QwQ-32B

// Overview

QwQ-32B is the flagship release in Alibaba's QwQ reasoning line, open-sourced by the Qwen team in early March 2025. It is a 32.5-billion-parameter dense transformer (31.0B non-embedding) built on the Qwen2.5-32B base and turned into a chain-of-thought 'thinking' model through large-scale reinforcement learning. The whole model ships as open weights under the permissive Apache-2.0 license on Hugging Face and ModelScope, and is small enough to run on a single high-end consumer GPU.

The headline claim is efficiency: despite having only 32B dense parameters, QwQ-32B reaches performance roughly comparable to DeepSeek-R1 — a 671B-parameter Mixture-of-Experts model with about 37B active per token — and outperforms OpenAI's o1-mini on the benchmarks Qwen reported. Qwen credits a two-stage, outcome-based RL pipeline: a first stage that rewards correct answers on math and code (verified by an accuracy checker and a code-execution server), then a second stage that adds instruction-following, tool use, and human-preference alignment without eroding the reasoning gains.

QwQ-32B is text-only with a 131,072-token (131K) context window, using YaRN to extend beyond the base 32K. It marks the production successor to the late-2024 QwQ-32B-Preview and the QVQ-72B-Preview visual-reasoning experiment, and represents the standalone phase of Qwen's reasoning work before 'thinking' folded into the unified Qwen3 family. You can try it on Qwen Chat or call it via Alibaba Cloud's DashScope (model id qwq-32b) and third-party hosts such as OpenRouter.

// Benchmarks

1. AIME2479.5%
2. LiveCodeBench63.4%
3. LiveBench73.1%
4. IFEval83.9%
5. BFCL (function calling)66.4%

Scores on a 0–100 scale (25-point gridlines); higher is better. Each benchmark links to its published source.

// Pricing

Representative hosted rate tracked by Artificial Analysis (blended ~$0.69/1M). The weights are open (Apache-2.0), so self-hosting is free aside from compute; per-token prices vary by provider on Alibaba Cloud DashScope, OpenRouter, and other hosts.

Pricing source ↗

// Strengths

• Open weights under the permissive Apache-2.0 license — free for commercial use, self-hosting, fine-tuning, and distillation
• Strong reasoning at a small footprint: a 32B dense model reaching scores roughly comparable to the 671B DeepSeek-R1 and beating OpenAI o1-mini on Qwen's reported benchmarks
• Competition-grade math and coding via RL scaling — AIME24 79.5, LiveCodeBench 63.4
• Leads its comparison set on general reasoning (LiveBench 73.1) and tool/function calling (BFCL 66.4)
• Runs locally on a single high-end consumer GPU, unlike the much larger MoE reasoning models it competes with
• 131K-token context window (with YaRN extension) for long problems and documents

// Best for

• Competition-style mathematics and multi-step logical reasoning
• Coding and algorithmic problem-solving (LiveCodeBench-style tasks)
• Agentic tool use and function-calling workflows
• Self-hosted reasoning deployments where an open, Apache-2.0-licensed model is required
• Running a capable reasoning model locally on a single consumer GPU
• Research and distillation: using QwQ-32B's chain-of-thought to study or train smaller reasoning models

// How to access

// QwQ / QVQ (reasoning preview) — every version

The full lineage of the QwQ / QVQ (reasoning preview) line, newest first. Every version has its own page — click any to compare specs, benchmarks and pricing.