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Steven Dillmann

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@StevenDillmann

Stanford, CA Joined January 2020
2K Following 2K Followers 509 Posts

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Steven Dillmann Verified account @StevenDillmann
We're releasing Terminal-Bench-Science: a benchmark for evaluating AI agents on research workflows across scientific domains.

An ongoing Stanford-led community effort, built by the team behind Terminal-Bench together with scientific domain experts at research institutions worldwide. v0.1 has 70 tasks. Claude Opus 5 solves only ~30%.

1/n 👇
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Steven Dillmann Verified account @StevenDillmann
Congrats to @bingran_bry & co. on FrontierPhysics 🎉⚛️

Another strong AI-for-science eval, this time for end-to-end physics research. Great to see more benchmarks built on real research workflows.
Xiangyi Li Verified account @xdotli 2d
Introducing FrontierPhysics - a benchmark evaluating agents for end-to-end physics research

Our core team from physics labs at Berkeley, Caltech, and Harvard recruited 42 physicists from 26 institutions. 28 of them published papers on Nature, Nature Physics, PRX, PRA*

1/7 🧵
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Steven Dillmann Verified account @StevenDillmann
Check out SIDERIUS by @Yue1650749 !
Yue Verified account @Yue1650749 Oct 30
Introducing SIDERIUS, an open-source AI Research IDE powered by agents, for scientists.

Division of labor: you bring the science, agents do the ML engineering. Step in anytime: advise, take over any step, or run end to end.

siderius.scitra.org
#AIforScience #OpenSource
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Steven Dillmann Verified account @StevenDillmann
Impressive Terminal-Bench-Science score by @GoogleDeepMind’s new Gemini 4 Carbon model 🤯
Logan Kilpatrick Verified account @OfficialLoganK Oct 28
Introducing Gemini 4 Carbon, it's a big jump over Argon which we released just 2 weeks ago.

Gemini 4 Carbon is SOTA on cyber, long horizon tasks, ranks #1 on Artificial Analysis V5, significantly improves on usability in domains like coding, and is more aligned.
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Steven Dillmann Verified account @StevenDillmann
Terminal-Bench-Science is now included in the Artificial Analysis Intelligence Index🔬

Congratulations to the team at @ArtificialAnlys for the release & thank you to @grmcameron @wmkeats @_micah_h for the fireside chat at yesterday’s launch event!
Artificial Analysis Verified account @ArtificialAnlys Oct 28
Announcing Artificial Analysis Intelligence Index v5, featuring 2 new benchmarks and 3 upgrades. For the first time, the majority of the Index is built on private datasets

The Artificial Analysis Intelligence Index is our composite measure of model capabilities across tasks reflecting real-world usage today. v5 is our biggest upgrade since v4 launched in January. With v5, 60% of the Index is now based on evaluations with private test sets or held-out answers.

Alongside Intelligence Index v5, we’re launching the Artificial Analysis Progress Index v1, which tracks model capability over time on one continuous scale.

New to the Intelligence Index:

➤ FrontierCode 2.0: Cognition's newly-launched private benchmark of real-world coding tasks, graded on whether a repository maintainer would merge the agent's change

➤ Terminal-Bench-Science: 70 agentic scientific research tasks, run in a terminal environment

Upgraded:

➤ HLE-Diamond (replacing Humanity's Last Exam): a refined 1,000-question version of Humanity's Last Exam, split evenly between reasoning and knowledge questions

➤ AA-Omniscience v1.1: An updated dataset with saturated and public set questions removed, new questions added, and ambiguous or erroneous questions revised

➤ CritPt v2: a private, 40-question hard subset of CritPt v2, revised by the CritPt authors and run with a code-execution tool

Staying in the Index: AA-Briefcase, AutomationBench-AA, GDP.pdf and Terminal-Bench 4.0

Removed from the Index: GDPval-AA v2.1, SciCode, and AA-LCR v1.1

Key results:

➤ Claude Opus 5.5 (max) leads at 58, ahead of GPT-6 Astra (max, 57) and GPT-6.1 Sol (max, 55): Anthropic and OpenAI hold the top five models. Gemini 4 Argon (high) is next at 50

➤ The open weights gap widens from 3 points to 12: Kimi K3.1 Pro (weights not yet released) is the top open weights model at 46. Among released weights, DeepSeek V4.1 Flash 1017 (max) and GLM-5.3 (max) lead at 32 - 26 points behind the leader and below Claude Haiku 5.5 (max, 36)

➤ Cost per task varies by more than 13x among the leading models: of the 10 highest-scoring models shown, GPT-6.1 Terra (max) is the cheapest at $0.96 per Intelligence Index task and Claude Fable 5.1 (max) the most expensive at $13.04
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