Qwen: QwQ 32B

Public pricingIntelligence 24/100Medium memoryDeep thinkingTool use

Qwen: QwQ 32B is a text model for reasoning and problem solving. It combines deep reasoning and planning with a 131K tokens context window and a low-cost profile. Use it for reasoning, analysis, and hard problem solving when quality, speed, and cost matters. It is a practical choice for teams that need reliable output, flexible deployment, and room to scale.

Input

$0.15/1M

Output

$0.58/1M

Cached

$0.01/1M

Batch

$0.07/1M

Calculate your QwQ 32B bill.

Set your workload β€” see cost at your exact volume.

What would QwQ 32B cost you?

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1,00010,00050,000250,0001M10M

Technical specifications

QwQ 32B at a glance.

Memory

131,072

tokens

Max reply

131,072

tokens

Memory tier

Medium

a long report or a codebase file

Tokenizer

qwen

Released

Mar 2025

Training cutoff

Oct 2024

Availability

Public pricing

Status

active

Benchmarks

Quality benchmarks

Independent evaluations from public leaderboards. Higher is better.

  • aime_2024

    79.5
  • bbh

    2.87
  • ifeval

    83.9
  • livecodebench

    63.4
  • mmlu_pro

    2.18

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 QwQ 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 β€” pick a vision-capable model instead.

Alternatives

Similar models to compare.

FAQ

QwQ 32B β€” the questions we see most.

Pricing, capabilities, alternatives β€” 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, QwQ 32B costs roughly $34 per month. Input is $0.15 /1M tokens and output is $0.58 /1M tokens.
QwQ 32B has a 131,072-token context window (medium memory β€” a long report or a codebase file). That means you can fit about 24,576 words of input and history in a single call.
Beyond text generation, QwQ 32B supports deep step-by-step reasoning, calling functions / tools, strict JSON output, fine-tuning on your own data. It streams replies by default.
QwQ 32B was released in March 2025, with training data cut off around October 2024.

Still unsure?

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