Qwen: Qwen3 32B

Public pricingIntelligence 79/100Medium memoryTiefes DenkenTool-Nutzung

Qwen: Qwen3 32B ist ein Text-Modell für Schlussfolgern und Problemlösen. Es verbindet tiefes Schlussfolgern und Planen und geringe Latenz und effiziente Inferenz, einen Kontext von 41K tokens und ein kostengünstig-Profil für zuverlässige Arbeit über reasoning, analysis, and hard problem solving.

Input

$0.08/1M

Output

$0.24/1M

Cached

$0.04/1M

Batch

$0.05/1M

Calculate your Qwen3 32B bill.

Set your workload — see cost at your exact volume.

What would Qwen3 32B cost you?

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1,00010,00050,000250,0001M10M

Technical specifications

Qwen3 32B at a glance.

Memory

40,960

tokens

Max reply

40,960

tokens

Memory tier

Medium

a long report or a codebase file

Tokenizer

qwen3

Released

Apr 2025

Training cutoff

Jan 2025

Availability

Public pricing

Status

active

Benchmarks

Quality benchmarks

Independent evaluations from public leaderboards. Higher is better.

  • mmlu

    83.3

  • mmlu_pro

    65.5

  • aime_2024

    81.4

  • aime_2025

    72.9

  • scipredict

    17.04

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 32B

  • Multi-step reasoning, research agents, or hard math.
  • Agentic workflows that call tools or APIs.
  • 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 32B — 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 32B costs roughly $16 per month. Input is $0.08 /1M tokens and output is $0.24 /1M tokens.
Qwen3 32B has a 40,960-token context window (medium memory — a long report or a codebase file). That means you can fit about 7,680 words of input and history in a single call.
Beyond text generation, Qwen3 32B supports deep step-by-step reasoning, calling functions / tools, strict JSON output, fine-tuning on your own data. It streams replies by default.
Qwen3 32B was released in April 2025, with training data cut off around January 2025.
Models in a similar class include Qwen3 30B A3B, Qwen3 30B A3B Thinking 2507, Qwen3.5-Flash. The "Similar models" section below this FAQ links into each.

Still unsure?

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