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reasoning benchmark

FRAMES

Factuality, Retrieval, And reasoning MEasurement Set - a unified evaluation dataset of 824 challenging multi-hop questions for testing retrieval-augmented generation systems across factuality, retrieval accuracy, and reasoning capabilities, requiring integration of 2-15 Wikipedia articles per question

Updated Aug 11, 2026

Models2
Model coverage2
MetricScore
EvidenceB

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FRAMES Ranking

Higher score ranks better on this benchmark.

2 rows
Columns

Show columns

01MAKimi K2-Thinking-0905Moonshot AI87.0%100.0%2CAug 11, 2026
02DEDeepSeek-V3DeepSeek73.3%0.0%2CAug 11, 2026

FRAMES Score Distribution

A closer view of the leading scores on this benchmark.

FRAMES

FRAMES Highlights

The leading models and scores on this benchmark.

Rank #1Kimi K2-Thinking-090587.0%Rank #2DeepSeek-V373.3%

What is FRAMES?

What FRAMES measures and how its scores work.

Factuality, Retrieval, And reasoning MEasurement Set - a unified evaluation dataset of 824 challenging multi-hop questions for testing retrieval-augmented generation systems across factuality, retrieval accuracy, and reasoning capabilities, requiring integration of 2-15 Wikipedia articles per question

Scores are shown in ratio. This benchmark is not independently verified and has an evidence level of B.

Family
FRAMES
Modality
text
Primary category
reasoning
Score direction
higher
LLMBoard eligible
No
Evaluation key
frames|llm-stats-current

Benchmark scores retain their original unit. Overall score eligibility is shown separately.

FAQ

Common questions about FRAMES.

Which model scores highest on FRAMES?

Kimi K2-Thinking-0905 is currently ranked first with 87.0%.

What does FRAMES measure?

Factuality, Retrieval, And reasoning MEasurement Set - a unified evaluation dataset of 824 challenging multi-hop questions for testing retrieval-augmented generation systems across factuality, retrieval accuracy, and reasoning capabilities, requiring integration of 2-15 Wikipedia articles per question

Is a higher score better?

Yes. Higher values rank better for this benchmark.

How many models are compared?

2 model results are currently shown.

Does this benchmark affect the overall score?

No. This benchmark is shown for reference but does not contribute to the overall score.