Kimi-K2.6-Reasoning-3300x-WandB

Kimi-K2.6-Reasoning-3300x-WandB is a W&B-only synthetic reasoning dataset generated with Kimi-K2.6 through Weights & Biases Inference.

This dataset is the pure W&B-generated subset from a larger planned 8,000-example Kimi reasoning distillation run. Generation stopped when the W&B quota limit was reached, and the completed accepted rows were audited, cleaned, and exported as a standalone dataset.

This release contains 3,303 accepted W&B-generated rows and uses 3300x as a rounded public release label.

Dataset Summary

Field	Value
Public release label	3300x
Actual rows	3,303
Teacher model	Kimi-K2.6
Teacher model ID	moonshotai/Kimi-K2.6
Generation backend	W&B Inference
Output format	<think>...</think> + final answer
SHA256 train.jsonl	9d8832e23f7d927a10cfb1b30d9a255a7836debd38003f290bf94622f4cc387f

Seed Data / Prompt Provenance

The seed prompts were sampled from Jackrong/GLM-5.1-Reasoning-1M-Cleaned, a large cleaned reasoning prompt corpus.

For this release, only the seed prompt text was used as the user-facing task. The original source outputs were not included in the public dataset and were not used as public target completions. Kimi-K2.6 generated new reasoning responses for the selected prompts.

The larger planned seed bank targeted 8,000 prompts across three source buckets:

Source bucket	Planned seed count
main	3,000
PHD-Science	2,500
Math	2,500

The W&B run completed 3,303 accepted examples before quota exhaustion. The completed subset has the following bucket distribution:

Source bucket	Rows
main	1,237
PHD-Science	1,034
Math	1,032

Domain Distribution

Domain	Rows
general	1,237
science	1,034
math	1,032

Backend and Release Scope

This is the W&B-only release. Every row in this dataset was generated through W&B Inference and has:

"generation_backend": "wandb_inference"

A separate mixed-backend continuation release may be published later using the completed W&B rows plus additional Ollama Cloud Kimi-K2.6 continuation rows. If released, that dataset will preserve backend metadata per row.

Schema

Each row contains exactly:

{
  "id": "...",
  "conversations": [
    {"from": "human", "value": "..."},
    {"from": "gpt", "value": "..."}
  ],
  "input": "...",
  "output": "<think>...reasoning...</think>\n\nfinal answer",
  "domain": "...",
  "meta": {...}
}

Columns

Column	Description
id	Unique row identifier
conversations	Chat-style SFT format with human/gpt turns
input	Original seed prompt / user task
output	Kimi-generated reasoning output in <think>...</think> format followed by the final answer
domain	Coarse domain label
meta	Generation metadata, source bucket info, backend, and settings

Generation Settings

{
  "max_tokens": 65536,
  "temperature": 0.6,
  "top_p": 0.95,
  "concurrency": 18
}

Validation

The exported dataset passed the following checks:

Check	Result
Raw rows	3,303
Clean rows	3,303
Dropped rows	0
Raw JSON parse errors	0
Row errors after sanitize	0
Row warnings after sanitize	0
Missing think blocks	0
Empty final answers	0
Raw teacher tags in public output	0
Rows changed during sanitization	1

Short final answers are allowed when the reasoning trace is valid. This matters for math/science examples where the correct final answer may be something like 5, 12, or 27.6122.

What Is Not Included

This dataset does not include:

• Original source dataset outputs as public completions
• Weave traces
• Private debugging logs
• Failed generations
• Rows from Ollama Cloud continuation
• Rows from other teacher models

Only accepted, cleaned, W&B-generated Kimi-K2.6 rows are included.

Intended Use

This dataset is intended for:

• supervised fine-tuning experiments
• reasoning-format SFT
• long-form synthetic reasoning research
• teacher-model distillation experiments
• comparison against other reasoning datasets

Limitations

This is a synthetic dataset and should be treated as generated training data, not ground truth. Outputs may contain mistakes, over-explanations, or reasoning paths that should be independently evaluated before high-stakes use.

The dataset was generated from a partial run because the W&B quota limit was reached. The public release label 3300x is rounded, while the exact row count is 3,303.

Reproducibility Notes

The exported train.jsonl file has the following checksum:

SHA256(train.jsonl): 9d8832e23f7d927a10cfb1b30d9a255a7836debd38003f290bf94622f4cc387f

This checksum can be used to verify that the downloaded file matches the audited upload.

Files

File	Description
train.jsonl	Main training dataset
generation_metadata.md	Generation settings and dataset metadata
validation_report.md	Audit and validation report