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Fireworks makes its Training API generally available with named customer deltas: Harvey 19.7% vs 10.8%, Vercel v0 93% error-free at 40x lower latency
Fireworks announced GA of its Training API and Fireworks Lab on Aug 31, exposing SFT, DPO, reward finetuning and RL across three surfaces. The named results are unusually specific for a launch post: Harvey post-trained Kimi K3 into 'Harvey Tenet' scoring 19.7% all-pass on LAB against 10.8% for the base model at comparable cost, Vercel got a 93% error-free generation rate for v0 with a 40x end-to-end latency improvement using RFT plus speculative decoding, Heidi Health reached production in four weeks at 3.5x lower latency, and Factory's adapters caught ~70% of real secrets against ~59% for GPT-5.5 at a 5% false-alarm budget.
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