Mercor (@mercor

Mercor

286 posts

Mercor

@mercor_ai

We connect human expertise with leading AI labs and enterprises to train frontier models.

San Francisco

Joined April 2021

Pinned
Mercor
@mercor_ai
Jun 9
Claude Fable 5 takes #1 on APEX-SWE: 65.5% Pass@1 overall. It scores ~18pp higher than Opus 4.8. We tested @claudeai Fable 5 on APEX-SWE which measures whether AI models can do real software engineering work. Fable 5 tops our two APEX-SWE categories: - Integration: 61.3% -
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Mercor reposted
Brendan (can/do)
@BrendanFoody
6h
Claude Fable 5's progress in coding (APEX SWE) dramatically outpaced progress in other domains like finance, law, and consulting (APEX Agents). The top reason for the fast progress in coding is that we have GitHub, with over 28 million repositories of human-written code. We're
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Mercor
@mercor_ai
7h
Replying to @mercor_ai
Sign up for the APEX-Agents newsletter: mercor.com/apex Download the APEX-Agents dataset: huggingface.co/datasets/merco… Open-source infra + eval service (Archipelago): github.com/Mercor-Intelli… Technical report: arxiv.org/abs/2601.14242
APEX Benchmarks: The AI Productivity Index | Mercor
From mercor.com
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Mercor
@mercor_ai
7h
Replying to @mercor_ai
APEX-Agents domain breakdown for Claude Fable 5 (Max), Pass@1: Corporate Law: 40.9% (1st) Investment Banking: 47.7% (2nd) Management Consulting: 46.4% (2nd) With 4 runs, Fable solved 246 of 480 tasks, including 8 that no other model has solved. All 8 tasks are in Law,
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Mercor
@mercor_ai
7h
Claude Fable 5 places 2nd on APEX-Agents leaderboard @claudeai Fable 5 (Max) scores 45.0% Pass@1, behind Gemini 3.5 Flash (49.6%) and ahead of Claude Opus 4.8 (42.5%). Fable 5 reached 2nd overall while spending far fewer tokens. It used 70% less than Gemini 3.5 Flash and 37%
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Mercor reposted
MTS
@MTSlive
Jun 9
What are the top AI researchers saying about the future of human work? @BrendanFoody, co-founder and CEO of Mercor: "People often have this misconception that we won't need data in three years because we'll have super intelligence... AI better than humans at absolutely
00:00
Brendan (can/do)
@BrendanFoody
May 6
Mercor's average pay rate just surpassed $100 / hour. We're mobilizing tens of thousands of top software engineers, bankers, lawyers, and doctors to build the next generation of AI models. Every top economist believes that there will be more jobs in 10 years than there are
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Mercor reposted
Brendan (can/do)
@BrendanFoody
Jun 9
Claude Fable 5's progress on hillclimbing APEX-SWE is accelerating exponentially. While other models focus on reasoning over a code base, Claude has unparalleled results at reasoning over Linear tickets, observability logs, Slack messages, and Google Drive files alongside the
Mercor
@mercor_ai
Jun 9
Claude Fable 5 takes #1 on APEX-SWE: 65.5% Pass@1 overall. It scores ~18pp higher than Opus 4.8. We tested @claudeai Fable 5 on APEX-SWE which measures whether AI models can do real software engineering work. Fable 5 tops our two APEX-SWE categories: - Integration: 61.3% -
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Mercor
@mercor_ai
Jun 9
Replying to @mercor_ai
The pattern is higher leverage, not more effort. Fable 5 spends less of its budget searching and more validating, testing as it goes and catching issues during edits rather than after. It rewrites less too: 3.8 edit iterations versus 6.0 for Opus 4.8. The result: 10% fewer
APEX-SWE: AI Rankings for Software Engineering | Mercor
From mercor.com
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Mercor
@mercor_ai
Jun 9
Replying to @mercor_ai
What changed is how Fable 5 works. Where Opus 4.8 reads code one file at a time, Fable 5 investigates in parallel: 10.4 parallel tool calls per trajectory versus zero for Opus 4.8. It searches code, reads files, runs tests, and queries logs at once, instead of chasing one
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Mercor reposted
Brendan (can/do)
@BrendanFoody
Jun 6
AI progress requires (1) compute, (2) algorithms, and (3) data. - The leading compute company is worth $5 trillion. - The leading model company is worth $1 trillion. - @mercor_ai is the leading data company and is currently valued orders of magnitude lower. There's an
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Mercor reposted
Brendan (can/do)
@BrendanFoody
Jun 4
I told @HarryStebbings on @20vcFund that @mercor_ai now spends more on tokens for our internal agents than we do on headcount. In a few years, every enterprise will too. We already see that the companies pulling ahead are running like AI labs: an eval for every workflow, agents
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Mercor
@mercor_ai
Jun 3
We worked with @trajectorylabs to run their SDPO++ algorithm on APEX-Agents and see what it could do with real production data. Pass rates went from 5% to 25% on GPT-OSS-120B, and the curve is still climbing. Read more about our work together in their blog post below.
Trajectory
@trajectorylabs
Jun 2
5 Days of Trajectory 🏹Day 5: Scaling SDPO to Agentic Tasks Continual learning means you must train on data from production. But production gives you one example per task. A user makes a request once. You get one trajectory, not a batch. However, current RL algorithms
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Mercor reposted
Harry Stebbings
@HarryStebbings
Jun 1
Companies will spend more on tokens than they do salaries very soon. Application layer companies have no defensibility, the model is the product. Hiring researchers will cost you tens of millions of dollars today. Everything you think you know about defensibility, token spend,
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