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Harvey and Fireworks AI launch Tenet model for legal work

By PulseAugur Editorial · [5 sources] ·

Fireworks AI has released Tenet, a new model developed in close collaboration with Harvey, specifically trained for long-horizon legal work. Tenet is post-trained from a Kimi K3 base model and demonstrates significant performance gains without a cost penalty, completing nearly twice as many tasks per LAB task compared to its base. The model shows generalized improvements across various benchmarks, including legal knowledge and agent performance, achieving state-of-the-art results on LAB Contracts. AI

IMPACT Sets a new benchmark for specialized legal AI models, potentially accelerating adoption in the legal tech sector.

RANK_REASON New model release from a recognized AI lab (Fireworks AI) with specific performance claims.

Read on X — Fireworks (inference infra) →

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

Harvey and Fireworks AI launch Tenet model for legal work

How we ranked this

Signal score
49 / 100
Composite score across the factors below. Higher = stronger signal that this story matters right now.
Newsworthiness bucket
Frontier Release
New model release from a recognized AI lab (Fireworks AI) with specific performance claims.
Source corroboration
5 independent sources
Strong cross-source corroboration — multiple independent publishers covered this within the clustering window.
Topics
model release, product
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AI-industry relevance
High
Clearly on-topic for AI-industry coverage.
Story freshness
Breaking (< 6h)
Fresh story with cross-source coverage still developing. Ranking may shift as more sources report.

Full methodology in our editorial standards.

COVERAGE [5]

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

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

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

    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. Promising initial results for both performance and cost-efficiency:🧵 https://t…

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