Can NVIDIA DGX Spark (GB10) · 64 GB run Qwen3 30B-A3B Instruct 2507?
64 GB unified · 273 GB/s memory bandwidth · Qwen3 30B-A3B Instruct 2507 has 30.5B parameters (3.3B active per token).
Short answer
Yes, excellent for chat and acceptable or better for every workload we test.
Best quantization for chat: Q6_K (24 GB of weights) on Ollama. Generation: 50–65 tok/s, leaving about 32 GB free for your other apps.
How it rates for each workload
Same model and machine, different jobs. Agents and long documents send far bigger prompts than chat, so they need much more speed and memory.
| Workload | Verdict | Quant | Generation | First reply | Context | |
|---|---|---|---|---|---|---|
| Chatwith Open WebUI | Excellent | Q6_K | 50–65 tok/s | under 1 s | 8K | Details |
| Coding questionswith Continue | Excellent | Q6_K | 45–60 tok/s | ≈2 s | 16K | Details |
| Coding in a repositorywith Aider | Comfortable | Q8_0 | 30–40 tok/s | ≈6 s | 32K | Details |
| Agentic codingwith OpenCode | Acceptable | Q6_K | 30–40 tok/s | ≈8 s | 32K | Details |
| Long documents (64K)with Open WebUI | Excellent | Q6_K | 19–25 tok/s | ≈30 s | 64K | Details |
Speeds are estimates calibrated against measured benchmarks on similar hardware. “First reply” is the time to read the workload’s opening prompt. How we calculate
Get it running
Copy-paste commands for the Q6_K build with a 64K context. Ollama and llama.cpp download the file straight from Hugging Face.
ollama run hf.co/unsloth/Qwen3-30B-A3B-Instruct-2507-GGUF:Q6_K
Downloads 25.09 GB (Q6_K). Ollama's default context is small: set OLLAMA_CONTEXT_LENGTH=65536 before `ollama serve` for long prompts.
Other models for NVIDIA DGX Spark (GB10) · 64 GB
The best-rated models for chat on this machine.
- Qwen3.6 35B-A3B60–80 tok/sExcellent
- Qwen3-Next 80B-A3B Instruct80–110 tok/sExcellent
- Gemma 4 26B-A4B45–60 tok/sExcellent
- Qwen3.5 35B-A3B60–80 tok/sExcellent
- LFM2.5 24B-A2B120–160 tok/sExcellent
- gpt-oss-20b≈75 tok/sExcellent
Cheapest machines for Qwen3 30B-A3B Instruct 2507
Hardware rated comfortable or better for chat, lowest price first.
- Laptop · Ryzen AI 9 HX 370 (Radeon 890M) · 32 GB$1,300 · 20–35 tok/sComfortable
- Laptop · Core Ultra 7 258V (Arc 140V) · 32 GB$1,300 · 17–30 tok/sComfortable
- Mac mini M4 32 GB$1,399 · 25–35 tok/sExcellent
- Desktop PC · Ryzen 9 9950X (no GPU) · 64 GB DDR5$1,400 · 11–18 tok/sComfortable
- Desktop PC · Intel Arc Pro B60 24GB · 32 GB RAM$1,500 · 60–95 tok/sExcellent
- Ryzen AI Max+ 395 mini PC / Framework Desktop · 64 GB$1,600 · 50–65 tok/sExcellent
Same chip, other memory: 128 GB
Different tool, context size or workload?
These pages use typical settings. The full check models your exact setup.