Vals MMMU (MMMU)
Multimodal Multi-task Benchmark
Data verifiedHow BenchLM shows MMMU
BenchLM mirrors the public Vals AI MMMU leaderboard captured from https://www.vals.ai/benchmarks/mmmu and updated by Vals on July 9, 2026. The snapshot preserves overall scores, uncertainty, latency, cost-per-test metadata, and task-level scores where Vals publishes them.
MMMU is display only on BenchLM. Vals proprietary or Vals-hosted aggregate views are useful context, but BenchLM does not use them as weighted ranking inputs or as a replacement for benchmark-native source records.
MMMU score on MMMU — July 9, 2026
BenchLM mirrors the published mmmu score view for MMMU. Claude Fable 5 leads the public snapshot at 89.31% , followed by GPT-5.6 Sol (88.84%) and Gemini 3.5 Flash (88.27%). BenchLM does not use these results to rank models overall.
Claude Fable 5
Anthropic
anthropic/claude-fable-5
GPT-5.6 Sol
OpenAI
openai/gpt-5.6-sol
Gemini 3.5 Flash
google/gemini-3.5-flash
The published MMMU snapshot is tightly clustered at the top: Claude Fable 5 sits at 89.31%, while the third row is only 1.04 points behind. The broader top-10 spread is 2.64 points, so many of the published scores sit in a relatively narrow band.
81 models have been evaluated on MMMU. The benchmark falls in the External benchmark mirrors category. BenchLM tracks this category separately from its weighted global scoring system, so these results are best compared on the dedicated Korean benchmark views. MMMU is currently displayed for reference but excluded from the scoring formula, so it does not directly affect overall rankings.
About MMMU
Year
2026
Tasks
Multimodal academic task suite
Format
Accuracy score
Difficulty
Multimodal college-level reasoning
BenchLM mirrors the public Vals AI MMMU leaderboard as display-only external evidence. The captured snapshot preserves overall scores, task-level scores where Vals publishes them, uncertainty, latency, and cost-per-test metadata. It is excluded from BenchLM weighted rankings.
BenchLM freshness & provenance
Version
MMMU 2026
Refresh cadence
Quarterly
Staleness state
Current
Question availability
Public benchmark set
BenchLM uses freshness metadata to decide whether a benchmark should still be treated as a strong differentiator, a benchmark to watch, or a display-only reference. For the full scoring policy, see the BenchLM methodology page.
MMMU score table (81 models)
FAQ
What does MMMU measure?
Multimodal Multi-task Benchmark
Which model leads the published MMMU snapshot?
Claude Fable 5 currently leads the published MMMU snapshot with 89.31% mmmu score. BenchLM shows this benchmark for display only and does not use it in overall rankings.
How many models are evaluated on MMMU?
81 AI models are included in BenchLM's mirrored MMMU snapshot, based on the public leaderboard captured on July 9, 2026.
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