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On September 22, 2026, Fireworks AI released the Specialized Intelligence Index (SII), which brings together the performance of open, closed-source, and specialized models on domain-specific benchmarks, initially covering seven domains: healthcare, legal, cybersecurity, finance, customer service, productivity, and software. According to the official description, each benchmark was designed by practitioners in the field, such as Harvey's Legal Agent Benchmark, Sierra's τ-Banking and τ-Voice, and Datacurve's DeepSWE v1.1. SII does not weight or average results across domains; it retains only benchmark- and domain-level scores and provides comparison views of score versus cost and score versus duration. Each benchmark is annotated with its reproducible scope, and new frontier models must pass a production deployability screening before being included. Fireworks also accepts partner submissions, with partners providing tasks and data in a Harbor-compatible format; Fireworks runs the evaluations free of charge and publishes scores with the partner's consent. There have been no further developments so far.
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Fireworks Research Releases Ember-1: A Token-Saving Specialized Model Based on Kimi K3Developments
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Sep 23
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Fireworks Research Releases Ember-1: A Token-Saving Specialized Model Based on Kimi K3
Fireworks Research has released Ember-1, a specialized model trained on Kimi K3 that reduces token consumption by about 40% while maintaining equivalent quality. The company says that across 7 benchmarks and production traffic from two customers, K3's reasoning process can be shortened by 35–50% without any drop in accuracy; on Bedside Bench, Ember-1 sits on the Pareto frontier for cost and task completion. The model is available on Serverless as a Research Preview, offered alongside the base Kimi K3, with training support on enterprises' own data also opened up.
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Sep 22
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