Can Qwen3-Coder 30B A3B Instruct run on NVIDIA GH200 96GB?

YES — Runs Great

S92Excellent
Estimated from fit model

Qwen3-Coder 30B A3B Instruct needs ~30.9 GB VRAM. NVIDIA GH200 96GB has 96.0 GB. With Q4_K_M quantization, expect ~490 tok/s.

Runtime: OllamaCapacity: RoomyBandwidth: HighStack: BasicBottleneck: Balanced
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Operating mode

Choose the run profile you care about

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.

Capabilities:

Select quantization to explore

Q4_K_M (Medium quality) 30.9 GB, 489.9 tok/s, Runs well
30.9 GB required96.0 GB available
32% VRAM used

Fit status

Runs well

Decode

489.9 tok/s

TTFT

395 ms

Safe context

256K

Memory

30.9 GB / 96.0 GB

Memory breakdown

Weights18.6 GB
KV Cache1.5 GB
Runtime1.2 GB
Headroom9.6 GB

See how fast it feels

See how fast it feelsQwen3-Coder 30B A3B Instruct on NVIDIA GH200 96GB
1st promptCold start — includes initialization
>Write a Python function to sort a list
Here's a Python function that sorts a list using quicksort: def quicksort(arr): if len(arr) <= 1: return arr pivot = arr[len(arr) // 2] left = [x for x in arr if x < pivot] middle = [x for x in arr if x == pivot] right = [x for x in arr if x > pivot] return quicksort(left) + middle + quicksort(right) # Example usage numbers = [3, 6, 8, 10, 1, 2, 1] print(quicksort(numbers)) # [1, 1, 2, 3, 6, 8, 10] The algorithm picks a pivot, partitions the list into smaller, equal, and larger elements, then recursively sorts each partition and concatenates the results.
2nd promptWarm — model ready, no init overhead
>Now add type hints and a docstring
def quicksort(arr: list[int]) -> list[int]: """Sort a list using the quicksort algorithm. Args: arr: List of integers to sort. Returns: A new sorted list. """ if len(arr) <= 1: return arr pivot = arr[len(arr) // 2] left = [x for x in arr if x < pivot] middle = [x for x in arr if x == pivot] right = [x for x in arr if x > pivot] return quicksort(left) + middle + quicksort(right) Added type hints for the input and return type, plus a Google-style docstring.
Estimated: 489.9 tok/s decode · 395ms TTFT (warm) · 1225 tok/s prefill

What limits this setup

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.

Best improvement path

Performance by workload

WorkloadGradeFitDecodeTTFTContext
ChatSRuns well489.9 tok/s350 ms256K
CodingSRuns well489.9 tok/s395 ms256K
Agentic CodingSRuns well489.9 tok/s575 ms256K
ReasoningSRuns well489.9 tok/s467 ms256K
RAGSRuns well489.9 tok/s718 ms256K

Quantization options

How Qwen3-Coder 30B A3B Instruct (30.5B params) fits at each quantization level on NVIDIA GH200 96GB (96.0 GB usable).

QuantBitsVRAMQualityFit
Q2_K
2
11.9 GB
LowA83
Q3_K_S
3
14.9 GB
LowA83
NVFP4
4
17.1 GB
MediumA83
Q4_K_M
4
18.6 GB
MediumA84
Q5_K_M
5
22.0 GB
HighA84
Q6_K
6
25.0 GB
HighA84
Q8_0
8
32.6 GB
Very HighS86
F16Best for your GPU
16
62.5 GB
MaximumS91

Get started

Copy-paste commands to run Qwen3-Coder 30B A3B Instruct on your machine.

Run

ollama run qwen3-coder

Your hardware

More models your NVIDIA GH200 96GB can run

ModelParamsGradeDecodeCapabilities
MistralDevstral 2 123B Instruct123BS47 tok/s

Frequently asked questions

Can NVIDIA GH200 96GB run Qwen3-Coder 30B A3B Instruct?

Yes, NVIDIA GH200 96GB can run Qwen3-Coder 30B A3B Instruct with a S grade (Runs well). Expected decode speed: 489.9 tok/s.

How much VRAM does Qwen3-Coder 30B A3B Instruct need?

Qwen3-Coder 30B A3B Instruct (30.5B parameters) requires approximately 30.9 GB of memory with Q4_K_M quantization.

What is the best quantization for Qwen3-Coder 30B A3B Instruct?

The recommended quantization for Qwen3-Coder 30B A3B Instruct is Q4_K_M, which balances quality and memory efficiency.

What speed will Qwen3-Coder 30B A3B Instruct run at on NVIDIA GH200 96GB?

On NVIDIA GH200 96GB, Qwen3-Coder 30B A3B Instruct achieves approximately 489.9 tokens per second decode speed with a time-to-first-token of 395ms using Q4_K_M quantization.

Can NVIDIA GH200 96GB run Qwen3-Coder 30B A3B Instruct for coding?

For coding workloads, Qwen3-Coder 30B A3B Instruct on NVIDIA GH200 96GB receives a S grade with 489.9 tok/s and 256K context.

What context window can Qwen3-Coder 30B A3B Instruct use on NVIDIA GH200 96GB?

On NVIDIA GH200 96GB, 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.

See all results for NVIDIA GH200 96GBSee all hardware for Qwen3-Coder 30B A3B Instruct
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