Claude Opus Mythos 5K is a synthetic supervised fine-tuning dataset designed to distill the capabilities of Anthropic's Claude Opus 4.8 and Claude Mythos Preview models. The dataset is intended for training open-weight models to approximate frontier-level performance in software engineering, agentic workflows, and defensive cybersecurity. It was created by WithinUsAI and last updated on June 6, 2026.
Use Cases
- Fine-tuning models for software engineering tasks based on the description of capabilities in that domain.
- Training models for agentic workflows based on the dataset's stated focus on agentic behavior.
- Developing models for complex reasoning tasks based on the dataset's design for reasoning style distillation.
- Training defensive cybersecurity models based on the specific mention of the Mythos set's focus.
- Distilling frontier-level AI performance into open-weight models based on the dataset's stated purpose.
Strengths
- Dataset is designed to distill capabilities from high-performance frontier models Claude Opus 4.8 and Claude Mythos Preview.
- Dataset is intended for multiple advanced domains: software engineering, agentic workflows, complex reasoning, and cybersecurity.
- Dataset was last updated on June 6, 2026, indicating recent maintenance.
Limitations
- Column-level documentation is absent; field semantics must be inferred after download.
- Row count is unknown, which may limit suitability assessment.
- Description metadata is limited; actual data quality requires manual inspection after download.
Provenance
- Source
- WithinUsAI
- Collection Method
- Synthetic generation for supervised fine-tuning.
- Freshness
- Last updated 2026-06-06 00:05:17