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multimodal benchmark

MedXpertQA Leaderboard

MedXpertQA is a benchmark of expert-level medical knowledge and advanced reasoning with 4,460 questions spanning 17 specialties and 11 body systems, including text-only and multimodal subsets.

Updated Sep 5, 2026

Models12
Model coverage12
MetricScore
EvidenceB

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MedXpertQA Ranking

Higher score ranks better on this benchmark.

12 rows
Columns

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Sort by
Rank
Model
Score
Percentile
Participants
Evidence
Evaluated
Rank01ModelMEMuse SparkMetaScore78.40%Percentile100.00%Participants12EvidenceCEvaluatedSep 8, 2026
Rank02ModelACQwen3.5-122B-A10BAlibaba Cloud / Qwen TeamScore67.30%Percentile90.91%Participants12EvidenceCEvaluatedSep 8, 2026
Rank03ModelACQwen3.5-27BAlibaba Cloud / Qwen TeamScore62.40%Percentile81.82%Participants12EvidenceCEvaluatedSep 8, 2026
Rank04ModelACQwen3.5-35B-A3BAlibaba Cloud / Qwen TeamScore61.40%Percentile72.73%Participants12EvidenceCEvaluatedSep 8, 2026
Rank05ModelGOGemma 4 31BGoogleScore61.30%Percentile63.64%Participants12EvidenceCEvaluatedSep 8, 2026
Rank06ModelGOGemma 4 26B-A4BGoogleScore58.10%Percentile54.55%Participants12EvidenceCEvaluatedSep 8, 2026
Rank07ModelGODiffusionGemma 26B-A4BGoogleScore49.00%Percentile45.45%Participants12EvidenceCEvaluatedSep 8, 2026
Rank08ModelGOGemma 4 12BGoogleScore48.70%Percentile36.36%Participants12EvidenceCEvaluatedSep 8, 2026
Rank09ModelMIMAI-Thinking-1MicrosoftScore43.00%Percentile27.27%Participants12EvidenceCEvaluatedSep 8, 2026
Rank10ModelGOGemma 4 E4BGoogleScore28.70%Percentile18.18%Participants12EvidenceCEvaluatedSep 8, 2026
Rank11ModelGOGemma 4 E2BGoogleScore23.50%Percentile9.09%Participants12EvidenceCEvaluatedSep 8, 2026
Rank12ModelGOMedGemma 4B ITGoogleScore18.80%Percentile0.00%Participants12EvidenceCEvaluatedSep 8, 2026

MedXpertQA Highlights

The leading models and scores on this benchmark.

MedXpertQA Score Distribution

A closer view of the leading scores on this benchmark.

MedXpertQA

The Top AI Models for MedXpertQA

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

What is MedXpertQA?

What MedXpertQA measures and how its scores work.

MedXpertQA is a medical benchmark featuring expert-level exam questions with diverse medical images and clinical information.

It measures expert-level medical knowledge and advanced reasoning using Score, reported as a ratio.

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

Family
MedXpertQA
Modality
multimodal
Primary category
multimodal
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 MedXpertQA.

Which model scores highest on MedXpertQA?

Muse Spark is currently ranked first with 78.40%.

What are the top three models on MedXpertQA?

The current leaders are Muse Spark (78.40%), Qwen3.5-122B-A10B (67.30%), and Qwen3.5-27B (62.40%).

Which MedXpertQA model has the lowest official input price?

Qwen3.5-35B-A3B has the lowest matched official input price at $0.25 input / $2.0 output per 1M tokens.

Which models are fastest among MedXpertQA results?

The fastest matched records are Gemma 4 31B (22.86 tok/s via FriendliAI).

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 MedXpertQA measure?

It measures expert-level medical knowledge and advanced reasoning using Score, reported as a ratio.

Is a higher score better?

Yes. Higher values rank better for this benchmark.

How many models are compared?

12 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 #1Muse Spark78.40%
Rank #2Qwen3.5-122B-A10B67.30%
Rank #3Qwen3.5-27B62.40%
Rank #4Qwen3.5-35B-A3B61.40%

Ranking basisThis medxpertqa 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
    ME
    Muse SparkMeta
    Score
    78.40%

    Strengths

    • Ranks #1 of 12 compared models
    • 100th percentile on this benchmark
    • C evidence result

    Considerations

    • This result measures MedXpertQA, not total model capability
  2. 02
    AC
    Qwen3.5-122B-A10BAlibaba Cloud / Qwen Team
    Score
    67.30%
    Price
    $0.40 input / $3.2 output per 1M tokens

    Strengths

    • Ranks #2 of 12 compared models
    • 91th percentile on this benchmark
    • C evidence result

    Considerations

    • This result measures MedXpertQA, not total model capability
  3. 03
    AC
    Alibaba Cloud / Qwen Team
    Score
    62.40%
    Price
    $0.30 input / $2.4 output per 1M tokens

    Strengths

    • Ranks #3 of 12 compared models
    • 82th percentile on this benchmark
    • C evidence result

    Considerations

    • This result measures MedXpertQA, not total model capability
  4. 04
    AC
    Alibaba Cloud / Qwen Team
    Score
    61.40%
    Price
    $0.25 input / $2.0 output per 1M tokens

    Strengths

    • Ranks #4 of 12 compared models
    • 73th percentile on this benchmark
    • C evidence result

    Considerations

    • This result measures MedXpertQA, not total model capability
  5. 05
    GO
    Google
    Score
    61.30%
    Speed
    Up to 22.86 tok/s via FriendliAI

    Strengths

    • Ranks #5 of 12 compared models
    • 64th percentile on this benchmark
    • C evidence result

    Considerations

    • This result measures MedXpertQA, not total model capability

Selection summary

Best AI Models for MedXpertQA

Muse Spark currently leads MedXpertQA with 78.40%. 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.

Qwen3.5-27B
Qwen3.5-35B-A3B
Gemma 4 31B
Benchmark rank #1Muse Spark78.40%
Benchmark rank #2Qwen3.5-122B-A10B67.30% · $0.40 input / $3.2 output per 1M tokens
Benchmark rank #3Qwen3.5-27B62.40% · $0.30 input / $2.4 output per 1M tokens