MacBook Pro M4 Max 96GBBudget pick
96 GB Unified (+32)
C
This setup is broadly balanced for this model.76.8 tok/s decode
~$2,499 MSRP
DeepSeek R1 0528 Qwen3 8B needs ~13.4 GB VRAM. NVIDIA A16 64GB has 64.0 GB. With Q4_K_M quantization, expect ~96 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
95.9 tok/s
TTFT
2019 ms
Safe context
879K
Memory
13.4 GB / 64.0 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 | C | Runs well | 95.9 tok/s | 1101 ms | 879K |
| Coding | C | Runs well | 95.9 tok/s | 2019 ms | 879K |
| Agentic Coding | C | Runs well | 95.9 tok/s | 2936 ms | 879K |
| Reasoning | C | Runs well | 95.9 tok/s | 2386 ms | 879K |
| RAG | C | Runs well | 95.9 tok/s | 3670 ms | 879K |
How DeepSeek R1 0528 Qwen3 8B (8B params) fits at each quantization level on NVIDIA A16 64GB (64.0 GB usable).
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 3.1 GB | Low | C40 |
Q3_K_S | 3 | 3.9 GB | Low | C40 |
NVFP4 | 4 | 4.5 GB | Medium | C41 |
Q4_K_M | 4 | 4.9 GB | Medium | C41 |
Q5_K_M | 5 | 5.8 GB | High | C41 |
Q6_K | 6 | 6.6 GB | High | C41 |
Q8_0 | 8 | 8.6 GB | Very High | C41 |
F16Best for your GPU | 16 | 16.4 GB | Maximum | C43 |
Copy-paste commands to run DeepSeek R1 0528 Qwen3 8B on your machine.
Run
lms load hf-maziyarpanahi--deepseek-r1-0528-qwen3-8b-gguf && lms server startUpgrade options
Yes, NVIDIA A16 64GB can run DeepSeek R1 0528 Qwen3 8B with a C grade (Runs well). Expected decode speed: 95.9 tok/s.
DeepSeek R1 0528 Qwen3 8B (8B parameters) requires approximately 13.4 GB of memory with Q4_K_M quantization.
The recommended quantization for DeepSeek R1 0528 Qwen3 8B is Q4_K_M, which balances quality and memory efficiency.
On NVIDIA A16 64GB, DeepSeek R1 0528 Qwen3 8B achieves approximately 95.9 tokens per second decode speed with a time-to-first-token of 2019ms using Q4_K_M quantization.
For coding workloads, DeepSeek R1 0528 Qwen3 8B on NVIDIA A16 64GB receives a C grade with 95.9 tok/s and 879K context.
On NVIDIA A16 64GB, DeepSeek R1 0528 Qwen3 8B can safely use up to 879K tokens of context. The model's official context limit is —, 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/hf-maziyarpanahi--deepseek-r1-0528-qwen3-8b-gguf-on-a16-64gb" width="400" height="180" frameborder="0" style="border:none;border-radius:12px;overflow:hidden;" title="Will It Run AI — fit result"></iframe>
Preview: