Qwen 3 30B A3B needs ~78.2 GB VRAM. NVIDIA DGX Spark 128GB has 0 MB. With F16 quantization, expect ~10 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
24.8 tok/s
TTFT
7816 ms
Safe context
131K
Memory
34.3 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 | F | Too heavy | 4.1 tok/s | 25759 ms | 4K |
| Coding | F | Too heavy | 4.1 tok/s | 47224 ms | 4K |
| Agentic Coding | F | Too heavy | 4.1 tok/s | 68689 ms | 4K |
| Reasoning | F | Too heavy | 4.1 tok/s | 55810 ms | 4K |
| RAG | F | Too heavy | 4.1 tok/s | 85862 ms | 4K |
How Qwen 3 30B A3B (30.5B params) fits at each quantization level on NVIDIA DGX Spark 128GB (92.2 GB usable).
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 11.9 GB | Low | A80 |
Q3_K_S | 3 | 14.9 GB | Low | A81 |
NVFP4 | 4 | 17.1 GB | Medium | A81 |
Q4_K_M | 4 | 18.6 GB | Medium | A81 |
Q5_K_M | 5 | 22.0 GB | High | A82 |
Q6_K | 6 | 25.0 GB | High | A82 |
Q8_0 | 8 | 32.6 GB | Very High | A84 |
F16Best for your GPU | 16 | 62.5 GB | Maximum | S88 |
Copy-paste commands to run Qwen 3 30B A3B on your machine.
Run
ollama run qwen3:30b-a3b升级选项
NVIDIA H200 141GB经济之选Raises estimated decode speed by about 2358%.
Adds memory headroom for longer context windows and future model growth.
~$30,000 MSRP
NVIDIA H200 PCIe 141GB最佳性价比Raises estimated decode speed by about 2358%.
Adds memory headroom for longer context windows and future model growth.
~$30,000 MSRP
NVIDIA B200 180GBNVIDIA 升级Raises estimated decode speed by about 3997%.
Adds memory headroom for longer context windows and future model growth.
~$30,000 MSRP
Yes, NVIDIA DGX Spark 128GB can run Qwen 3 30B A3B at F16 quantization (Runs well). The recommended Q4_K_M requires 21.3 GB which exceeds available memory, but at F16 it needs only 78.2 GB. Expected decode speed: 10.3 tok/s.
Qwen 3 30B A3B (30.5B parameters) requires approximately 21.3 GB at Q4_K_M quantization. On NVIDIA DGX Spark 128GB, it fits at F16 using 78.2 GB.
The recommended quantization is Q4_K_M, but on NVIDIA DGX Spark 128GB the best fitting quantization is F16, which uses 78.2 GB.
On NVIDIA DGX Spark 128GB, Qwen 3 30B A3B achieves approximately 10.3 tokens per second decode speed with a time-to-first-token of 18763ms using F16 quantization.
For coding workloads, Qwen 3 30B A3B on NVIDIA DGX Spark 128GB receives a F grade with 4.1 tok/s and 4K context.
On NVIDIA DGX Spark 128GB, Qwen 3 30B A3B can safely use up to 131K tokens of context at F16 quantization. The model's official context limit is 131K, 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/qwen-3-30b-a3b-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>
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