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Alibaba Qwen · Qwen
No. 30
Qwen3-30B-A3B-Instruct-2507
Small, fast open-weight MoE with big-model manners.
Field notes
- Context window
- 262Ktokens
- Max output
- 33Ktokens
- Input price
- $0.05/ 1M tokens
- Output price
- $0.19/ 1M tokens
- Cached input
- $0.05/ 1M tokens
- Modalities
- Text
- Knowledge cutoff
- Apr 2025
- Released
- Jul 2025
- Parameters
- 30B
- License
- Apache-2.0
- Approx. speed
- —
Overview
What this model is
Qwen3-30B-A3B-Instruct-2507 is a compact open-weight MoE (30B total, 3B active) tuned for fast, efficient instruction following. It is remarkably capable for its size, runs cheaply, and is easy to self-host under Apache-2.0. It is not built for complex long-horizon agentic or coding work, where its limits show quickly.
Strengths
- Very fast and cheap thanks to 3B active params
- Great capability per active parameter
- Runs on consumer-grade GPUs
- Apache-2.0 open weights
Trade-offs
- Limited depth on hard reasoning
- Not suited to complex coding
- Text-only, no vision
- Struggles with long agentic chains
Best for
- On-device and edge deployment
- High-volume simple tasks
- Routing, classification, and lightweight assistants
- Cost-optimized chat backends
Not ideal for
- Complex agentic coding
- Hard multi-step reasoning
Capabilities
Capability profile
Normalized 0–100 scores, comparable across the whole catalog.
- Reasoning
- 66
- Coding
- 60
- Math
- 68
- Writing
- 70
- Knowledge
- 72
- Speed
- 90
- Agentic
- 58
- Vision
- 5
- Multilingual
- 82
- Long Context
- 74
Benchmarks
How it scores
Public benchmark results, with independent third-party results where available. Bars normalize percentages to 100 and Elo ratings to a 1500 ceiling.
BenchmarkResult
MMLU-Pro
KnowledgeVendor-reported
78.4%
GPQA Diamondindependent
ReasoningIndependent aggregators
70.4%
AIME 2025
MathVendor-reported
61.3%
LiveCodeBenchindependent
CodingLiveCodeBench
43.2%
LiveBenchindependent
GeneralLiveBench
74.3%