Benchmark Almanac

DiffusionGemma 26B A4B

DiffusionGemma 26B A4B ranks first on 2 of the 22 benchmarks it has scores on.

Google DeepMind Released 10 Jun 2026 Family Gemma 4 The lab's model card
23
Benchmarks with a score
2
Ranked first, out of five or more models
3
In the top three
Google DeepMind Jun 2026

DiffusionGemma 26B A4B

Open weights Mid-size

No Epoch Capabilities Index score yet
  • MMMU-Pro 54.3% #62 /72
  • MedXpertQA-MM 49% #10 /12
  • BIG-Bench Extra Hard 47.6% #6 /11

Where it ranks

Its best score on each benchmark, and where that ranks among every model with a score there. We rank each model once, at its best setting.

Knowledge and language

BenchmarkScoreRankSource
IFEval 97.4% #3 of 126 Model card
MGSM 84.8% #25 of 52 Model card
BIG-Bench Extra Hard 47.6% #6 of 11 Model card
MMLU-Pro 77.6% #89 of 151 Model card
MMMLU 81.5% #37 of 62 Model card
Humanity's Last Exam 11.9% #126 of 147 Model card
MRCR v2 32% #25 of 27 Model card

Math and science

BenchmarkScoreRankSource
GSM8K 96.3% #5 of 87 Model card
HiddenMath 80.6% #1 of 11 Model card
GPQA Diamond 73.2% #151 of 284 Model card
PutnamBench 67.4% #4 of 7 Model card
AIME 2026 69.1% #33 of 34 Model card

Coding

BenchmarkScoreRankSource
HumanEval 94.5% #5 of 95 Model card
Natural2Code 94% #1 of 9 Model card
LBPP (Less Basic Python Problems) 81% #1 of 2 Model card
BigCodeBench 46% #6 of 11 Model card
LiveCodeBench v6 69.1% #50 of 76 Model card
Codeforces rating 1,429 #38 of 41 Model card

Agents and tools

BenchmarkScoreRankSource
tau2-bench 56.2% #63 of 69 Model card

Professional work

BenchmarkScoreRankSource
MedXpertQA-MM 49% #10 of 12 Model card

Vision, audio and robotics

BenchmarkScoreRankSource
OmniDocBench v1.5 0.32 #6 of 13 Model card
MATH-Vision (MathVision) 70.5% #24 of 42 Model card
MMMU-Pro 54.3% #62 of 72 Model card

Its launch post

The benchmarks the lab chose to headline, with the scores it gave.

Its system card

Every result in the longer documents the lab published with it. 9 of them aren't in the launch post.