Mercor ✓
@mercor · San Francisco · joined 14 Apr 2021
Organizing human intelligence to power the AI economy.
23 415Followers
31Following
396Posts total
142.8KViews on collected posts
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GPT-6 Astra debuts on APEX-Agents at #1 on the leaderboard.
🥇 62.4% Mean score (#1)
🥈 46.7% Pass@1 (#2)
It leads Fable 5.1 by 0.4 points on mean score and trails it by 0.8 on Pass@1.
APEX-Agents runs long-horizon tasks written by bankers, consultants, and corporate lawyers htt
22.2K views · 255 likes
· 22 reposts · 7 replies
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Data is the most important ingredient in post-training.
The Mercor Research team focuses on making every hour of expert work yield the most model improvement, through better learning algorithms for knowledge work and automated, domain-specific post-training.
We're also
11.8K views · 95 likes
· 8 reposts · 2 replies
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@mercor @AnthropicAI @claudeai When are we getting Eddice?
https://t.co/ojKN7n16gF
69 views · 0 likes
· 0 reposts · 0 replies
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@mercor @AnthropicAI @claudeai Big congratulations to everyone at @AnthropicAI who contributed to releasing a new SOTA model on APEX-Agents.
119 views · 0 likes
· 0 reposts · 0 replies
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Fable 5.1 debuts at #2 on the APEX-SWE leaderboard, within the confidence band of first place.
It’s also the new leader for Integration tasks.
Overall: 63.6% (#2)
Integration: 68.1% (#1)
Observability: 59.0% (#2)
Congratulations to @AnthropicAI @claudeai. https://t.co/WGq5syM
6.8K views · 39 likes
· 3 reposts · 3 replies
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Fable 5.1 sweeps all three APEX-Agents domains on Pass@1.
📊Management consulting: 52.2% (#1)
💰Investment banking: 48.3% (#1)
🏛️Corporate law: 41.9% (#1)
The model demonstrates significant capability for agentic coding, long-running agentic workflows, and knowledge work. https:/
13.6K views · 100 likes
· 5 reposts · 4 replies
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Claude Fable 5.1 debuts as the new leader on APEX-Agents and #2 on APEX-SWE.
APEX-Agents:
🥇62.0% Mean score (#1)
🥇47.5% Pass@1 (#1)
APEX-SWE:
🥈63.6% Pass@1 (#2)
Congratulations to @AnthropicAI @claudeai. https://t.co/Gkj3cWgkTQ
37.1K views · 31 likes
· 2 reposts · 8 replies
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@mercor I present to you, TRACE-Eval. I don't want to build another benchmark that tells us whether an agent passed once. I want to build the benchmark that tells us whether we can trust the agent after the repository changes.
83 views · 2 likes
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@mercor the reason most ai benchmarks focus on toy problems is because they're easier to quantify. a professional-quality workload for frontier ai would blow those results wide open, but nobody wants that kind of transparency
83 views · 0 likes
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@mercor “We’re crowd sourcing ideas but we’ll pay u for it”
446 views · 5 likes
· 0 reposts · 2 replies
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Today we're introducing the Mercor Research Fellowship.
We're funding a small group of people to build a new APEX benchmark, the definitive measure of frontier AI on professional-quality work.
Applications are now open: https://t.co/he7gBYUFMG https://t.co/KDche7rkT4
50.4K views · 169 likes
· 10 reposts · 8 replies
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Against accounts of the same size
11 posts from the last 90 days, next to the 10K–100K follower range. shown widely, but few of those viewers react.
Median views6 850this account924median for 10K–100K
Reach, %29.25%this account3.62%median for 10K–100K
Engagement, %0.67%this account1.52%median for 10K–100K
| Metric | This account | Median for 10K–100K | Ratio |
|---|---|---|---|
| Median views per post | 6 850 | 924 | 7.41× |
| Reach (views ÷ followers) | 29.25% | 3.62% | 8.08× |
| Engagement rate | 0.67% | 1.52% | 0.44× |
Others in this range → Compare with another account → How these benchmarks are built →
Growth & engagement
How the posts we collected actually performed: views and reaction rate post by post, what the audience did with them, and where the follower count goes.
Views per post
50.4K26 Aug
446
83
8327 Aug
37.1K1 Sep
13.6K
6.8K
119
69
11.8K
22.2K3 Sep
Last 11 collected posts, oldest on the left. The scale is logarithmic: one post can outrun the rest a hundred times over.
Engagement rate per post
0.37%26 Aug
1.57%
0.00%
2.41%27 Aug
0.11%1 Sep
0.82%
0.67%
0.00%
0.00%
0.90%
1.29%3 Sep
Reactions — likes, reposts, replies and quotes — divided by views. Median for 10K–100K accounts is 1.52%.
What the audience does
Likes64.3%696 in total
Reposts4.6%50 in total
Replies3.1%34 in total
Quotes0.7%8 in total
Bookmarks27.2%294 in total
Share of every reaction we collected for this account. Replies mean argument, reposts mean endorsement, bookmarks mean the post was worth keeping.
The follower curve appears once this account has two daily snapshots — we take one a day, and this one is on its first.
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Frequently asked questions about @mercor
How many followers does @mercor have?
23 415 followers.
How many posts has @mercor published?
396 posts.
How do posts by @mercor perform?
Collected posts: 11. Views: 142 798. Likes: 696.