DeepSeek V4.1 Flash post-training is fully data-centric: synthetic multi-agent trajectories plus checkpoint merging
nrehiew_ · x · 2026-09-11
nrehiew's notes on DeepSeek V4.1 Flash's post-training:
- Data-centric approach: agent trajectories are, for the first time explicitly, inspired by real-world usage patterns from partners, with data generated synthetically by multiple agents in a system
- Checkpoint merging: checkpoints from runs with different scaffolds and configurations are merged, yielding (free) performance gains
- Philosophy shift: the post-training strategy is now entirely data-focused rather than training-algorithm research
Takeaway: DeepSeek's edge now comes from data recipes and engineering detail rather than novel training algorithms.
Related event: Leaked DeepSeek V4.1 Flash Tech Report Reveals KV Cache-Obsessed Flagship(44 posts)→
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