llmboard.aiAI model intelligence
Home

Model Rankings

OverallOpen ModelsAgentCodingReasoningMathKnowledgeInstruction FollowingTextVision
Image GenerationImage Editing
Video GenerationImage to VideoVideo Editing
Text to SpeechSpeech to Text
Embeddings

Efficiency

Chat Token PricingImage PricingVideo PricingAudio Pricing
Chat Speed & LatencyProvider Reliability

Benchmarks

GPQAMMLU-ProAIME 2025SWE-Bench VerifiedMMLUHumanity's Last ExamLiveCodeBenchMATHHumanEvalMMMU-Pro
All Benchmarks

Tools

Model Directory

Scoring & Data

Scoring & Data
1224 models729 benchmarks

Leaderboard Center

Overall RankingCodingCore BenchmarksPrice & ValueRuntime Performance

Modalities

All ModelsImage GenerationImage EditingVideo GenerationImage-to-VideoVideo EditingText-to-SpeechSpeech-to-TextEmbeddings

Data & Methods

Scoring MethodAll Benchmarks
llmboard.aiCopyright 2026 llmboard.ai

reasoning benchmark

HellaSwag Leaderboard

HellaSwag is a commonsense natural language inference dataset with questions requiring completion of sentence endings based on physical situations and everyday activities.

Updated Sep 5, 2026

Models27
Model coverage27
MetricScore
EvidenceB

On this page

  • Ranking
  • Highlights
  • Distribution
  • Top models
  • About
  • FAQ

HellaSwag Ranking

Higher score ranks better on this benchmark.

27 rows
Columns

Show columns

Sort by
Rank
Model
Score
Percentile
Participants
Evidence
Evaluated
Rank01ModelANClaude 3 OpusAnthropicScore95.40%Percentile100.00%Participants27EvidenceCEvaluatedSep 8, 2026
Rank02ModelOPGPT-4OpenAIScore95.30%Percentile96.15%Participants27EvidenceCEvaluatedSep 8, 2026
Rank03ModelGOGemini 1.5 ProGoogleScore93.30%Percentile92.31%Participants27EvidenceCEvaluatedSep 8, 2026
Rank04ModelXIMiMo-V2.5-ProXiaomiScore89.80%Percentile88.46%Participants27EvidenceCEvaluatedSep 8, 2026
Rank05ModelANClaude 3 SonnetAnthropicScore89.00%Percentile84.62%Participants27EvidenceCEvaluatedSep 8, 2026
Rank06ModelCOCommand R+CohereScore88.60%Percentile80.77%Participants27EvidenceCEvaluatedSep 8, 2026
Rank07ModelNRHermes 3 70BNous ResearchScore88.19%Percentile76.92%Participants27EvidenceCEvaluatedSep 8, 2026
Rank08ModelACQwen2 72B InstructAlibaba Cloud / Qwen TeamScore87.60%Percentile73.08%Participants27EvidenceCEvaluatedSep 8, 2026
Rank09ModelGOGemini 1.5 FlashGoogleScore86.50%Percentile69.23%Participants27EvidenceCEvaluatedSep 8, 2026
Rank10ModelGOGemma 2 27BGoogleScore86.40%Percentile65.38%Participants27EvidenceCEvaluatedSep 8, 2026
Rank11ModelANClaude 3 HaikuAnthropicScore85.90%Percentile61.54%Participants27EvidenceCEvaluatedSep 8, 2026
Rank12ModelNVLlama 3.1 Nemotron 70B InstructNVIDIAScore85.58%Percentile57.69%Participants27EvidenceCEvaluatedSep 8, 2026
Rank13ModelACQwen2.5 32B InstructAlibaba Cloud / Qwen TeamScore85.20%Percentile53.85%Participants27EvidenceCEvaluatedSep 8, 2026
Rank14ModelMIPhi-3.5-MoE-instructMicrosoftScore83.80%Percentile50.00%Participants27EvidenceCEvaluatedSep 8, 2026
Rank15ModelMAMistral NeMo InstructMistral AIScore83.50%Percentile46.15%Participants27EvidenceCEvaluatedSep 8, 2026
Rank16ModelACQwen2.5-Coder 32B InstructAlibaba Cloud / Qwen TeamScore83.00%Percentile42.31%Participants27EvidenceCEvaluatedSep 8, 2026
Rank17ModelGOGemma 2 9BGoogleScore81.90%Percentile38.46%Participants27EvidenceCEvaluatedSep 8, 2026
Rank18ModelIBGranite 3.3 8B BaseIBMScore80.10%Percentile34.62%Participants27EvidenceCEvaluatedSep 8, 2026
Rank19ModelGOGemma 3n E4BGoogleScore78.60%Percentile30.77%Participants27EvidenceCEvaluatedSep 8, 2026
Rank20ModelGOGemma 3n E4B Instructed LiteRT PreviewGoogleScore78.60%Percentile26.92%Participants27EvidenceCEvaluatedSep 8, 2026
Rank21ModelACQwen2.5-Coder 7B InstructAlibaba Cloud / Qwen TeamScore76.80%Percentile23.08%Participants27EvidenceCEvaluatedSep 8, 2026
Rank22ModelGOGemma 3n E2BGoogleScore72.20%Percentile19.23%Participants27EvidenceCEvaluatedSep 8, 2026
Rank23ModelGOGemma 3n E2B Instructed LiteRT (Preview)GoogleScore72.20%Percentile15.38%Participants27EvidenceCEvaluatedSep 8, 2026
Rank24ModelMELlama 3.2 3B InstructMetaScore69.80%Percentile11.54%Participants27EvidenceCEvaluatedSep 8, 2026
Rank25ModelMIPhi-3.5-mini-instructMicrosoftScore69.40%Percentile7.69%Participants27EvidenceCEvaluatedSep 8, 2026
Rank26ModelMIPhi 4 MiniMicrosoftScore69.10%Percentile3.85%Participants27EvidenceCEvaluatedSep 8, 2026
Rank27ModelBAERNIE 4.5BaiduScore33.00%Percentile0.00%Participants27EvidenceCEvaluatedSep 8, 2026

HellaSwag Highlights

The leading models and scores on this benchmark.

HellaSwag Score Distribution

A closer view of the leading scores on this benchmark.

HellaSwag

The Top AI Models for HellaSwag

The first five results on this benchmark, with official price and output speed added where the model identity can be matched.

What is HellaSwag?

What HellaSwag measures and how its scores work.

HellaSwag is a commonsense natural language inference dataset that uses Adversarial Filtering to create questions designed to be trivial for humans and difficult for state-of-the-art models.

It measures performance on sentence-ending completion questions based on physical situations and everyday activities, reported as Score in ratio units.

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

Family
HellaSwag
Modality
text
Primary category
reasoning
Score direction
higher
LLMBoard eligible
No
Evaluation key
overall

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

FAQ

Common questions about HellaSwag.

Which model scores highest on HellaSwag?

Claude 3 Opus is currently ranked first with 95.40%.

What are the top three models on HellaSwag?

The current leaders are Claude 3 Opus (95.40%), GPT-4 (95.30%), and Gemini 1.5 Pro (93.30%).

Which HellaSwag model has the lowest official input price?

Phi 4 Mini has the lowest matched official input price at $0.08 input / $0.30 output per 1M tokens.

Which models are fastest among HellaSwag results?

The fastest matched records are Llama 3.2 3B Instruct (171.50 tok/s via DeepInfra), Gemini 1.5 Flash (150.00 tok/s via Google), and GPT-4 (104.00 tok/s via Azure).

Does the highest score result prove overall model quality?

No. This benchmark measures one defined capability or task. The overall LLMBoard score uses a separate aggregation across eligible benchmark evidence.

What does HellaSwag measure?

It measures performance on sentence-ending completion questions based on physical situations and everyday activities, reported as Score in ratio units.

Is a higher score better?

Yes. Higher values rank better for this benchmark.

How many models are compared?

27 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.

Rank #1Claude 3 Opus95.40%
Rank #2GPT-495.30%
Rank #3Gemini 1.5 Pro93.30%
Rank #4MiMo-V2.5-Pro89.80%

Ranking basisThis hellaswag AI model leaderboard uses descending score in the benchmark original unit. The leaderboard ranking keeps matched price and speed data separate from benchmark evidence.

  1. 01
    AN
    Claude 3 OpusAnthropic
    Score
    95.40%
    Speed
    Up to 100.00 tok/s via Anthropic

    Strengths

    • Ranks #1 of 27 compared models
    • 100th percentile on this benchmark
    • C evidence result

    Considerations

    • This result measures HellaSwag, not total model capability
  2. 02
    OP
    GPT-4OpenAI
    Score
    95.30%
    Price
    $30 input / $60 output per 1M tokens
    Speed
    Up to 104.00 tok/s via Azure

    Strengths

    • Ranks #2 of 27 compared models
    • 96th percentile on this benchmark
    • C evidence result

    Considerations

    • This result measures HellaSwag, not total model capability
  3. 03
    GO
    Google
    Score
    93.30%
    Speed
    Up to 85.00 tok/s via Google

    Strengths

    • Ranks #3 of 27 compared models
    • 92th percentile on this benchmark
    • C evidence result

    Considerations

    • This result measures HellaSwag, not total model capability
  4. 04
    XI
    Xiaomi
    Score
    89.80%
    Price
    $0.44 input / $0.87 output per 1M tokens
    Speed
    Up to 5.27 tok/s via DeepInfra

    Strengths

    • Ranks #4 of 27 compared models
    • 88th percentile on this benchmark
    • C evidence result

    Considerations

    • This result measures HellaSwag, not total model capability
  5. 05
    AN
    Anthropic
    Score
    89.00%
    Speed
    Up to 100.00 tok/s via Anthropic

    Strengths

    • Ranks #5 of 27 compared models
    • 85th percentile on this benchmark
    • C evidence result

    Considerations

    • This result measures HellaSwag, not total model capability

Selection summary

Best AI Models for HellaSwag

Claude 3 Opus currently leads HellaSwag with 95.40%. 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.

Gemini 1.5 Pro
MiMo-V2.5-Pro
Claude 3 Sonnet
Benchmark rank #1Claude 3 Opus95.40% · Up to 100.00 tok/s via Anthropic
Benchmark rank #2GPT-495.30% · $30 input / $60 output per 1M tokens
Benchmark rank #3Gemini 1.5 Pro93.30% · Up to 85.00 tok/s via Google