LLM training task (Anthropic)
Only in system cards
Agents optimize a CPU-only small language model training implementation. Scored by speedup.
In-house Anthropic evaluation. The tasks are not public.
Made by Anthropic Released May 2025 Machine learning engineering Tasks kept private Last in a system card Jul 2026
Last model added Jul 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
- Code A program or patch run against tests.
12
System cards report it, from 1 lab
No scores here yet
No lab, leaderboard or Epoch AI run has reported a score for LLM training task (Anthropic) yet.
Labs report it only in system cards
We read the headline results of 479 launch posts from 51 labs, and none of them list this benchmark. Some system cards do, below.
12 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.
| Date | Document | Score | As the document writes it | Section |
|---|---|---|---|---|
| 24 Jul 2026 | Claude Opus 5 system card | 68.5 | LLM training (easy), average speedup. New hard variant starting from optimized reference code 14.19x (Table 2.3.5.A) | AI R&D risk |
| 30 Jun 2026 | Claude Sonnet 5 system card | 26.5 | LLM training, average speedup 26.49x, fixed-CPU re-run methodology (Table 2.3.3.A) | AI R&D risk |
| 16 Apr 2026 | Claude Opus 4.7 system card | 40.8 | LLM training, average speedup 40.81x (Table 2.3.4.A) | AI R&D risk |
| 7 Apr 2026 | Claude Mythos Preview system card | 51.9 | LLM training, average speedup 51.91x (Table 2.3.3.A) | AI R&D risk |
| 17 Feb 2026 | Claude Sonnet 4.6 system card | 16.5 | LLM training, average best speedup 16.53x (6.3.3.4) | AI R&D risk |
| 5 Feb 2026 | Claude Opus 4.6 system card | 34 | LLM training, 34x speedup (8.3.3.4) | AI R&D risk |
| 24 Nov 2025 | Claude Opus 4.5 system card | 16.5 | LLM training, 16.53x speedup (7.3.2.4) | AI R&D risk |
| 29 Sep 2025 | Claude Sonnet 4.5 system card | 5.5 | LLM training, average best speedup 5.5x, threshold 4x (9.3.3.4) | AI R&D risk |
| 5 Aug 2025 | Claude Opus 4.1 system card addendum | 2.84 | LLM training optimization, average best speedup 2.837x (6.4.1) | AI R&D risk |
| 22 May 2025 | Claude Sonnet 4 system card | 1.88 | LLM training, average best speedup 1.875x (7.3.3.4) | AI R&D risk |
| 22 May 2025 | Claude Opus 4 system card | 2.99 | LLM training, average best speedup 2.993x (7.3.3.4) | AI R&D risk |
| 24 Feb 2025 | Claude 3.7 Sonnet system card | Internal AI Research Evaluation Suite, AIRD Fast Training, distribution of maximum training speedups, chart without printed average. One run peaked above 7x then broke, reference about 4x (Figure 22) | AI R&D risk |
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