DeepSeek R1 Distill Llama 8B needs ~9.4 GB VRAM. RTX A5000 24GB has 24.0 GB. With Q4_K_M quantization, expect ~110 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
110.2 tok/s
TTFT
1757 ms
Safe context
265K
Memory
9.4 GB / 24.0 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 | 110.2 tok/s | 959 ms | 265K |
| Coding | C | Runs well | 110.2 tok/s | 1757 ms | 265K |
| Agentic Coding | C | Runs well | 110.2 tok/s | 2556 ms | 265K |
| Reasoning | C | Runs well | 110.2 tok/s | 2077 ms | 265K |
| RAG | C | Runs well | 110.2 tok/s | 3195 ms | 265K |
How DeepSeek R1 Distill Llama 8B (8B params) fits at each quantization level on RTX A5000 24GB (24.0 GB usable).
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 3.1 GB | Low | C45 |
Q3_K_S | 3 | 3.9 GB | Low | C45 |
NVFP4 | 4 | 4.5 GB | Medium | C45 |
Q4_K_M | 4 | 4.9 GB | Medium | C46 |
Q5_K_M | 5 | 5.8 GB | High | C46 |
Q6_K | 6 | 6.6 GB | High | C47 |
Q8_0 | 8 | 8.6 GB | Very High | C48 |
F16Best for your GPU | 16 | 16.4 GB | Maximum | C50 |
Copy-paste commands to run DeepSeek R1 Distill Llama 8B on your machine.
Run
lms load hf-unsloth--deepseek-r1-distill-llama-8b-gguf && lms server startYes, RTX A5000 24GB can run DeepSeek R1 Distill Llama 8B with a C grade (Runs well). Expected decode speed: 110.2 tok/s.
DeepSeek R1 Distill Llama 8B (8B parameters) requires approximately 9.4 GB of memory with Q4_K_M quantization.
The recommended quantization for DeepSeek R1 Distill Llama 8B is Q4_K_M, which balances quality and memory efficiency.
On RTX A5000 24GB, DeepSeek R1 Distill Llama 8B achieves approximately 110.2 tokens per second decode speed with a time-to-first-token of 1757ms using Q4_K_M quantization.
For coding workloads, DeepSeek R1 Distill Llama 8B on RTX A5000 24GB receives a C grade with 110.2 tok/s and 265K context.
On RTX A5000 24GB, DeepSeek R1 Distill Llama 8B can safely use up to 265K 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-unsloth--deepseek-r1-distill-llama-8b-gguf-on-a5000-24gb" width="400" height="180" frameborder="0" style="border:none;border-radius:12px;overflow:hidden;" title="Will It Run AI — fit result"></iframe>
Preview: