Benchmark Almanac

SMolInstruct

Intern-S1-Pro 74.8% leads since Feb 2026 Fading

Models solve 14 chemistry tasks such as name conversion, property prediction, molecule captioning, generation and reaction prediction. Each task uses its own metric on the test split.

It is an instruction-tuning dataset with a test split. Shanghai AI Lab Intern-S models report the test split as a benchmark.

Made by The Ohio State University (LlaSMol team) Released Feb 2024 Genomics and life sciences All tasks public Last in a launch post Feb 2026 , dropped before it saturated Last model added Mar 2026
Level
Expert Specialists with years of training, often over hours of work
Scored
Checked automatically A program checks the result against an answer key, unit tests or the expected final state.
Answers
Short answer A number, word or short string matched to a key.
2
Models scored in lab cards
2
Launch posts list it, from 1 lab
2
System cards report it, from 1 lab

Intern-S1-Pro leads with 74.8%

Best score per model as labs report them in their own cards. Labs pick their own settings, so these compare less cleanly than independent runs.

  1. 1 Intern-S1-Pro 74.8%
  2. 2 Intern-S1 51%
#ModelScoreSettingDateSource
1 Intern-S1-Pro 74.8% Feb 2026 Model card
2 Intern-S1 51% Jul 2025 Model card

2 models have held number one since its release in Feb 2024

Lab claims count from the day the card came out, independent runs from the model’s release.

Shanghai AI Lab
Lab claims Not tested since Mar 2026

Scores over time

All the scores we have, one dot each, so a model tested at several settings appears more than once.

Reported by the lab in its model card Best so far
0% 20% 40% 60% 80% 100% 2026 Near the ceiling (85%) Intern-S1-Pro Intern-S1 0% 20% 40% 60% 80% 100% 2026 Near the ceiling (85%) Intern-S1-Pro Intern-S1

Labs headline it less often now, last in Feb 2026

Launch posts from every lab that has listed it, one tick per post. Tall colored ticks include it, and short gray ones leave it out.

Shanghai AI Lab
DateLaunch postScoreAs the post writes it
2 Feb 2026 Intern-S1-Pro 74.8 SmolInstruct (Small Molecule)
24 Jul 2025 Intern-S1 51 SmolInstruct

2 system cards report it, from 1 lab

Besides launch posts, we read the system cards, model cards and technical reports labs publish with a release. They report far more, including safety and frontier-risk tests.

DateDocumentScoreAs the document writes itSection
26 Mar 2026 Intern-S1-Pro technical report 74.8 SmolInstruct, Small Molecule, non-thinking (Table 2) Capabilities
21 Aug 2025 Intern-S1 technical report 51 SmolInstruct, official test split (Table 3) Capabilities

More in Biology and chemistry

All 96 in Biology and chemistry
  • SUPERChem In use Models solve 500 expert-written chemistry reasoning problems, offered in multimodal and text-only forms. Expert solution paths also allow a reasoning path score. Tencent Hy4 preview 66.4%
  • GeneBench Pro In use Agents analyze messy simulated genomics and biology datasets to estimate a decision-relevant quantity across 129 problems. Scored automatically against known answers. GPT-6 Astra 37.1%
  • LifeSciBench In use Models complete 750 expert-written life science research tasks, often with attached figures, tables, or sequence files. Graded against expert rubrics as score and pass rate. GPT-6 Astra 60.3%
  • MolecularIQ In use Models answer questions about molecular graphs, such as counting, indexing and constrained generation, and a symbolic checker verifies each answer. Intern-S2-397B 62.4%
  • TOMG-Bench In use Models generate molecules from natural language requests in three tasks: molecule editing, molecule optimization and customized generation. Each output is checked for validity and for meeting the requested properties. Intern-S2-397B 66.8%
  • BABE Fading Models reason from experimental results in peer-reviewed biology papers to draw conclusions, with causal and cross-scale inference. Seed2.0 Lite (0428) 57.9%