DeepSeek R1 Distill Qwen 14B needs ~24.4 GB VRAM. NVIDIA DGX Spark 128GB has 108.8 GB. With Q4_K_M quantization, expect ~19 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
19.2 tok/s
TTFT
10094 ms
Safe context
839K
Memory
24.4 GB / 108.8 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 | C | Runs well | 19.2 tok/s | 5506 ms | 839K |
| Coding | C | Runs well | 19.2 tok/s | 10094 ms | 839K |
| Agentic Coding | C | Runs well | 19.2 tok/s | 14682 ms | 839K |
| Reasoning | C | Runs well | 19.2 tok/s | 11929 ms | 839K |
| RAG | C | Runs well | 19.2 tok/s | 18352 ms | 839K |
How DeepSeek R1 Distill Qwen 14B (14B params) fits at each quantization level on NVIDIA DGX Spark 128GB (92.2 GB usable).
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 5.5 GB | Low | D39 |
Q3_K_S | 3 | 6.9 GB | Low | D39 |
NVFP4 | 4 | 7.8 GB | Medium | D40 |
Q4_K_M | 4 | 8.5 GB | Medium | D40 |
Q5_K_M | 5 | 10.1 GB | High | D40 |
Q6_K | 6 | 11.5 GB | High | D40 |
Q8_0 | 8 | 15.0 GB | Very High | C40 |
F16Best for your GPU | 16 | 28.7 GB | Maximum | C42 |
Copy-paste commands to run DeepSeek R1 Distill Qwen 14B on your machine.
Run
lms load hf-unsloth--deepseek-r1-distill-qwen-14b-gguf && lms server startUpgrade-Optionen
NVIDIA H200 141GBGünstige WahlRaises estimated decode speed by about 921%.
Adds memory headroom for longer context windows and future model growth.
ca. $30,000 MSRP
NVIDIA H200 PCIe 141GBBestes Preis-Leistungs-VerhältnisRaises estimated decode speed by about 921%.
Adds memory headroom for longer context windows and future model growth.
ca. $30,000 MSRP
NVIDIA B200 180GBNVIDIA-UpgradeRaises estimated decode speed by about 921%.
Adds memory headroom for longer context windows and future model growth.
ca. $30,000 MSRP
Yes, NVIDIA DGX Spark 128GB can run DeepSeek R1 Distill Qwen 14B with a C grade (Runs well). Expected decode speed: 19.2 tok/s.
DeepSeek R1 Distill Qwen 14B (14B parameters) requires approximately 24.4 GB of memory with Q4_K_M quantization.
The recommended quantization for DeepSeek R1 Distill Qwen 14B is Q4_K_M, which balances quality and memory efficiency.
On NVIDIA DGX Spark 128GB, DeepSeek R1 Distill Qwen 14B achieves approximately 19.2 tokens per second decode speed with a time-to-first-token of 10094ms using Q4_K_M quantization.
For coding workloads, DeepSeek R1 Distill Qwen 14B on NVIDIA DGX Spark 128GB receives a C grade with 19.2 tok/s and 839K context.
On NVIDIA DGX Spark 128GB, DeepSeek R1 Distill Qwen 14B can safely use up to 839K tokens of context. The model's official context limit is —, but available memory constrains the safe maximum.
Not always. NVIDIA DGX Spark 128GB 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.
Paste this snippet into any page to show a live fit card.
<iframe src="https://willitrunai.com/embed/hf-unsloth--deepseek-r1-distill-qwen-14b-gguf-on-dgx-spark-128gb" width="400" height="180" frameborder="0" style="border:none;border-radius:12px;overflow:hidden;" title="Will It Run AI — fit result"></iframe>
Preview: