LLM Reference

Qwen3-30B-A3B

Released
2025-04-28
Last refreshed
2026-06-30
Status
Researched 112d ago
Open sourceCommercial use: permittedRAGLong contextClassificationJSON / Tool use

Qwen3-30B-A3B is worth evaluating for rag, long context, and classification when its provider route and context window match the workload.

Use it for

  • Teams evaluating rag, long context, and classification
  • Workloads that can use a 128k context window
  • Buyers comparing 4 tracked provider routes

Do not use it for

  • Vision or document-understanding workloads
Specifications
Family
Qwen3
Released
2025-04-28
Context
128k
Parameters
30B
Architecture
Mixture of Experts
Specialization
general
Openness
Open source
License
Apache 2.0OSI-approvedCommercial use: permitted
Weights
Unknown
Code
Unknown
Training
Pretrained
Created by

AI research institute of Alibaba Group.

Hangzhou, Zhejiang, China
Founded 2017
Website
Pricing
Output / 1M
$0.280
Input / 1M
$0.080

Cheapest of 7 routes · OpenRouter

About

Alibaba's Qwen3-30B with 3B active parameters via mixture-of-experts architecture. Delivers strong performance with efficient inference on Cloudflare Workers AI platform.

Top use-case fit

RAG

Included by capability and metadata signals in the decision map.

Long context

Included by capability and metadata signals in the decision map.

Classification

Included by capability and metadata signals in the decision map.

Capabilities

Structured Outputs

Benchmark peer barsfor RAG

No task-mapped benchmark peers are available for this model yet.

Benchmark scores(1)

Scores are benchmark-specific and are direction-aware: the same numeric gap can mean very different outcomes across suites. Use the leaderboard context and this model's provider route to decide whether the winning margin is meaningful for your workload.
BenchmarkScoreVersionEvaluationSource
Google-Proof Q&A61.6diamondObserved 2026-04-18—Source

Migration checks

No linked migration route is available for this model yet.

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