long context benchmark
MMLongBench-128K
MMLongBench-128K evaluates multimodal long-context understanding at a 128K token context length, testing how well vision-language models reason over very long mixed text and image inputs.
Updated Aug 11, 2026
Models2
Model coverage2
MetricScore
EvidenceB
MMLongBench-128K Ranking
Higher score ranks better on this benchmark.
| 1 | BY | 78.3% | 100.0% | 2 | C | |
| 2 | BY | 76.9% | 0.0% | 2 | C |
MMLongBench-128K Score Distribution
A closer view of the leading scores on this benchmark.
MMLongBench-128K Highlights
The leading models and scores on this benchmark.
What is MMLongBench-128K?
What MMLongBench-128K measures and how its scores work.
MMLongBench-128K evaluates multimodal long-context understanding at a 128K token context length, testing how well vision-language models reason over very long mixed text and image inputs.
Scores are shown in ratio. This benchmark is not independently verified and has an evidence level of B.
- Family
- MMLongBench-128K
- Modality
- multimodal
- Primary category
- long context
- Score direction
- higher
- LLMBoard eligible
- No
- Evaluation key
- mmlongbench-128k|llm-stats-current
Benchmark scores retain their original unit. Overall score eligibility is shown separately.
FAQ
Common questions about MMLongBench-128K.
Which model scores highest on MMLongBench-128K?
Seed 2.1 Pro is currently ranked first with 78.3%.
What does MMLongBench-128K measure?
MMLongBench-128K evaluates multimodal long-context understanding at a 128K token context length, testing how well vision-language models reason over very long mixed text and image inputs.
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.