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Fireworks AI launches Tenet model for legal work, boosting performance without cost increase · 5 sources…

By PulseAugur Editorial · [5 sources] ·

Fireworks AI has introduced Tenet, a new model developed in close collaboration with Harvey for long-horizon legal work. Tenet, post-trained from a Kimi K3 base model, demonstrates significant performance gains on legal benchmarks like the Legal Agent Benchmark (LAB), improving the all-pass rate from 10.8% to 19.7%. This advancement was achieved without a cost penalty, maintaining a similar cost per task to its base model while nearly doubling task completion. Tenet also shows generalized improvements on benchmarks it was not specifically trained on, including Apex Agents and Redline Bench, and maintains legal knowledge on benchmarks like LegalBench, CUAD, and MAUD. AI

IMPACT Enhances specialized AI capabilities for the legal sector, potentially improving efficiency in legal document analysis and deliverable generation.

RANK_REASON This is a product release from a company that provides inference infrastructure, not a frontier model lab.

Read on X — Fireworks (inference infra) →

AI-generated summary · Google Gemini · from 5 sources. How we write summaries →

Fireworks AI launches Tenet model for legal work, boosting performance without cost increase · 5 sources…

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This is a product release from a company that provides inference infrastructure, not a frontier model lab.
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5 independent sources
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model release, product
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COVERAGE [5]

  1. X — Fireworks (inference infra) TIER_1 English(EN) · FireworksAI_HQ ·

    Tenet came out of a close collaboration with @ItsJulioPereyra @nikogrupen @calvincongelado @gabepereyra: many base models, recipes, and data approaches; many ru

    Tenet came out of a close collaboration with @ItsJulioPereyra @nikogrupen @calvincongelado @gabepereyra: many base models, recipes, and data approaches; many runs, rollbacks, and harness revisions to reach this checkpoint. We’re so grateful for the partnership!

  2. X — Fireworks (inference infra) TIER_1 English(EN) · FireworksAI_HQ ·

    The performance came without a cost penalty: Tenet runs at $5.92 per LAB task vs $5.62 for base Kimi K3, effectively flat, while completing nearly twice as many

    The performance came without a cost penalty: Tenet runs at $5.92 per LAB task vs $5.62 for base Kimi K3, effectively flat, while completing nearly twice as many tasks. That comes from open-weight per-token pricing and reward shaping for token efficiency.

  3. X — Fireworks (inference infra) TIER_1 English(EN) · FireworksAI_HQ ·

    The gains generalize. On benchmarks Tenet never trained on, it improved on @mercor's Apex Agents and @crosbylegal's Redline Bench, the latter in a different har

    The gains generalize. On benchmarks Tenet never trained on, it improved on @mercor's Apex Agents and @crosbylegal's Redline Bench, the latter in a different harness entirely. And it showed no meaningful regression on legal knowledge benchmarks like LegalBench, CUAD and MAUD.

  4. X — Fireworks (inference infra) TIER_1 English(EN) · FireworksAI_HQ ·

    On LAB, Harvey's Legal Agent Benchmark, agents produce finished legal deliverables graded against dozens of criteria.

    On LAB, Harvey's Legal Agent Benchmark, agents produce finished legal deliverables graded against dozens of criteria. All-pass counts a task only if it clears them all. Tenet lifts all-pass from 10.8% to 19.7% over the Kimi K3 base, reaching state-of-the-art on LAB Contracts. h…

  5. X — Fireworks (inference infra) TIER_1 English(EN) · FireworksAI_HQ ·

    Recently @Harvey introduced Tenet, its first model, trained for long horizon legal work.

    Recently @Harvey introduced Tenet, its first model, trained for long horizon legal work. Harvey post-trained it from a Kimi K3 base in collaboration with Fireworks using async RL on our Training API. A thread on promising initial results for both performance and https://t.co/7J…

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