CFEval
CFEval - Qwen's CodeForces-style competitive programming evaluation; score is an Elo-like rating (higher is better).
Category
Agentic Coding
Score type
elo
Scale
relative
higher is better
Models tested
1
What is CFEval?
CFEval is a benchmark for how well a model works as an autonomous coding agent. The official description says: "CFEval - Qwen's CodeForces-style competitive programming evaluation; score is an Elo-like rating (higher is better)". Below we describe in simple words what benchmarks of this type generally examine.
What does it test?
CFEval measures how well a model works as an autonomous coding agent. In detail, it checks:
- fixing real, open bugs from real software repositories
- planning multi-step changes, running commands and editing files by itself
- passing the project's test suite after its changes
- handling whole repositories, not just small isolated code snippets
How to read the score
The score is an Elo rating, built from head-to-head comparisons between models (like chess ratings). The number is only meaningful relative to the other rated models — higher is better.
Official methodology note: CFEval - Qwen's CodeForces-style competitive programming evaluation; score is an Elo-like rating (higher is better).
Frequently asked questions
What is the CFEval benchmark?
CFEval is a benchmark for how well a model works as an autonomous coding agent. The official description says: 'CFEval - Qwen's CodeForces-style competitive programming evaluation; score is an Elo-like rating (higher is better)'. Below we describe in simple words what benchmarks of this type generally examine.
What does CFEval test?
CFEval mainly measures how well a model works as an autonomous coding agent. Concretely, it checks: fixing real, open bugs from real software repositories; planning multi-step changes, running commands and editing files by itself; passing the project's test suite after its changes.
How is the CFEval score calculated?
The score is an Elo rating, built from head-to-head comparisons between models (like chess ratings). The number is only meaningful relative to the other rated models — higher is better.
Where do I get CFEval data and scores?
The official source is https://huggingface.co/Qwen/Qwen3-Next-80B-A3B-Thinking. The official benchmark page/reference is linked on this page. Every score on Open LLM Radar is also available as open data: download the scores JSON (http://open-llm-radar-api:8000/api/v1/benchmarks/cfeval/scores) or pull it directly from the Open LLM Radar API with any HTTP client.
Benchmark data & downloads
Where to get, inspect and reuse the data behind this benchmark.
Official benchmark page / paper
The benchmark maintainer's website, paper or leaderboard
Benchmark metadata (JSON)
This page's benchmark record from the Open LLM Radar API
All model scores (JSON download)
Full score table as JSON; paginate with limit/offset params
Open LLM Radar API docs
Swagger UI to explore and reuse all radar API endpoints
Model scores 1 model tested
| # | Model | Score | Date | Source | Verified |
|---|---|---|---|---|---|
| 1 |
Qwen3-Next-80B-A3B-Thinking
Qwen
|
2071 Elo
|
10.09.2025 | Report | Verified |