QwQ 32B Preview — Benchmarks

Benchmark scores for QwQ 32B Preview aggregated from public leaderboards (3 boards), with how it ranks among open models and how it compares with its nearest neighbours. See hardware requirements for what you need to run it.

No llmrun Composite Score for QwQ 32B Preview: the score is only published for a model measured on at least 4 of the boards in the score panel, spanning at least 2 benchmark categories and including a reasoning or coding board — or on 3 boards that narrow its score to a 90% range of at most 15.6 points. Either way the results must come from at least two different benchmarks. Its individual scores below stand on their own — see how the llmrun Composite Score gets calculated.

QwQ 32B Preview reasoning benchmarks

Multi-step logic and problem-solving — can the model think through a hard problem rather than recall an answer.

ForecastBench
ForecastBench, from the Forecasting Research Institute, asks models to predict real-world future events, with questions that only resolve after the model's training cutoff so the answers can't have been memorised. It is scored as a difficulty-adjusted Brier index, where higher is better.
58.3
58.3
median 58.1open leader 61.9
Overall best: O3 (Apr 16, 2025, unspecified) 62.5
52nd percentile · #13 of 26 open · #58 of 82 all
#13 of 26
#58 of 82
Lab-reported
Epoch AI · Nov 2024

QwQ 32B Preview knowledge benchmarks

Breadth and depth of factual knowledge across many subjects, paired with the reasoning to apply it.

MMLU-Pro
MMLU-Pro is a harder, cleaned-up successor to MMLU with ten answer choices and more reasoning-heavy questions across 14 subjects, measuring broad knowledge and reasoning together.
71.0%
71.0%
median 52.1%open leader 88.0%
Overall best: Gemini-3.1-Pro 91.2%
76th percentile · #36 of 145 open · #97 of 257 all
#36 of 145
#97 of 257
Independent
TIGER-Lab

QwQ 32B Preview instruction following benchmarks

How precisely a model obeys explicit, verifiable instructions — format, length, and content constraints — and, more broadly, how much people prefer its responses head-to-head in blind human voting.

LMArena Text
Arena (arena.ai, formerly LMArena / Chatbot Arena) ranks models by millions of blind, head-to-head human votes on real prompts. The Arena Score shown here is a Bradley-Terry rating computed with Arena's default style control, so higher means people preferred that model's answers more often — it's a relative rating, not a percentage, so compare it only to other models on this board.
1154.3
1154.3
median 1321.5open leader 1487.1
Overall best: Gemini 4 Argon (High) 1523.9
11th percentile · #166 of 187 open · #363 of 405 all
#166 of 187
#363 of 405
Arena
Arena · Oct 2026

Scores aggregated from public benchmark sources (Epoch AI: 1 board, Arena: 1 board, TIGER-Lab: 1 board) — each linked from the benchmark pages. llmrun does not run these benchmarks. Percentiles and ranks are among open models in the llmrun catalogue; the median and leader marks refer to the same field.