Qwen3-Coder 30B A3B Instruct needs ~35.4 GB VRAM. NVIDIA H200 141GB has 141.0 GB. With Q4_K_M quantization, expect ~610 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
609.7 tok/s
TTFT
350 ms
Safe context
256K
Memory
35.4 GB / 141.0 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 | S | Runs well | 609.7 tok/s | 350 ms | 256K |
| Coding | S | Runs well | 609.7 tok/s | 350 ms | 256K |
| Agentic Coding | S | Runs well | 609.7 tok/s | 462 ms | 256K |
| Reasoning | S | Runs well | 609.7 tok/s | 375 ms | 256K |
| RAG | S | Runs well | 609.7 tok/s | 577 ms | 256K |
How Qwen3-Coder 30B A3B Instruct (30.5B params) fits at each quantization level on NVIDIA H200 141GB (141.0 GB usable).
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 11.9 GB | Low | A81 |
Q3_K_S | 3 | 14.9 GB | Low | A81 |
NVFP4 | 4 |
Copy-paste commands to run Qwen3-Coder 30B A3B Instruct on your machine.
Run
ollama run qwen3-coderYour hardware
| Model | Params | Grade | Decode | Capabilities |
|---|---|---|---|---|
| 123B | S | 58.4 tok/s |
Yes, NVIDIA H200 141GB can run Qwen3-Coder 30B A3B Instruct with a S grade (Runs well). Expected decode speed: 609.7 tok/s.
Qwen3-Coder 30B A3B Instruct (30.5B parameters) requires approximately 35.4 GB of memory with Q4_K_M quantization.
The recommended quantization for Qwen3-Coder 30B A3B Instruct is Q4_K_M, which balances quality and memory efficiency.
On NVIDIA H200 141GB, Qwen3-Coder 30B A3B Instruct achieves approximately 609.7 tokens per second decode speed with a time-to-first-token of 350ms using Q4_K_M quantization.
For coding workloads, Qwen3-Coder 30B A3B Instruct on NVIDIA H200 141GB receives a S grade with 609.7 tok/s and 256K context.
On NVIDIA H200 141GB, Qwen3-Coder 30B A3B Instruct can safely use up to 256K tokens of context. The model's official context limit is 256K, 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/qwen-3-coder-30b-a3b-on-h200-141gb" width="400" height="180" frameborder="0" style="border:none;border-radius:12px;overflow:hidden;" title="Will It Run AI — fit result"></iframe>
Preview:
17.1 GB |
| Medium |
| A82 |
Q4_K_M | 4 | 18.6 GB | Medium | A82 |
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 | A83 |
F16Best for your GPU | 16 | 62.5 GB | Maximum | S88 |