Qwen: Qwen3 30B A3B Instruct 2507
Analysis Summary
Qwen3 30B A3B Instruct 2507 is a compact text model offering a 262K context window, tool use, and function calling at exceptionally low pricing. It has useful mathematical and coding signals for its size, but the overall reasoning, instruction-following, long-context, and agentic results are limited. The model is better understood as an efficient task engine than a general problem solver.
It suits classification, extraction, SEO formatting, routine code assistance, and tightly specified tool workflows. It is not a strong choice for strategic analysis, complex autonomous agents, or high-stakes client copy, where weak long-context and agentic results can create rework. No vision capability is listed.
Its price makes it compelling for bulk traffic and fallback routing. Adopt it for constrained workloads with validation, while escalating ambiguous or reasoning-intensive requests to a stronger model.
Assessed August 9, 2026
Editorial notes
Qwen3 30B A3B Instruct 2507 is a very low-cost text model with 262K context, tool use, and function calling. Its limited reasoning and agentic results make it best for constrained, high-volume tasks.
Rankings consider pricing, capabilities, benchmarks, and real-world applicability and are refreshed as new models launch. Feedback?
DFO Verdict
Qwen3 30B A3B Instruct 2507 is a very low-cost text model with 262K context, tool use, and function calling. Its limited reasoning and agentic results make it best for constrained, high-volume tasks.
Benchmark scores
Magenta = intelligence · Ink = technical/agentic · Cyan = content & long-context · Grey = community benchmarks. Data: Artificial Analysis, Hugging Face.
9.1 Intelligence Index·8.1 Agentic Index·66.3 Math Index
How Qwen: Qwen3 30B A3B Instruct 2507 compares
Qwen: Qwen3 30B A3B Instruct 2507 ranks #289 of 430 AI models we track for overall intelligence, #125 of 185 for agentic tasks. Its 262K-token context window is larger than 72% of the models we list. At $0.05 per million input tokens it is cheaper than 76% of comparable models.
Dark bar = input · light bar = output, scaled to the priciest peer.
1M tokens ≈ 8 full-length novels or ~2,500 pages of business documents in a single request.
Strongest on value. The pulled-in technical corner is the trade-off, and if the shape matters more than the price, this is your model.
Compare shapes side-by-side →Pricing
| Token Type | Cost per 1M tokens | Cost per 1K tokens |
|---|---|---|
| Input | $0.05 | $0.000048 |
| Output | $0.19 | $0.000193 |
What would Qwen: Qwen3 30B A3B Instruct 2507 cost your business?
Pick the job that looks most like yours, then fine-tune with the sliders. Estimates update live.
A website chatbot handling around 100 customer conversations a day, a few short messages each.
Full calculator with 738 models → Price Calculator
These numbers get smaller with the right architecture.
We route routine calls to cheap models and save Qwen: Qwen3 30B A3B Instruct 2507 for the hard ones. Most clients cut their estimate by 60-80%.
Talk to our teamAbout Qwen: Qwen3 30B A3B Instruct 2507
Qwen3-30B-A3B-Instruct-2507 is a 30.5B-parameter mixture-of-experts language model from Qwen, with 3.3B active parameters per inference. It operates in non-thinking mode and is designed for high-quality instruction following, multilingual understanding, and..
Frequently asked questions about Qwen: Qwen3 30B A3B Instruct 2507
How much does Qwen: Qwen3 30B A3B Instruct 2507 cost?
Qwen: Qwen3 30B A3B Instruct 2507 costs $0.05 per million input tokens and $0.19 per million output tokens.
What is the context window of Qwen: Qwen3 30B A3B Instruct 2507?
Qwen: Qwen3 30B A3B Instruct 2507 has a context window of 262,144 tokens (262K).
What can Qwen: Qwen3 30B A3B Instruct 2507 do?
Qwen: Qwen3 30B A3B Instruct 2507 supports tool use and function calling.
Who created Qwen: Qwen3 30B A3B Instruct 2507?
Qwen: Qwen3 30B A3B Instruct 2507 is developed by Qwen and was released on July 29, 2025.