gpt-5.2
Mistral-Nemo-2407-12B-Thinking-Claude-Gemini-GPT5.2-Uncensored-HERETIC-GGUFQwen3-8B-GPT-5.2-High-Reasoning-Distill-i1-GGUFSentie1.0-3B-Claude-Fable-5-GPT5.2-Sol-Kimi-K3-GLM-5.2-GGUFMistral-Nemo-2407-12B-Thinking-Claude-Gemini-GPT5.2-Uncensored-HERETIC-i1-GGUFMistral-Nemo-2407-12B-Thinking-Claude-Gemini-GPT5.2-Uncensored-HERETICMistral-Nemo-2407-12B-Thinking-Claude-Gemini-GPT5.2-Uncensored-HERETIC-GGUFQwen2.5-7B-Instruct-1M-Thinking-Claude-Gemini-GPT5.2-DISTILL-i1-GGUFQwen3-14B-GPT-5.2-High-Reasoning-Distill-GGUF
Datasets
All datasets matching “gpt-5.2”gpt-5.2-high-reasoning-250x
Generated using DataGen by TeichAI
This is a reasoning dataset created using GPT 5.2 with a reasoning depth set to high.
The dataset is meant for creating distilled versions of GPT 5.2 by fine-tuning already existing open-source LLMs.
Stats
Costs: $ 10.58 (USD)
Total tokens (input + output): N\A
Sonnet-Opus-4.5-4.6-Gemini-3.0-3.1-Pro-GPT-5-5.1-5.2-GLM-4.7-MiniMax-M2.1-DeepSeek-V3.2-High
Distill
This is a multi-source curated instruction and reasoning dataset specifically for training and distilling large language models (LLMs) to exhibit advanced Chain-of-Thought (CoT), Agentic, Mathematical and Coding capabilities. It aggregates high-quality outputs from frontier models into messages ChatML format.
Dataset Structure
The dataset contains a total of 70.2K examples, split into three subsets based on the presence of visible reasoning… See the full description on the dataset page: https://huggingface.co/datasets/VINAY-UMRETHE/Sonnet-Opus-4.5-4.6-Gemini-3.0-3.1-Pro-GPT-5-5.1-5.2-GLM-4.7-MiniMax-M2.1-DeepSeek-V3.2-High.v3-2k-traj-gpt-5.2swebench-verified-gpt-5.2btc-reasoning-traces-gpt5.2
BTC Reasoning Traces — gpt-5.2-chat-latest
LLM reasoning traces for BTC/USD trading decisions. Each row is one hourly
trading decision: the model receives account state + multi-timeframe OHLCV
market data, reasons step-by-step in <think> tags, and outputs a discrete
action (<answer>N</answer>). The dataset stores the full chain-of-thought
alongside the resulting reward and next state — making it suitable for
offline RL, imitation learning, or reward modelling.
Generation… See the full description on the dataset page: https://huggingface.co/datasets/Torch-Trade/btc-reasoning-traces-gpt5.2.qgqa-gpt-5.2-20260213-041705