Adds memory headroom for longer context windows and future model growth.
~$3,999 MSRP
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DeepSeek R1 0528 Qwen3 8B needs ~11.8 GB VRAM. NVIDIA A40 48GB has 48.0 GB. With Q4_K_M quantization, expect ~111 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
111.2 tok/s
TTFT
1740 ms
Safe context
634K
Memory
11.8 GB / 48.0 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 | 111.2 tok/s | 949 ms | 634K |
| Coding | C | Runs well | 111.2 tok/s | 1740 ms | 634K |
| Agentic Coding | C | Runs well | 111.2 tok/s | 2531 ms | 634K |
| Reasoning | C | Runs well | 111.2 tok/s | 2057 ms | 634K |
| RAG | C | Runs well | 111.2 tok/s | 3164 ms | 634K |
How DeepSeek R1 0528 Qwen3 8B (8B params) fits at each quantization level on NVIDIA A40 48GB (48.0 GB usable).
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 3.1 GB | Low | C42 |
Q3_K_S | 3 | 3.9 GB | Low | C42 |
NVFP4 | 4 | 4.5 GB | Medium | C42 |
Q4_K_M | 4 | 4.9 GB | Medium | C42 |
Q5_K_M | 5 | 5.8 GB | High | C42 |
Q6_K | 6 | 6.6 GB | High | C42 |
Q8_0 | 8 | 8.6 GB | Very High | C43 |
F16Best for your GPU | 16 | 16.4 GB | Maximum | C45 |
Copy-paste commands to run DeepSeek R1 0528 Qwen3 8B on your machine.
Run
lms load hf-lmstudio-community--deepseek-r1-0528-qwen3-8b-gguf && lms server startUpgrade options