# Qwen3-Coder VRAM: Check the Exact Model Variant

Read Qwen3-Coder VRAM requirements from the exact model variant, total MoE weights, supported runtime and a narrow code-quality test.

Author: Retrivium team
Updated: 2026-11-01
Canonical URL: https://retrivium.ai/journal/qwen3-coder-vram-requirements/
Language: en

For Qwen3-Coder VRAM planning, name the exact model first. The word Coder and a mixture-of-experts active parameter count do not define the memory needed to store and run the artifact. Format, context and engine remain part of the configuration.

Useful capacity is established by a correct coding result, not simply by reaching model startup.

## Use the complete model name

Qwen3-Coder-30B-A3B-Instruct is a specific official candidate. Do not mix its requirements with other sizes or revisions under a shortened family label. Preserve the original artifact reference and any conversion provenance.

vLLM's supported-model list can help check architecture support in the relevant version. Also record the selected format and loading method; a supported architecture does not automatically validate every derivative file.

## Separate total and active parameters

In a mixture-of-experts model, parameters active for one token and the complete stored set are different quantities. The active count helps describe computation; it does not mean the remaining expert weights disappear from the resource budget.

| Planning item | Required information |
| --- | --- |
| Storage estimate | Complete model composition |
| Execution estimate | Architecture and chosen runtime |
| Weight representation | Actual artifact format |
| Request memory | Input, output and active sessions |
| Useful outcome | Coding checks that must pass |

Do not calculate VRAM only from A3B. If a smaller artifact is considered, record it as a different candidate rather than an interchangeable mode of the original.

## Prepare a narrow coding set

Choose a function repair, a small interface change and a patch-format response. Keep the expected behaviour and tests. Check invented APIs, unrequested edits and changes to the function contract.

Use isolated examples without production credentials. A plausible explanation or syntactically valid patch is not enough when the required tests fail. Preserve failure cases for comparison between formats.

## Measure the actual working input

Begin with a short file, then add only the dependencies and requirements needed for the task. Record token lengths, memory and time at each step. Extend output separately before introducing concurrent sessions.

For distributed execution, preserve device count, connections and allocation per GPU. A combined VRAM total is not evidence of supported model partitioning. Also test a normal restart and retain the complete environment record.

The next check might involve another artifact or execution arrangement. A model list does not guarantee hardware demand, utilisation or a ready sales channel.

Continue with [Coding LLMs on 12GB VRAM: Budget Context and Headroom](/journal/coding-llm-12gb-vram/) and [gpt-oss-120b VRAM: Total MoE Weights and Active Parameters](/journal/gpt-oss-120b-vram-setup/).

## Official references

- [Official model documentation — Qwen3 Coder 30B A3B Instruct](https://huggingface.co/Qwen/Qwen3-Coder-30B-A3B-Instruct)
- [vLLM — supported models](https://docs.vllm.ai/en/stable/models/supported_models/)