Agents at Scale: Inside MiniMax's Model and the Infrastructure Behind It
Official Schedule Context
- Date/time: 2026-06-30 · 2:50pm-3:10pm
- Track/room: Posttraining & Midtraining · Track 9
- Speaker(s): Olive Song, Dan Fu
- Session type/status: session · confirmed
Official Description
Olive Song (RL Lead, https://www.minimax.io/) and Dan Fu (VP of Kernels, https://www.together.ai/)
dig into the engineering behind one of the most widely used open model families in the agent
ecosystem: how MiniMax built the model for agentic workloads, and what it takes to serve it at
scale. Olive on the model side: The RL decisions behind long-context reasoning and tool use
What training for agentic behavior actually looks like in practice Dan on the infrastructure
side: Why agentic workloads break inference engines built for chat: prefill-heavy traffic, high
cache hit rates, long-context inputs The kernel-level optimizations built for MiniMax's workload
profile How the two teams collaborate on model launches and ongoing performance work
Related YouTube Video
Minimax M2: Building the #1 Open Model – Olive Song, MiniMax (speaker-match related prior/adjacent AI Engineer video; captions: English auto-captions).
Transcript Status
Related video transcript availability: English auto-captions. Treat this as supporting context, not a recording of this exact scheduled session unless later confirmed. Not fetched yet.
People
Notes
- Pending transcript synthesis when an official recording or confirmed matching video is available.
Supporting Slides
- youtube lY1iFbDPRlw slides — extracted from the related public AI Engineer video.
Slide Evidence
- Slide-only cropped deck: youtube lY1iFbDPRlw dense slides (5 viable slide images).
- Related slide/OCR pages:
- youtube lY1iFbDPRlw dense slides
- youtube lY1iFbDPRlw reconstructed slides
- youtube lY1iFbDPRlw slides
- Slide-derived terms:
minimax,research,open-weight,senior,engineer,tasks,minimax-m2,agentic,model,fast,coding,intetgence,everyene,olive,song,intelligence,real,experience