Cognition's SWE-2 achieves 92.8 on Terminal-Bench 2.1

2.8T total params, 104B active per token (MoE) - the Kimi K3 base with Cognition’s post-training on top, and the first time Cognition has scaled RL into the multi-trillion-parameter regime. The base had already been RL-heavy for agentic coding; Cognition’s pass added another 5 to 6 points on most benchmarks.

Benchmarks (Cognition self-reported): FrontierCode 1.1 Main 50.0, DeepSWE 1.1 73.0, Terminal-Bench 2.1 92.8, Terminal-Bench 4.0 27.3. The headline: 50.0 on FrontierCode is one point behind Claude Fable 5.1 (50.9) and 3.3 behind GPT-6 Astra (53.3) - at a claimed 64% lower cost than Fable 5.1 and a quarter of Astra’s. Terminal-Bench 2.1 is the highest number in the published table. The soft spot is Terminal-Bench 4.0, where SWE-2’s 27.3 trails Fable 5.1 (55.8) and GPT-6 Astra (57.9) by a wide margin - long-horizon agentic work is where the gap to the frontier still lives.