a B grade with 24.1 tok/s and 33K context.
On MacBook Pro M3 Pro 18GB, 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-m3-pro-18gb" 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 |
| B67 |
Q4_K_M | 4 | 4.9 GB | Medium | B67 |
Q5_K_M | 5 | 5.8 GB | High | B69 |
Q6_K | 6 | 6.6 GB | High | B69 |
Q8_0Best for your GPU | 8 | 8.6 GB | Very High | B68 |
F16 | 16 | 16.4 GB | Maximum | F0 |
Not always. MacBook Pro M3 Pro 18GB 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.