datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
DeepSeek-v4-Pro-AgentThis dataset was generated using teich by TeichAI
Prepare these datasets for supervised fine-tuning in just a few lines of code — see the Conversion section below.
DeepSeek v4 Pro Agent Traces
This directory contains raw agent trace files generated by teich.
All assistant responses were generated by deepseek/deepseek-v4-pro.
JSONL files: 4006
Training-ready tools
A complete configured tools schema snapshot is embedded in the collapsed section at the bottom of… See the full description on the dataset page: https://huggingface.co/datasets/TeichAI/DeepSeek-v4-Pro-Agent.DeepSeek-v4-Pro-AgentThis dataset was generated using teich by TeichAI
Prepare these datasets for supervised fine-tuning in just a few lines of code — see the Conversion section below.
DeepSeek v4 Pro Agent Traces
This directory contains raw agent trace files generated by teich.
All assistant responses were generated by deepseek/deepseek-v4-pro.
JSONL files: 4006
Training-ready tools
A complete configured tools schema snapshot is embedded in the collapsed section at the bottom of… See the full description on the dataset page: https://huggingface.co/datasets/ronaldcmz/DeepSeek-v4-Pro-Agent.DeepSeek-V4-Pro-Distilled-200K
DeepSeek‑V4‑Pro‑Distilled‑200K
High-quality Math & STEM reasoning distilled from DeepSeek‑V4‑Pro in Max mode
Reasoning traces · Proofs · Verification · Mathematics · Physics · Chemistry · Biology
Overview
DeepSeek‑V4‑Pro‑Distilled‑200K is a supervised fine-tuning collection of long-form mathematical and scientific reasoning. Its responses were generated with DeepSeek‑V4‑Pro in Max inference mode, then normalized into a compact conversational… See the full description on the dataset page: https://huggingface.co/datasets/Jackrong/DeepSeek-V4-Pro-Distilled-200K.DeepSeek-V4-Distill-8000x
🐳 DeepSeek-V4-Distill-8100x
Dataset Summary
DeepSeek-V4-Distill-8100x is a supervised fine-tuning dataset for reasoning-oriented distillation. The question prompts come from Jackrong/GLM-5.1-Reasoning-1M-Cleaned, and the answers were generated by the teacher model DeepSeek-V4-Flash.
After the cleaning process, the released train split contains 7,716 high-quality JSONL examples.
[!NOTE]
The answer pool was cleaned to remove real-time questions… See the full description on the dataset page: https://huggingface.co/datasets/Jackrong/DeepSeek-V4-Distill-8000x.DeepSeek-v4-Pro-AgentThis dataset was generated using teich by TeichAI
Prepare these datasets for supervised fine-tuning in just a few lines of code — see the Conversion section below.
DeepSeek v4 Pro Agent Traces
This directory contains raw agent trace files generated by teich.
All assistant responses were generated by deepseek/deepseek-v4-pro.
JSONL files: 4006
Training-ready tools
A complete configured tools schema snapshot is embedded in the collapsed section at the bottom of… See the full description on the dataset page: https://huggingface.co/datasets/hardcoremoore/DeepSeek-v4-Pro-Agent.DeepSeek-V4-Flash-0731-Teacher-Distillation-40513x
DeepSeek V4 Flash 0731 Teacher Distillation — 40,513 Retained Rows
Teacher-distillation corpus generated with
deepseek-ai/DeepSeek-V4-Flash-0731.
The original manifest contained 45,000 unique seeds.
Following generation, QC, retry-based repair, quarantine auditing,
and recovery adjudication, 40,513 rows were retained.
Composition
Bucket
Rows
Coding
5,601
Agentic
9,982
Cyber blue
13,000
Controlled cyber red
6,999
Tool use
4,931
Total
40,513… See the full description on the dataset page: https://huggingface.co/datasets/trjxter/DeepSeek-V4-Flash-0731-Teacher-Distillation-40513x.deepseek-v4-pro-max-distill-1k
Overeview
This dataset contains reasoning traces and final answers generated by DeepSeek-V4-Pro
(reasoning_effort=max, thinking.enabled=true) using prompts sampled from
Jackrong/GLM-5.1-Reasoning-1M-Cleaned.
Goal: just check quality
Update: The dataset have fully 1000 samples in 04/27/2026 cost only ~$5.46
Planning: try out another distill style such as roleplay
Why DeepSeek-V4-Pro instead of OpenAI / Anthropic?
For distillation, the teacher must expose… See the full description on the dataset page: https://huggingface.co/datasets/ansulev/deepseek-v4-pro-max-distill-1k.Deepseek-v4.1-CoTDatasets created by deepseek-ai/DeepSeek-V4.1-Flash.
You can use them to distill other models.
Ty!
DeepSeek-v4-Flash-ChatThis dataset was generated using teich by TeichAI
Prepare these datasets for supervised fine-tuning in just a few lines of code — see the Conversion section below.
Teich Test
This directory contains newline-delimited JSON training examples generated by teich.
All assistant responses were generated by deepseek/deepseek-v4-flash.
Rows: 6313
Format
Each file is newline-delimited JSON where every line is already a training example.
Chat-only datasets include messages… See the full description on the dataset page: https://huggingface.co/datasets/TeichAI/DeepSeek-v4-Flash-Chat.swebench-verified-deepseek-v4-flash-failure-analysis
SWE-bench Verified runs & failure analysis — DeepSeek-V4-flash (local) × mini-swe-agent
Per-instance analysis of SWE-bench Verified runs of a locally-served DeepSeek-V4-flash model
driven by mini-swe-agent, graded with the official
SWE-bench harness. Each instance carries the full agent trajectory, a readable transcript, the
submitted patch, the harness test output, deterministic metrics, and a hand-verified qualitative
root-cause diagnosis.
Current numbers (resolve rates… See the full description on the dataset page: https://huggingface.co/datasets/daaain/swebench-verified-deepseek-v4-flash-failure-analysis.DeepSeek-V4-Pro-Reasoning-8000x
DeepSeek-V4-Pro-Reasoning-8000x
This dataset contains 8,014 synthetic reasoning examples generated with DeepSeek V4 Pro through the DeepSeek API.
The release is branded as 8000x for readability, while the exact row count is 8,014.
This dataset is designed for supervised fine-tuning, reasoning distillation, and experimentation with long-form visible reasoning traces.
Dataset Summary
Release label: 8000x
Actual rows: 8,014
Teacher model: DeepSeek-V4-Pro… See the full description on the dataset page: https://huggingface.co/datasets/trjxter/DeepSeek-V4-Pro-Reasoning-8000x.DeepSeek_V4_Flash_distilled_dataset_5k
DeepSeek V4 Flash — Distilled Reasoning Dataset
A synthetic dataset of 5,099 unique reasoning traces designed to mirror the step-by-step thinking style of DeepSeek V4 Flash. Generated entirely with template-based parameterized generation (no LLM API calls).
Format
JSONL (one JSON object per line):
{
"id": "ds4f_math_000042",
"domain": "mathematics",
"subdomain": "algebra",
"difficulty": "easy",
"prompt": "Solve 3x + 7 = 22.",
"reasoning_trace":… See the full description on the dataset page: https://huggingface.co/datasets/WithinUsAI/DeepSeek_V4_Flash_distilled_dataset_5k.deepseek-v4-tiny-fidelity-root-v1
deepseek-v4 random CPU fixture root
A root fidelity dataset in hidden form, produced by engines/tools/hf_capture.py from malaiwah/deepseek-v4-tiny-random-bf16.
The cut
the final hidden state handed to lm_head -- after the text model's final norm and immediately before the head matmul -- captured as the head module's input via torch.nn.Module.register_forward_pre_hook; replay applies the head ONLY (no final norm at replay time: the capture already sits after it).… See the full description on the dataset page: https://huggingface.co/datasets/malaiwah/deepseek-v4-tiny-fidelity-root-v1.deepseek-v4-pro-math-cot-1k
DeepSeek V4 Pro Math CoT 1K
A small, high-signal supervised-fine-tuning (SFT) dataset of math reasoning traces. Problems were sampled from a Nemotron math problem set (originally sourced from StackExchange-Math and AoPS), answered by DeepSeek V4 Pro with thinking enabled at high reasoning effort, then independently reviewed by DeepSeek V4 Flash for correctness against the expected answer. Pathological reasoning traces (looping, run-away length, excessive Wait-style backtracking)… See the full description on the dataset page: https://huggingface.co/datasets/blythet/deepseek-v4-pro-math-cot-1k.deepseek-v41-flash-thinking-tooluseDeepSeek-V4-Distill-8000x
🐳 DeepSeek-V4-Distill-8100x
Dataset Summary
DeepSeek-V4-Distill-8100x is a supervised fine-tuning dataset for reasoning-oriented distillation. The question prompts come from Jackrong/GLM-5.1-Reasoning-1M-Cleaned, and the answers were generated by the teacher model DeepSeek-V4-Flash.
After the cleaning process, the released train split contains 7,716 high-quality JSONL examples.
[!NOTE]
The answer pool was cleaned to remove real-time questions… See the full description on the dataset page: https://huggingface.co/datasets/rampisipati/DeepSeek-V4-Distill-8000x.llm_timeline_deepseek_v4_flash-pi
Coding agent session traces
This dataset contains coding agent session traces collected while working on LLM Timeline web app using the prompt from coding-agent-bench-prompts
Deepseek-V4-Flash-11000x
Sherlock Thinking Alpha DeepSeek V4 Flash Distillation
Seed Prompt Dataset
Prompts are sourced from TeichAI/sherlock-thinking-alpha-11000x.
Model
Solutions and reasoning traces were generated with deepseek-ai/DeepSeek-V4-Flash.
DeepSeek-V4-Flash is part of the DeepSeek-V4 preview series. Its model card describes it as a Mixture-of-Experts language model with 284B total parameters, 13B activated parameters, and a 1M-token context length. The model repository is… See the full description on the dataset page: https://huggingface.co/datasets/SLoonker/Deepseek-V4-Flash-11000x.deepseek-v4-flash-swe-cot
DeepSeek-V4-Flash SWE Agent Trajectories (with raw chain-of-thought)
795 multi-turn software-engineering agent trajectories generated by
DeepSeek-V4-Flash-0731 at reasoning_effort=max, each one executed in a real
repository inside an isolated container and verified by running the repository's own
tests. 469 are verified-correct.
Every assistant turn preserves reasoning_content — the model's raw chain-of-thought,
not a summary. That is the point of this dataset: the DeepSeek API… See the full description on the dataset page: https://huggingface.co/datasets/blythet/deepseek-v4-flash-swe-cot.deepseek-v4-distill-8k
🐳 DeepSeek-V4-Distill-8100x
Dataset Summary
DeepSeek-V4-Distill-8100x is a supervised fine-tuning dataset for reasoning-oriented distillation. The question prompts come from Jackrong/GLM-5.1-Reasoning-1M-Cleaned, and the answers were generated by the teacher model DeepSeek-V4-Flash.
After the cleaning process, the released train split contains 7,716 high-quality JSONL examples.
[!NOTE]
The answer pool was cleaned to remove real-time questions… See the full description on the dataset page: https://huggingface.co/datasets/ansulev/deepseek-v4-distill-8k.DeepSeek-V4-Pro-distilled
DeepSeek-V4-Pro-distilled
17,670 general-purpose instruction-following examples distilled from DeepSeek-V4-Pro, fact-checked and patched using GPT-5.5 Thinking.
Pipeline
Distillation — responses generated via DeepSeek-V4-Pro API
Fact-checking — GPT-5.5 Thinking with web search reviewed all examples for factual errors and hallucinations
Format
Standard chat format, compatible with most SFT frameworks. Each row is one JSON object with a messages array:… See the full description on the dataset page: https://huggingface.co/datasets/Spakie/DeepSeek-V4-Pro-distilled.DeepSeek-V4-Pro-distill-V2
DeepSeek-V4-Pro-distill-V2
39,830 general-purpose chat and instruction-following examples distilled from DeepSeek-V4-Pro, fact-checked and patched using GPT-5.5 Thinking.
Pipeline
Distillation — responses generated via DeepSeek-V4-Pro API
Fact-checking — GPT-5.5 Thinking with web search inside Codex reviewed all examples for factual errors, hallucinations and syntax/runtime erros in code examples
Format
Standard chat format, compatible with most… See the full description on the dataset page: https://huggingface.co/datasets/Spakie/DeepSeek-V4-Pro-distill-V2.Deepseek-v4-Distill-TR-CoT-1k
Deepseek-v4-Distill-TR-CoT-1k
Deepseek-v4-Distill-TR-CoT-1k, Türkçe Yapay Zeka modellerinin akıl yürütme (Reasoning / Chain-of-Thought) ve problem çözme kabiliyetlerini artırmak amacıyla hazırlanmış 1,007 adet yüksek kaliteli veri örneğinden oluşan Türkçe SFT (Supervised Fine-Tuning) veri setidir.
Veri seti, açık kaynak ekosistemindeki Jackrong/DeepSeek-V4-Distill-8000x veri setinden seçilen 1007 örneğin qwen 3.8 27B modeli kullanılarak Türkçeye çevrilmesiyle oluşturulmuştur.… See the full description on the dataset page: https://huggingface.co/datasets/WrittenWithRust/Deepseek-v4-Distill-TR-CoT-1k.deepseek-v4-pro-pi-reasoning-sample-traces
DeepSeek V4 Pro Pi Reasoning Sample Traces
This dataset contains a compact sample of successful DeepSeek V4 Pro teacher trajectories for Pi-style reasoning and tool-use workflows.
It includes selected pass-only traces from these task providers:
abcbench
aider
autocodebench
bfcl
swebench
swtbench
termigen
Format
Each row contains:
id: stable sample id
segments: Qwen-style template-free supervised segments
label=false segments are context only
label=true segments… See the full description on the dataset page: https://huggingface.co/datasets/bytkim/deepseek-v4-pro-pi-reasoning-sample-traces.DeepSeek-V4-Distill-8000x
🐳 DeepSeek-V4-Distill-8100x
Dataset Summary
DeepSeek-V4-Distill-8100x is a supervised fine-tuning dataset for reasoning-oriented distillation. The question prompts come from Jackrong/GLM-5.1-Reasoning-1M-Cleaned, and the answers were generated by the teacher model DeepSeek-V4-Flash.
After the cleaning process, the released train split contains 7,716 high-quality JSONL examples.
[!NOTE]
The answer pool was cleaned to remove real-time questions… See the full description on the dataset page: https://huggingface.co/datasets/Bas95/DeepSeek-V4-Distill-8000x.kanitakorn-deepseek-v45-v44-openthaieval-bridge-mix
Kanitakorn v45 v44 + OpenThaiEval bridge mix
Train-ready SFT mix for a non-Thai-base DeepSeek/Qwen-style <=14B candidate.
Delta from v44:
reuses all v44 normalized MCQ replay and identity rows unchanged
adds locked, verified synthetic OpenThaiEval-style rows
normalizes those bridge rows so explanation precedes the final answer
keeps single-model training only; no BoN, self-consistency, routing, ensemble, or benchmark-label leakage
Rows: 1240
Bridge rows: 70
Train SHA256:… See the full description on the dataset page: https://huggingface.co/datasets/Jnx03/kanitakorn-deepseek-v45-v44-openthaieval-bridge-mix.DeepSeek-V4-Distill-8000x
🐳 DeepSeek-V4-Distill-8100x
Dataset Summary
DeepSeek-V4-Distill-8100x is a supervised fine-tuning dataset for reasoning-oriented distillation. The question prompts come from Jackrong/GLM-5.1-Reasoning-1M-Cleaned, and the answers were generated by the teacher model DeepSeek-V4-Flash.
After the cleaning process, the released train split contains 7,716 high-quality JSONL examples.
[!NOTE]
The answer pool was cleaned to remove real-time questions… See the full description on the dataset page: https://huggingface.co/datasets/wuqingsuiyue/DeepSeek-V4-Distill-8000x.Deepseek-V4-flash-QA-distill-3000Distill from Deepseek V4 Flash.
deepseek-v4-distill-ko-1k
DeepSeek-V4-Distill — Korean Translation (1K Sample)
A 1,000-item Korean translation derived from
Jackrong/DeepSeek-V4-Distill-8000x,
which itself contains reasoning traces distilled from DeepSeek-V4-Flash.
This is an early-stage test sample intended to validate the translation
pipeline (model, prompt, schema) before scaling to the full 7,716-item
dataset. The translations preserve the original <think>...</think> reasoning
blocks and structural formatting.
🛈 Status: experimental… See the full description on the dataset page: https://huggingface.co/datasets/drlee1/deepseek-v4-distill-ko-1k.deepseek-v4-flash-distill-multiturn-expr-rp