DeepSeek V4 Flash Distilled Dataset: 5K Synthetic Reasoning Traces

5,099 unique reasoning traces designed to mirror the step-by-step thinking style of the DeepSeek V4 Flash model. The dataset was generated entirely with template-based parameterized generation by author gss1147 and was last updated on May 25, 2026.

Use Cases

• Fine-tune language models for step-by-step problem-solving based on the structured reasoning traces.
• Benchmark model reasoning capabilities on mathematical problems based on the described algebra subdomain.
• Study the patterns of synthetic reasoning generation based on the template-based creation method.
• Train models to generate intermediate reasoning steps based on the 'reasoning_trace' field structure.

Strengths

• Contains 5,099 unique reasoning traces, providing a substantial corpus for training.
• Explicitly designed to mirror the reasoning style of a specific, advanced model (DeepSeek V4 Flash).
• Generated without LLM API calls, suggesting a reproducible and potentially lower-cost methodology.

Limitations

• Column-level documentation is absent; field semantics must be inferred after download.
• Row count is unknown beyond the 5,099 figure, which may limit suitability assessment for large-scale training.
• Data may reflect bias inherent to the synthetic generation templates and the source model's style.

Provenance

Source

huggingface

Collection Method

Template-based parameterized generation (synthetic).

Freshness

Last updated 2026-05-25 01:30:43; freshness should be verified.