@ClementDelangue: Routing and post-training open-source models won't only give you more accurate systems but also meaningfully faster and…

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Summary

Discussion on how routing and post-training open-source models can outperform frontier models in accuracy, speed, and cost, with Harvey's partnership with Fireworks AI demonstrating hybrid legal agents beating frontier models on quality and cost.

Routing and post-training open-source models won't only give you more accurate systems but also meaningfully faster and cheaper systems as most companies are currently learning (in addition to giving you more control and privacy). The idea that a "frontier" model (by frontier we mean is slightly more accurate on a few very limited benchmarks) will be better for all domains, all tasks, all setups just doesn't hold up! It's marketing for making you pay more!
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Cached at: 06/03/26, 07:54 PM

Routing and post-training open-source models won’t only give you more accurate systems but also meaningfully faster and cheaper systems as most companies are currently learning (in addition to giving you more control and privacy).

The idea that a “frontier” model (by frontier we mean is slightly more accurate on a few very limited benchmarks) will be better for all domains, all tasks, all setups just doesn’t hold up! It’s marketing for making you pay more!

Harvey (@harvey): We partnered with @FireworksAI_HQ to train open-source models for legal. Here’s what we found:

  1. Hybrid legal agents can beat frontier models on quality and cost by routing selectively to a frontier advisor.

We tested a hybrid setup where GLM 5.1 served as the primary worker,

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