productivity benchmark
CoWorkBench is Qwen's internal cowork benchmark for evaluating long-horizon office and productivity agent tasks across domains such as computer science, finance, law, and medicine.
Updated Sep 5, 2026
Higher score ranks better on this benchmark.
Rank | Model | Score | Percentile | Participants | Evidence | Evaluated |
|---|
| Rank01 | ModelAC | Score74.80% | Percentile100.00% | Participants6 | EvidenceC | Evaluated |
| Rank02 | ModelAC | Score73.90% | Percentile80.00% | Participants6 | EvidenceC | Evaluated |
| Rank03 | ModelAC | Score73.90% | Percentile60.00% | Participants6 | EvidenceC | Evaluated |
| Rank04 | ModelAC | Score70.70% | Percentile40.00% | Participants6 | EvidenceC | Evaluated |
| Rank05 | ModelAC | Score67.20% | Percentile20.00% | Participants6 | EvidenceC | Evaluated |
| Rank06 | ModelAC | Score65.10% | Percentile0.00% | Participants6 | EvidenceC | Evaluated |
The leading models and scores on this benchmark.
A closer view of the leading scores on this benchmark.
The first five results on this benchmark, with official price and output speed added where the model identity can be matched.
What CoWorkBench measures and how its scores work.
CoWorkBench is Qwen's internal cowork benchmark.
It measures performance on long-horizon office and productivity agent tasks across domains such as computer science, finance, law, and medicine, using the Score metric as a ratio.
Scores are shown in ratio. This benchmark is not independently verified and has an evidence level of B.
LLM Stats. Benchmark scores retain their original unit. Overall score eligibility is shown separately.
Common questions about CoWorkBench.
Qwen3.8 Max is currently ranked first with 74.80%.
The current leaders are Qwen3.8 Max (74.80%), Qwen3.8-Flash-Next (73.90%), and Qwen3.8 Flash (73.90%).
Qwen3.8 Flash has the lowest matched official input price at $0.15 input / $0.47 output per 1M tokens.
The fastest matched records are Qwen3.8 Max (60.87 tok/s via DeepInfra).
No. This benchmark measures one defined capability or task. The overall LLMBoard score uses a separate aggregation across eligible benchmark evidence.
It measures performance on long-horizon office and productivity agent tasks across domains such as computer science, finance, law, and medicine, using the Score metric as a ratio.
Yes. Higher values rank better for this benchmark.
6 model results are currently shown.
No. This benchmark is shown for reference but does not contribute to the overall score.
Ranking basisThis coworkbench AI model leaderboard uses descending score in the benchmark original unit. The leaderboard ranking keeps matched price and speed data separate from benchmark evidence.
Selection summary
Qwen3.8 Max currently leads CoWorkBench with 74.80%. It is the top model on this specific benchmark, while the best LLM for the broader task should also be checked against other benchmarks, price, and runtime.
Use this leaderboard with the supporting benchmark results and coverage details above. A leaderboard position summarizes the selected ranking signal; it does not replace workload-specific testing.