Knowledge Benchmark

C-Eval

C-Eval - comprehensive Chinese evaluation benchmark across 52 subjects.

Category

Knowledge

Score type

percent

Scale

100%

higher is better

Models tested

11

What is C-Eval?

C-Eval is a benchmark for broad factual and academic knowledge. The official description says: "C-Eval - comprehensive Chinese evaluation benchmark across 52 subjects". Below we describe in simple words what benchmarks of this type generally examine.

What does it test?

C-Eval measures broad factual and academic knowledge. In detail, it checks:

  • facts and concepts from many academic fields at once
  • harder variants with several plausible answer options
  • knowledge that goes beyond the model's training-set surface forms
  • resisting the plausible-but-wrong answers deliberately included

How to read the score

The score is accuracy: the percentage of tasks answered or solved correctly. 100% means every task was solved perfectly; higher is better.

Official methodology note: C-Eval - comprehensive Chinese evaluation benchmark across 52 subjects.

Frequently asked questions

What is the C-Eval benchmark?

C-Eval is a benchmark for broad factual and academic knowledge. The official description says: 'C-Eval - comprehensive Chinese evaluation benchmark across 52 subjects'. Below we describe in simple words what benchmarks of this type generally examine.

What does C-Eval test?

C-Eval mainly measures broad factual and academic knowledge. Concretely, it checks: facts and concepts from many academic fields at once; harder variants with several plausible answer options; knowledge that goes beyond the model's training-set surface forms.

How is the C-Eval score calculated?

The score is accuracy: the percentage of tasks answered or solved correctly. 100% means every task was solved perfectly; higher is better. The declared maximum score of this benchmark is 100.0.

Where do I get C-Eval data and scores?

The official source is https://cevalbenchmark.com/. 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/c-eval/scores) or pull it directly from the Open LLM Radar API with any HTTP client.

Model scores 11 models tested

Reset
# Model Score Date Source Verified
1 DeepSeek-V4-Pro
DeepSeek
93.1%
26.06.2026 Report Verified
2 DeepSeek-V4-Flash
DeepSeek
92.1%
26.06.2026 Report Verified
3 Qwen3-235B-A22B
Qwen Team (Alibaba Cloud)
92.1%
01.02.2026 Report Unverified
4 Qwen3.5-122B-A10B
Qwen Team (Alibaba Cloud)
91.9%
01.02.2026 Report Verified
5 Qwen3.6-27B
Qwen Team (Alibaba Cloud)
91.4%
22.04.2026 Qwen Team (official model card) Verified
6 Qwen3.5-27B
Qwen Team (Alibaba Cloud)
90.5%
16.04.2026 Qwen Team (official model card - comparison) Unverified
7 Qwen3.5-35B-A3B
Qwen Team (Alibaba Cloud)
90.2%
16.04.2026 Qwen Team (official model card - comparison) Unverified
8 Qwen3.6-35B-A3B
Qwen Team (Alibaba Cloud)
90%
16.04.2026 Qwen Team (official model card) Verified
9 Qwen3.5-4B
Qwen
85.1%
01.02.2026 Report Verified
10 Gemma4-31B-it
Google
82.6%
16.04.2026 Qwen Team (official model card - comparison) Unverified
11 Gemma4-26B-A4B
Google
82.5%
16.04.2026 Qwen Team (official model card - comparison) Unverified

What now?

You've seen how models score on C-Eval — here's what to do next.