Qwen: Qwen3 30B A3B Instruct 2507

Public pricingIntelligence 74/100Large memoryツール利用

Qwen: Qwen3 30B A3B Instruct 2507 は テキスト モデルで、推論と問題解決 に向いています。深い推論と計画、262K tokensのコンテキスト、低コストの特性を組み合わせ、reasoning, analysis, and hard problem solving で安定した動作を支えます。品質・速度・コスト が重要な場面に合っており、安定した出力、柔軟な導入、拡張性を求めるチームに実用的です。 安定した応答、長い文脈処理、そして試作から本番まで広く使える柔軟さが必要な場面で役立ちます。 安定した応答、長い文脈処理、そして試作から本番まで広く使える柔軟さが必要な場面で役立ちます。 安定した応答、長い文脈処理、そして試作から本番まで広く使える柔軟さが必要な場面で役立ちます。

Input

$0.09/1M

Output

$0.30/1M

Cached

$0.01/1M

Batch

$0.03/1M

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What would Qwen3 30B A3B Instruct 2507 cost you?

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1,00010,00050,000250,0001M10M

Technical specifications

Qwen3 30B A3B Instruct 2507 at a glance.

Memory

262,144

tokens

Max reply

262,144

tokens

Memory tier

Large

an entire book or large codebase

Tokenizer

qwen3

Released

Jul 2025

Training cutoff

Apr 2025

Availability

Public pricing

Status

active

Benchmarks

Quality benchmarks

Independent evaluations from public leaderboards. Higher is better.

  • aime_2025

    61.3

  • gpqa_diamond

    70.4

  • ifeval

    84.7

  • livecodebench

    43.2

  • mmlu_pro

    78.4

What it can do

Capabilities & limits.

  • Understands images
  • Deep step-by-step thinking
  • Uses tools / calls functions
  • Strict JSON output
  • Streams replies
  • Fine-tunable on your data

When to pick Qwen3 30B A3B Instruct 2507

  • Agentic workflows that call tools or APIs.
  • Long documents, full codebases, or extensive chat histories.
  • High-volume workloads where unit cost matters.

When to look elsewhere

  • Your workload involves images — pick a vision-capable model instead.

Alternatives

Similar models to compare.

FAQ

Qwen3 30B A3B Instruct 2507 — the questions we see most.

Pricing, capabilities, alternatives — generated from the same data that powers the calculator above.

Get instant answers from our AI agent

At a typical workload of 50,000 conversations a month with 1,500-token prompts and 800-token replies, Qwen3 30B A3B Instruct 2507 costs roughly $19 per month. Input is $0.09 /1M tokens and output is $0.30 /1M tokens.
Qwen3 30B A3B Instruct 2507 has a 262,144-token context window (large memory — an entire book or large codebase). That means you can fit about 49,152 words of input and history in a single call.
Beyond text generation, Qwen3 30B A3B Instruct 2507 supports calling functions / tools, strict JSON output, fine-tuning on your own data. It streams replies by default.
Qwen3 30B A3B Instruct 2507 was released in July 2025, with training data cut off around April 2025.
Models in a similar class include Qwen3 Next 80B A3B Instruct, Qwen3.5-9B, Qwen3 235B A22B Instruct 2507. The "Similar models" section below this FAQ links into each.

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