Can Qwen3-Coder 30B A3B Instruct run on NVIDIA A800 80GB?

YES — Runs Great

S93Excellent
Estimated from fit model

Qwen3-Coder 30B A3B Instruct needs ~29.3 GB VRAM. NVIDIA A800 80GB has 80.0 GB. With Q4_K_M quantization, expect ~228 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) 29.3 GB, 228.2 tok/s, Runs well
29.3 GB required80.0 GB available
37% VRAM used

Fit status

Runs well

Decode

228.2 tok/s

TTFT

848 ms

Safe context

256K

Memory

29.3 GB / 80.0 GB

Memory breakdown

Weights18.6 GB
KV Cache1.5 GB
Runtime1.2 GB
Headroom8.0 GB

See how fast it feels

See how fast it feelsQwen3-Coder 30B A3B Instruct on NVIDIA A800 80GB
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: 228.2 tok/s decode · 848ms TTFT (warm) · 571 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 well228.2 tok/s463 ms256K
CodingSRuns well228.2 tok/s848 ms256K
Agentic CodingSRuns well228.2 tok/s1234 ms256K
ReasoningSRuns well228.2 tok/s1003 ms256K
RAGSRuns well228.2 tok/s1542 ms256K

Quantization options

How Qwen3-Coder 30B A3B Instruct (30.5B params) fits at each quantization level on NVIDIA A800 80GB (80.0 GB usable).

QuantBitsVRAMQualityFit
Q2_K
2
11.9 GB
LowA84
Q3_K_S
3
14.9 GB
LowA84
NVFP4
4
17.1 GB
MediumA84
Q4_K_M
4
18.6 GB
MediumA85
Q5_K_M
5
22.0 GB
HighS85
Q6_K
6
25.0 GB
HighS86
Q8_0
8
32.6 GB
Very HighS88
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 A800 80GB can run

ModelParamsGradeDecodeCapabilities
MistralDevstral 2 123B Instruct123BA15.5 tok/s

Frequently asked questions

Can NVIDIA A800 80GB run Qwen3-Coder 30B A3B Instruct?

Yes, NVIDIA A800 80GB can run Qwen3-Coder 30B A3B Instruct with a S grade (Runs well). Expected decode speed: 228.2 tok/s.

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

Qwen3-Coder 30B A3B Instruct (30.5B parameters) requires approximately 29.3 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 A800 80GB?

On NVIDIA A800 80GB, Qwen3-Coder 30B A3B Instruct achieves approximately 228.2 tokens per second decode speed with a time-to-first-token of 848ms using Q4_K_M quantization.

Can NVIDIA A800 80GB run Qwen3-Coder 30B A3B Instruct for coding?

For coding workloads, Qwen3-Coder 30B A3B Instruct on NVIDIA A800 80GB receives a S grade with 228.2 tok/s and 256K context.

What context window can Qwen3-Coder 30B A3B Instruct use on NVIDIA A800 80GB?

On NVIDIA A800 80GB, 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 A800 80GBSee all hardware for Qwen3-Coder 30B A3B Instruct
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