Applied research lab curating data solutions to accelerate foundation model development.
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Kimi K3 ranks #1 on @AfterQuery's SpreadsheetBench 2, surpassing Claude Fable 5.
An open weight model now outperforms all closed-sourced models. Read more in the Kimi K3 blog and SpreadsheetBench 2 paper linked below.
Congrats to the @kimi_moonshot team on the incredible model!
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AfterQuery retweeted
@AfterQuery is hosting a panel with @GoldmanSachs during SF Tech Week to discuss the frontier of finance!
RSVP in the replies👇
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AfterQuery retweeted
People still underestimate how large the data market will become.
Better models do not reduce demand for data. They increase the number of useful things models can learn.
The frontier keeps moving, so the data has to keep getting harder.
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AfterQuery retweeted
last nights spread for @AfterQuery‘s 3rd poker night
now hosting these biweekly♠️
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AfterQuery retweeted
If you're free tomorrow night, @AfterQuery is hosting a researcher poker night tmr @ 8:30pm
rsvp for deets👇
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AfterQuery retweeted
The @AfterQuery post-training team helped patch a critical LoRA weight-loading bug in SkyRL today.
Check out our PR in the replies.
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AfterQuery retweeted
Gemini 3.8 set SOTA on DeepSWE at 9am. Muse Spark 1.3 took it back at 12:30pm.
Incredible work from the MSL coding team.
Muse Spark 1.3 is rolling out today with frontier performance almost too cheap to meter. This is the biggest jump we've made so far on coding and agentic work. Try it in Muse Code and our API.
Next up 🍉 and Muse Spark open weights releases coming soon.
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AfterQuery retweeted
Legal and finance are two of the highest-impact domains to crack.
3.8 Flash now leads both Harvey’s Legal Agent Benchmark and Vals Finance Agent v2. Huge congrats to GDM ⚡️
Introducing Gemini 3.8 Flash, another jump in Gemini's agentic + coding capabilities, and our 3rd updated Flash model in only 6 weeks...
This model has been a ton of fun to work with, excited to see what you all think!
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AfterQuery retweeted
New @nvidia DGX Spark just came in.
Hyped to put it to work and eliminate inference costs on a few of my workflows.
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Congratulations to the @motif_tech team on the release of Motif 3!
AfterQuery is proud to have served as the sole data partner on this model.
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This is a historic moment for Korean sovereign AI and the open weights ecosystem writ large. We look forward to supporting Motif and the Korean AI ecosystem as they push the frontier of open intelligence.
Motif 3 leads its comparison set on τ³-Banking, and posts 94.7 on τ²-Bench Telecom, 74.9 on Terminal-Bench 2.1, and 76.2 on SWE-bench Verified. It’s also great to see @nvidia's open foundation put to use here - Motif 3's post-training was done via NeMo-RL.
In a world where it’s easy to assume that the AI race is already won, the team at Motif is proof that the field is open, and we’re still at the starting line.
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AfterQuery retweeted
Congrats to the @thinkymachines team on the release of Inkling-Small :bufo-yay:
Today, we are releasing Inkling-Small.
Inkling-Small achieves comparable performance to Inkling at a quarter of its size. It features 276B total parameters, 12B active. We are making the full weights available.
thinkingmachines.ai/news/ink…
Fine-tune it on Tinker today, or chat with it in text, image, and audio on Tinker Playground.
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AfterQuery retweeted
hosting poker night at the @AfterQuery office this Thursday @ 8:30 pm
join us 👇
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Congrats to the @WeAreLegora team on the release of the Legora BAR, a benchmark for agentic legal work built on 5,161 real law firm cases across 28 practice areas!
@AfterQuery helped QA the benchmark with Legora. Proud to work with their team on measuring the frontier of agentic legal work.
Link to the full blog post in the replies.
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AfterQuery retweeted
Huge congrats to the @MicrosoftAI team on MAI-Cyber-1-Flash and 96% on CyberGym.
Super hyped to see Microsoft keep pushing the frontier.
Big news! Our new MAI-Cyber-1-Flash model combined with MDASH, our multi agent security harness, delivers 96% on the CyberGym benchmark, 12pts above Mythos, at HALF the cost.
Proud of the team. More details in THREAD:
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AfterQuery retweeted
@AfterQuery is hiring SWEs!
In 14 months, AfterQuery has surpassed $100M in revenue run rate and works with all leading AI labs to build the data and systems that models train on.
Our founding eng team joined from firms like Citadel Securities, Palantir, and Meta, and we're hiring more.
Apply in the link below or drop your email.
Refer a successful hire and earn $10K.
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AfterQuery retweeted
To the researchers impacted by the Amazon AGI layoffs: @AfterQuery is hiring post-training researchers.
We work on data solutions that support all frontier labs. If you’ve thought deeply about what improves model capability or behavior, we want to talk. DMs open.
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Join our team.
The best operators at @AfterQuery chose us over Wall Street, and we’re hiring more of them.
They’re business or CS majors who left Goldman, JPMorgan, and Jane Street because they believe this is the most consequential work they could be doing right now.
If this is you, apply at the link in the comments or leave your email below.
Know someone cracked? Tag them - we pay $10,000 for successful referrals.
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AfterQuery retweeted
Congrats @mgalle on the new model🎉
Congrats to the @PoolsideAI team on Laguna S 2.1!
With thinking enabled, Poolside reports scoring 70.2% on Terminal-Bench 2.1.
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