opus-4.7
Huihui-Qwen3.6-35B-A3B-Claude-4.7-Opus-abliterated-MTP-GGUFRavenX-CyberAgent-Qwen3.6-35B-A3B-Opus-4.7-OpenMythos-Pentester-BugHunter-RATH-GGUFQwen3.6-35B-A3B-Claude-4.7-Opus-Reasoning-Distilled-APEX-GGUFQwen3.6-35B-A3B-Claude-4.7-Opus-Reasoning-Distilled-APEX-MTP-GGUFQwen3.6-35B-A3B-Claude-4.7-Opus-Reasoning-Distilled-IQ4_XS-GGUFGLM-4.7-Flash-Claude-Opus-4.5-High-Reasoning-Distill-GGUFQ36-35B-A3B-Opus4.7-Ablit-Heretic-OBLITERATUS-Hermes-MTP-Vision-FT-i1-GGUFHuihui-Qwen3.6-35B-A3B-Claude-4.7-Opus-abliterated-mlx-8bit
Datasets
All datasets matching “opus-4.7”claude-opus-4.6-4.7-reasoning-8.7k
Background
Ended up with some tokens to burn on a Claude Max plan. Assembly began during 4.6 and moved to 4.7. Model is tagged. The development evolved as it went along. The dataset has not been manually reviewed. It's entirely Claude developed.
Clarification on Reasoning
The reasoning is not Claude's actual chain-of-thought (cot) and is not summarized cot. It's a fully synthetic cot created as part of the Assistant response to mimic the type of "thinking"… See the full description on the dataset page: https://huggingface.co/datasets/angrygiraffe/claude-opus-4.6-4.7-reasoning-8.7k.Claude-opus-4.7-TraceInversion-5000x
🌀 Claude-opus-4.7-TraceInversion-5000x
v1.0 Release
A High-Fidelity Reconstructed CoT Dataset Saturated with the 'Opus Deep Logic Style' via Trace Inversion
📊 5,000 Samples
🧬 Trace Inversion & Negentropy
🛠 SFT & DPO Ready
🔥 Claude 4.7-Max Distillation
🌐 English & Multilingual
💡 What is Trace Inversion?
In Large Language Model (LLM) reasoning distillation, proprietary API models (such as GPT-4/5 and Claude)… See the full description on the dataset page: https://huggingface.co/datasets/Jackrong/Claude-opus-4.7-TraceInversion-5000x.lordx64-claude-opus-4.7-max-cleaned
reasoning-distill-claude-opus-4-7-max-cleaned
Cleaned version of lordx64/reasoning-distill-claude-opus-4-7-max.
See the original dataset for full provenance, collection methodology, and terms of use.
Cleaning steps
Step
Filter
Reason
Rows removed
1
Simulated thinking (...)
Rows with ... in thinking/response indicate the model learned to simulate reasoning (e.g., "Now I'm laying out the puzzle grids...") rather than actually performing it. This causes failures… See the full description on the dataset page: https://huggingface.co/datasets/TeichAI/lordx64-claude-opus-4.7-max-cleaned.fable5-gpt5.5-opus4.7-mixed-agent-traces
Fable5 · GPT-5.5 · Opus-4.7 Mixed Agent Traces
A high-density post-training mixture for agentic reasoning, instruction following, code generation, function calling, and tool-use decision making.
This is the training-data release behind Qwen3.5-9B-Distill-Agent-Instruct, an Agent Instruct model distilled and post-trained from Qwen3.5-9B-Base. The title highlights three of the mixture's principal model-labelled trajectory families—Claude Fable5, GPT-5.5 Agent, and Claude Opus… See the full description on the dataset page: https://huggingface.co/datasets/lzy510016411/fable5-gpt5.5-opus4.7-mixed-agent-traces.Axiom-1.0-Opus4.7-Kimi2.6-GLM5.2-Deepseek4-Mythos5-Fable5-Qwen3.7
Project Axiom 1.0 (102 GB Reasoning Corpus)
27-Billion Token Pure-Text Chain-of-Thought Corpus Across 7 Frontier Architectures
Executive Summary
Project Axiom 1.0 is a landmark, high-density, multi-architecture reasoning corpus comprising 102 GB of uncompressed, pure-text JSONL data (axiom.jsonl). Curated by Shreyan Gondaliya and the Solstice-AI research team, the dataset synthesizes ~5.74 million unique samples and ~27.3 billion tokens of… See the full description on the dataset page: https://huggingface.co/datasets/Solstice-AI/Axiom-1.0-Opus4.7-Kimi2.6-GLM5.2-Deepseek4-Mythos5-Fable5-Qwen3.7.combined-reasoning-opus-4.6-opus-4.7-kimi-k2.5-kimi-k2.6-glm-5.1
Combined Reasoning Distill — Multi-Model
A large-scale unified reasoning dataset combining thinking and chain-of-thought traces distilled from frontier models, normalized into a single consistent schema for fine-tuning. Includes data from Claude (Opus 4.5/4.6/4.7, Sonnet 4.5/4.6, Haiku 4.5), GPT (5.1/5.2), Gemini 3 Pro Preview, Kimi (K2/K2.5/K2.6), GLM (4.6/4.7/5.1), MiniMax M2.1, Grok Code Fast 1, and more.
Schema
Every row has a single field:
Field
Type… See the full description on the dataset page: https://huggingface.co/datasets/Avtrkrb/combined-reasoning-opus-4.6-opus-4.7-kimi-k2.5-kimi-k2.6-glm-5.1.
Academic_Paper_Deep_Analysis_POE_CLAUDE_OPUS_4.6_4.7_OR_OLLAMA_CLOUD_MODEL_OPTIONAL_WEBSEARCHGLM-4.7-Flash-Claude-Opus-4.5-High-Reasoning-Distill-GGUF-Q3_K_MGLM-4.7-Flash-Claude-Opus-4.5-High-Reasoning-Distill-GGUF-Q3_K_MGLM-4.7-Flash-Claude-Opus-4.5-High-Reasoning-Distill-GGUF-Q3_K_MGLM-4.7-Flash-Claude-Opus-4.5-High-Reasoning-Distill-GGUF-Q3_K_MGLM-4.7-Flash-Claude-Opus-4.5-High-Reasoning-Distill-GGUF-Q3_K_M