# Qwen 3 Coder 30B A3B Instruct

A deployment-friendly agentic coding model: 30 billion total parameters, 3 billion activated per forward pass, purpose-built for software engineering workflows that need strong code intelligence without the infrastructure demands of a full-scale model.

- **Model ID:** `alibaba/qwen3-coder-30b-a3b`
- **Type:** chat
- **Providers:** bedrock
- **Context window:** 262,144
- **Maximum output tokens:** 8,192
- **Pricing:** $0.15/1M input tokens, $0.6/1M output tokens
- **Canonical page:** https://vercel.com/ai-gateway/models/qwen3-coder-30b-a3b

## Supported parameters

Detailed capability metadata has not been reported for this model.

## Example

```ts
import { streamText } from 'ai'

const result = streamText({
  model: 'alibaba/qwen3-coder-30b-a3b',
  prompt: 'Why is the sky blue?'
})
```

## About

Qwen 3 Coder 30B A3B Instruct is the accessible tier of the Qwen3-Coder family. The "30B-A3B" naming convention is explicit: 30 billion total parameters in the MoE architecture, with 3 billion activated during inference. That 10:1 ratio between stored and active capacity is the model's defining characteristic: broad capacity at 30B scale combined with 3B-equivalent serving costs.

Like its larger sibling, Qwen 3 Coder 30B A3B Instruct was developed within the Qwen3-Coder framework, carrying the same coding-first orientation: deep familiarity with programming languages, patterns, and developer workflows, paired with tuning for real-world coding tasks rather than just benchmark patterns.

The 3B active parameter count translates to meaningfully faster inference than dense models of comparable quality, which matters for interactive development tools where the model is invoked frequently.

Agentic capabilities (multi-turn tool use, plan-execute-debug iteration, and environment interaction) are present in this variant given its origin in the Qwen3-Coder lineage. Teams building coding assistants, automated review pipelines, or developer-facing products can use Qwen 3 Coder 30B A3B Instruct as a cost-effective foundation without sacrificing the core agentic orientation that distinguishes the Qwen3-Coder family from general-purpose models.

## What to consider

The 30B total / 3B active parameter structure keeps serving costs tractable, worth factoring in when you're comparing tiers within the Qwen3-Coder family.

## When to use

### Best For

- **Cost-sensitive agentic coding deployments:** When you need a model that understands code at a meaningful depth and can handle multi-step workflows, but the per-token cost of the 480B-A35B variant isn't justified by your use case or volume, the 30B-A3B offers a practical alternative
- **Interactive coding tools with latency requirements:** The 3B active parameter count yields faster token generation than larger dense or MoE models. For coding assistants embedded in editors or IDEs where response time affects user experience, this matters
- **High-frequency automated code tasks:** CI/CD pipelines, automated PR description generation, code review summarization, and similar high-volume tasks are served well by a capable but economical model

### Consider Alternatives When

- **The task requires the highest coding capability:** For the most complex repository-level engineering problems, multi-file refactors with subtle dependencies, or tasks where getting it right the first time is critical, the larger Qwen3-Coder variant offers a higher performance ceiling
- **General knowledge and reasoning matter as much as code:** This model is optimized for coding scenarios. Tasks that blend heavy general-domain reasoning with code may perform better on a general-purpose Qwen3 model of equivalent or larger size
- **Extremely long context is required:** Verify the context window (262.1K tokens) against your specific use case, particularly for agentic tasks that accumulate long tool-call histories

## Best for

- **Cost-sensitive agentic coding deployments:** When you need a model that understands code at a meaningful depth and can handle multi-step workflows, but the per-token cost of the 480B-A35B variant isn't justified by your use case or volume, the 30B-A3B offers a practical alternative
- **Interactive coding tools with latency requirements:** The 3B active parameter count yields faster token generation than larger dense or MoE models. For coding assistants embedded in editors or IDEs where response time affects user experience, this matters
- **High-frequency automated code tasks:** CI/CD pipelines, automated PR description generation, code review summarization, and similar high-volume tasks are served well by a capable but economical model

## Consider alternatives

- **The task requires the highest coding capability:** For the most complex repository-level engineering problems, multi-file refactors with subtle dependencies, or tasks where getting it right the first time is critical, the larger Qwen3-Coder variant offers a higher performance ceiling
- **General knowledge and reasoning matter as much as code:** This model is optimized for coding scenarios. Tasks that blend heavy general-domain reasoning with code may perform better on a general-purpose Qwen3 model of equivalent or larger size
- **Extremely long context is required:** Verify the context window (262.1K tokens) against your specific use case, particularly for agentic tasks that accumulate long tool-call histories

## Frequently asked questions

### What is the relationship between Qwen 3 Coder 30B A3B Instruct and the 480B-A35B variant?

Both belong to the Qwen3-Coder family and share the same coding-first orientation. The 30B-A3B activates 3B parameters per inference versus 35B for the 480B-A35B model. The tradeoff is lower peak capability in exchange for lower serving cost and latency.

### What does the "A3B" suffix indicate?

"A3B" stands for 3 billion activated parameters. In the mixture-of-experts architecture, each inference step routes through a subset of the total parameter space. The model stores 30 billion parameters but computes with only 3 billion per forward pass.

### How is Qwen 3 Coder 30B A3B Instruct different from the general Qwen3-30B-A3B?

Qwen 3 Coder 30B A3B Instruct is specifically from the coding-specialized line in the Qwen3-Coder family. The general Qwen3-30B-A3B targets broader task coverage. The coder variant will generally outperform the general variant on coding-specific evaluations.

### What programming languages and frameworks does Qwen 3 Coder 30B A3B Instruct cover?

The model covers common programming languages and developer tooling. Specific language coverage details are in the Qwen3-Coder technical documentation at https://docs.aws.amazon.com/bedrock/latest/userguide/models-supported.html.

### Can I use Qwen 3 Coder 30B A3B Instruct for multi-file codebases and agentic sessions?

Yes. Qwen 3 Coder 30B A3B Instruct inherits the agentic coding orientation of the Qwen3-Coder family, including tool-calling support and the ability to operate in plan-execute-debug loops. The context window (262.1K tokens) determines how much code and conversation history fits in a single session.

### How does the MoE architecture affect throughput compared to a dense model?

With 3B active parameters, the per-token compute cost is equivalent to a 3B dense model, which is substantially faster than a dense 30B model serving the same traffic. For throughput-sensitive applications, this translates to more requests served per unit of compute.

### Is Qwen 3 Coder 30B A3B Instruct open source?

The Qwen3-Coder family is released as open models. Check https://docs.aws.amazon.com/bedrock/latest/userguide/models-supported.html for licensing terms and model cards.

## Links

- [Model page](https://vercel.com/ai-gateway/models/qwen3-coder-30b-a3b)
- [AI Gateway documentation](https://vercel.com/docs/ai-gateway)
- [Provider model documentation](https://docs.aws.amazon.com/bedrock/latest/userguide/models-supported.html)
- [Provider pricing](https://aws.amazon.com/bedrock/pricing/)