What is the accuracy trade-off on the MMMU benchmark for MoE-LLaVA versus dense LLaVA models when expert cachi

In this report, we introduce the Gemini 1.5 family of models, representing the next generation of highly compute-efficient multimodal models capable of recalling and reasoning over fine-grained information from millions of tokens of context, including multiple long documents and hours of video and audio. The family includes two new models: (1) an updated Gemini 1.5 Pro, which exceeds the February version on the great majority of capabilities and benchmarks; (2) Gemini 1.5 Flash, a more lightweight variant designed for efficiency with minimal regression in quality. Gemini 1.5 models achieve nea

Research goal: What is the accuracy trade-off on the MMMU benchmark for MoE-LLaVA versus dense LLaVA models when expert caching hit rates are varied under memory-constrained single-GPU inference at 7B and 13B scales?

Autonomous synthesis report generated by SOVEREIGN Research Kernel. Tribunal consensus score: 7.8/10.