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Alibaba (Qwen) · language model

Qwen3 Coder 30B A3B Instruct: pricing, context and benchmarks

Qwen3 Coder 30B A3B Instruct is a language model from Alibaba (Qwen) released on July 31, 2025. It costs $0.07 per million input tokens and $0.28 per million output tokens, with a 262.1K-token context window. No independent score has been published for it so far.

Low costOpen weightsTool calling

What you need to know about Qwen3 Coder 30B A3B Instruct

Qwen3 Coder 30B A3B Instruct was released by Alibaba (Qwen) (China) on July 31, 2025. It accepts text as input and produces text. Its context window reaches 262,144 tokens, larger than 58 % of the models in the registry, and it can write up to 235,929 tokens in one go.

It has been available for about 15 months, long enough for its prices and scores to have settled.

Qwen3 Coder 30B A3B Instruct pricing

On OpenRouter, Qwen3 Coder 30B A3B Instruct costs $0.07 per million input tokens and $0.28 per million output tokens. Counting three tokens read for every token written, its average price is $0.123 per million, more expensive than 12 % of paid models (6.2 times cheaper than the median of $0.76).

A concrete example: a task that sends 2,000 tokens (about 1,500 words) and receives a 500-token answer costs $0.0003. At 1,000 tasks a day, budget $8 a month. The price calculator redoes this with your own volumes.

Performance and benchmarks

Epoch AI does not yet publish a capabilities index for Qwen3 Coder 30B A3B Instruct. We therefore show no made-up performance rating: only price, context and features count towards its score.

Features, privacy and local use

  • It supports tool calling, so it can drive an AI agent, call APIs or MCP servers.
  • It can answer in an enforced JSON format (structured outputs).
  • Its knowledge stops at June 2025.

Its weights are open and downloadable from Hugging Face (apache-2.0 licence): you can run it on your own machines without sending your data to a third party. With 30,532,122,624 billion parameters, it needs about 17,061,153,030 GB of memory at 4-bit quantisation. Check with the VRAM calculator. It was downloaded 699,963 times on Hugging Face last month.

Other Alibaba (Qwen) models

Average price per million tokens (3 input for 1 output).
ModelReleasedAvg. priceECI
Qwen3.8 Max PrimeSep 23, 2026$6—
Qwen3.8 Omni FlashSep 21, 2026$0.23—
Qwen3.8 Max (0902)Sep 3, 2026$3155.1
Qwen3.8 FlashAug 26, 2026$0.23—
Qwen3.8 27BAug 14, 2026$0.78151.7
Qwen3.8 2.4T A95BAug 12, 2026$3—
Qwen3.7 FlashJul 27, 2026$0.06144.1
Qwen3.7 PlusJun 3, 2026$0.56147

Verdict

Qwen3 Coder 30B A3B Instruct scores 78/100 on our grid, which only uses published figures.

Strengths

  • Low price: cheaper than 88 % of paid models.
  • Open weights: self-hostable, your data stays with you.
  • Agent-ready: tool calling and structured JSON output.

Limitations

  • No independent score published: performance cannot be verified.
  • Text only: reads neither images nor files.

Avoid if…

  • you want to host it on a single consumer computer (≈ 17,061,153,030 GB needed at 4-bit).

Frequently asked questions

How much does Qwen3 Coder 30B A3B Instruct cost?

$0.07 per million input tokens and $0.28 per million output tokens on OpenRouter (checked October 25, 2026). A task with 2,000 tokens read and 500 written costs $0.0003.

How big is Qwen3 Coder 30B A3B Instruct's context window?

262,144 tokens, roughly 197,000 words, with a maximum of 235,929 output tokens.

Can Qwen3 Coder 30B A3B Instruct run locally?

Yes, its weights are published under the apache-2.0 licence. Expect about 17,061,153,030 GB of memory at 4-bit.

Is Qwen3 Coder 30B A3B Instruct suitable for an AI agent?

Technically yes: it supports tool calling and structured outputs. Then check its cost for your volume.

What are the alternatives to Qwen3 Coder 30B A3B Instruct?

The closest models on price and performance are Nex-N2.5-Pro, Ling 3.1 Flash, and Seed 1.6 Flash.

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Neutrality. No affiliate links. No vendor pays to be reviewed, rated or ranked. Reviews are directed by François Chollet, neutral and factual, and every data point is dated and sourced. How we score