Reasoning Benchmark

BIG-Bench Hard

BIG-Bench Hard (BBH) - a subset of 23 challenging BIG-Bench tasks. few-shot.

Category

Reasoning

Score type

percent

Scale

100%

higher is better

Models tested

8

What is BIG-Bench Hard?

BIG-Bench Hard (BBH) is a subset of 23 challenging tasks from the crowd-sourced BIG-Bench collection on which earlier language models still clearly trailed the human average. Today BBH is one of the most established reasoning baselines.

What does it test?

BIG-Bench Hard measures general reasoning and comprehension. In detail, it checks:

  • 23 very different reasoning task types
  • logical, linguistic and spatial reasoning
  • multi-step thinking with chain-of-thought
  • comparability as an established baseline

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.

Frequently asked questions

What is the BIG-Bench Hard benchmark?

BIG-Bench Hard (BBH) is a subset of 23 challenging tasks from the crowd-sourced BIG-Bench collection on which earlier language models still clearly trailed the human average. Today BBH is one of the most established reasoning baselines.

What does BIG-Bench Hard test?

BIG-Bench Hard mainly measures general reasoning and comprehension. Concretely, it checks: 23 very different reasoning task types; logical, linguistic and spatial reasoning; multi-step thinking with chain-of-thought.

How is the BIG-Bench Hard 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 BIG-Bench Hard data and scores?

The official source is https://paperswithcode.com/dataset/bbh. 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/big-bench-hard/scores) or pull it directly from the Open LLM Radar API with any HTTP client.

Model scores 8 models tested

Reset
# Model Score Date Source Verified
1 GLM-5.3-Flash
Zhipu AI
86.6%
27.08.2026 Report Verified
2 Gemma 3 27B PT
Google DeepMind
77.7%
27.02.2025 Report Verified
3 ERNIE-5.5-Flash-Base
Baidu
77.1%
— HF model card baidu/ERNIE-5.5-Flash-Base (BBH, EM direct, 3-shot, Unified Pipeline) Unverified
4 Clef
Cloudflare
73.7%
— Report Verified
5 Gemma 3 12B PT
Google DeepMind
72.6%
27.02.2025 Report Verified
6 Clef-Flash
Cloudflare
68.9%
— Report Verified
7 Gemma 3 4B PT
Google DeepMind
50.9%
27.02.2025 Report Verified
8 Gemma 3 1B PT
Google DeepMind
28.4%
27.02.2025 Report Verified

What now?

You've seen how models score on BIG-Bench Hard — here's what to do next.