Cognition releases SWE-1.7, a coding model trained with long-horizon RL
Original titleSWE-1.7: Frontier Intelligence at a Fraction of the Cost
AISummary
Cognition launched SWE-1.7, which it says reaches frontier-level coding performance at lower cost, trained from a Kimi K2.7 base. The post describes RL methods including top-p sampling replay to preserve entropy, compressed weight deltas across multi-cluster training, and self-compaction for rollouts up to six hours. SWE-1.7 is available in Devin via Cerebras at 1000 TPS.
AIWhy it matters
The post details entropy preservation, multi-cluster weight sync, and self-compaction, offering concrete RL training techniques for long-horizon coding agents to compare against one's own pipeline.
Source: Cognition Blog (Devin, Windsurf) · cognition.comPublished · added here