public benchmarks are saturated. every frontier model has trained against them, and the leaderboard tells you near nothing.
we built ours from inside ramp — code no model has seen, graded against the bar our engineers ship to.
every company running on AI needs its own.
In long agent loops, reasoning tokens get reused as context on every following turn.
Shorter reasoning means smaller contexts downstream, faster generations, and fewer retries.
K2.7 Code reduces that overhead without giving up quality, which lowers the real cost per…
Moonshot released K2.7 Code, the latest in their K2 line of coding models, and it's live on Fireworks Day 0, on serverless and the API.
It produces roughly 30% fewer reasoning tokens than K2.6 while scoring higher on Moonshot’s coding benchmarks.
For agentic coding work,…
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