Qwen: Qwen3 30B A3B Instruct 2507
Analysis Summary
Qwen3 30B A3B Instruct 2507 is a compact Qwen model with a 262K context window, tool use, and function calling. The supplied results show useful mathematical capability and moderate instruction, coding, and long-context performance, making it appropriate for structured generation, extraction, SEO operations, and routine technical assistance.
Pricing is especially low at 0.0482 per million input tokens and 0.1931 per million output tokens. That supports high-volume workflows where occasional review is acceptable, such as metadata generation, content briefs, classification, and internal knowledge processing. Its lower reasoning and agentic results make it a poor choice for autonomous, high-stakes decisions or complex code changes. Use it as a budget workhorse with validation around factual and tool-driven outputs.
Assessed September 7, 2026
Editorial notes
Qwen3 30B A3B Instruct 2507 is an inexpensive, tool-enabled model with 262K context and useful instruction and math results, but its broader reasoning and agent reliability remain limited.
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 an inexpensive, tool-enabled model with 262K context and useful instruction and math results, but its broader reasoning and agent reliability remain limited.
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 #241 of 435 AI models we track for overall intelligence, #122 of 190 for agentic tasks. Its 262K-token context window is larger than 71% of the models we list. At $0.05 per million input tokens it is cheaper than 77% 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 756 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.