Mac Studio M2 Ultra 128GBBudget pick
128 GB Unified (+48)
B
This setup is broadly balanced for this model.102.2 tok/s decode
~$3,999 MSRP
DeepSeek R1 Distill 8B needs ~16.0 GB VRAM. NVIDIA H100 PCIe 80GB has 80.0 GB. With Q4_K_M quantization, expect ~112 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
112.0 tok/s
TTFT
1729 ms
Safe context
33K
Memory
16.0 GB / 80.0 GB
This setup is broadly balanced for this model.
No major red flags
This recommendation has enough memory headroom and acceptable estimated speed for the selected workload.
| Workload | Grade | Fit | Decode | TTFT | Context |
|---|---|---|---|---|---|
| Chat | B | Runs well | 112.0 tok/s | 943 ms | 33K |
| Coding | B | Runs well | 112.0 tok/s | 1729 ms | 33K |
| Agentic Coding | B | Runs well | 112.0 tok/s | 2514 ms | 33K |
| Reasoning | B | Runs well | 112.0 tok/s | 2043 ms | 33K |
| RAG | B | Runs well | 112.0 tok/s | 3143 ms | 33K |
Inference speed
Estimated decode speed (tokens/sec) for DeepSeek R1 Distill 8B at Q4_K_M across popular GPUs and Apple Silicon, using the fastest local runtime per device. Fastest is RTX 5090 32GB at ~112 tok/s. Speed is memory-bandwidth bound, so cards that fit the whole model in VRAM run far faster than ones that offload to system RAM.
| GPU / Mac | Memory | Quant | Speed (tok/s) | Fits? |
|---|---|---|---|---|
 RTX 5090 32GB | 32 GB | Q4_K_M | 112.0 | Fits |
| RTX 4090 24GB | 24 GB | Q4_K_M | 112.0 | Fits |
| RTX 4080 Super 16GB | 16 GB | Q4_K_M | 112.0 | Fits |
| RTX 3090 24GB | 24 GB | Q4_K_M | 112.0 | Fits |
RX 7900 XTX 24GB | 24 GB | Q4_K_M | 112.0 | Fits |
Mac Studio M3 Ultra 256GB | 256 GB | Q4_K_M | 112.0 | Fits |
Mac Studio M2 Ultra 128GB | 128 GB | Q4_K_M | 102.2 | Fits |
Mac Studio M1 Ultra 128GB | 128 GB | Q4_K_M | 96.9 | Fits |
| RTX 4070 12GB | 12 GB | Q4_K_M | 83.3 | Fits |
MacBook Pro M4 Max 128GB | 128 GB | Q4_K_M | 82.6 | Fits |
MacBook Pro M4 Max 64GB | 64 GB | Q4_K_M | 82.6 | Fits |
MacBook Pro M3 Max 64GB | 64 GB | Q4_K_M | 52.9 | Fits |
| RTX 3060 12GB | 12 GB | Q4_K_M | 52.3 | Fits |
MacBook Pro M1 Max 64GB | 64 GB | Q4_K_M | 48.5 | Fits |
MacBook Pro M4 Pro 48GB | 48 GB | Q4_K_M | 42.6 | Fits |
| RTX 4060 8GB | 8 GB | Q4_K_M | 26.6 | Heavy offload |
Estimates for single-stream decoding at Q4_K_M; real tokens/sec varies with prompt length, context, batch size, and runtime build. Prompt processing (prefill) is faster than the decode figures shown here.
How DeepSeek R1 Distill 8B (8B params) fits at each quantization level on NVIDIA H100 PCIe 80GB (80.0 GB usable).
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 3.1 GB | Low | B56 |
Q3_K_S | 3 | 3.9 GB | Low | B56 |
NVFP4 | 4 | 4.5 GB | Medium | B56 |
Q4_K_M | 4 | 4.9 GB | Medium | B56 |
Q5_K_M | 5 | 5.8 GB | High | B56 |
Q6_K | 6 | 6.6 GB | High | B56 |
Q8_0 | 8 | 8.6 GB | Very High | B57 |
F16Best for your GPU | 16 | 16.4 GB | Maximum | B58 |
Copy-paste commands to run DeepSeek R1 Distill 8B on your machine.
Run
ollama run deepseek-r1:8bUpgrade options
Yes, NVIDIA H100 PCIe 80GB can run DeepSeek R1 Distill 8B with a B grade (Runs well). Expected decode speed: 112.0 tok/s.
DeepSeek R1 Distill 8B (8B parameters) requires approximately 16.0 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 NVIDIA H100 PCIe 80GB, DeepSeek R1 Distill 8B achieves approximately 112.0 tokens per second decode speed with a time-to-first-token of 1729ms using Q4_K_M quantization.
For coding workloads, DeepSeek R1 Distill 8B on NVIDIA H100 PCIe 80GB receives a B grade with 112.0 tok/s and 33K context.
On NVIDIA H100 PCIe 80GB, 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-h100-pcie-80gb" width="400" height="180" frameborder="0" style="border:none;border-radius:12px;overflow:hidden;" title="Will It Run AI — fit result"></iframe>
Preview: