Markdown source

Agents at Scale: Inside MiniMax's Model and the Infrastructure Behind It

Conference Context

Session 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

Media Evidence

Minimax M2: Building the #1 Open Model – Olive Song, MiniMax (speaker-match related prior/adjacent AI Engineer video; captions: English auto-captions).

Evidence Graph

This evidence graph is generated from currently linked source material: official schedule text, related video pages, cached transcripts, visible slide text, dense/reconstructed slide pages, and AI slide-classification audits.

Media Signals

Agent Reading Notes

Use these signals to refine the synopsis, topic links, people/company context, and method notes. If a source is a related external video rather than an exact official recording, keep it framed as supporting evidence.

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

Supporting Slides

Slide Evidence

Synthesis

Synthesized Breakdown

Agents at Scale: Inside MiniMax's Model and the Infrastructure Behind It ## Conference 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 - Track: Posttraining & Midtraining - Room: Track 9 - Session type: session - Status: confirmed ## Session 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 ## Media Evidence Minimax M2: Building the #1 Open Model – Olive Song, MiniMax (speaker-match related prior/adjacent AI Engineer video; captions: English auto-captions). - Source video: youtube-lY1iFbDPRlw - Slide deck: Dense Slides: Minimax M2: Building the #1 Open Model – Olive Song, MiniMax — 5 visible slide image(s); 5 HTML recreation(s). slide-001.jpg slide-002.jpg slide-003.jpg - Additional slide evidence: Slides: Minimax M2: Building the #1 Open Model – Olive Song, MiniMax, Reconstructed Slides: Minimax M2: Building the #1 Open Model – Olive Song, MiniMax - Slide-derived themes for youtube-lY1iFbDPRlw: excel, speech, music, users, globally, olive, song, senior.

Speaker And Company Context

Topics Covered

Derived Links And Source Material

Novel Concepts / Clever Methods

Evidence Boundary

This synthesis is based on the official schedule and linked source pages. It should be revisited when exact session recordings or transcript-backed secondary sources are available.