TeichAI launches high-reasoning GGUF distillate

#distillation #quantized #reasoningglm-4.7-flash-claude-opus-4.5-high-reasoning-distill-gguf

💡New GGUF distillate beats priors on reasoning—test locally now

⚡ 30-Second TL;DR

What Changed

Distilled from GLM-4.7-Flash and Claude Opus 4.5

Why It Matters

Provides open-weight alternative for advanced reasoning on local hardware, boosting accessibility for LocalLLaMA users.

What To Do Next

Download GGUF from Hugging Face repo and benchmark reasoning with llama.cpp.

Who should care:Developers & AI Engineers

Background and context from public sources — not the original article. 2 sources cited.

•TeichAI released GLM-4.7-Flash-Claude-Opus-4.5-High-Reasoning-Distill-GGUF, a model trained on a small reasoning dataset from Claude Opus 4.5 with high reasoning effort.[1]
•The model is available on ModelScope under TeichAI/GLM-4.7-Flash-Claude-Opus-4.5-High-Reasoning-Distill-GGUF and also listed on Hugging Face as per Reddit post.[1]
•Dataset used is TeichAI/claude-4.5-opus-high-reasoning, specifically optimized for high reasoning capabilities.[1]
•Model was featured in recent AI news aggregators like Hype on Replicate for past three days, indicating quick community pickup around Feb 18-21, 2026.[2]
•GGUF format enables efficient local inference, as highlighted in Reddit r/LocalLLaMA post and Unsloth/X mentions on 2026-02-20.[article]

Trained on small reasoning dataset from Claude Opus 4.5, with reasoning effort explicitly set to 'High'.[1]
Base models: GLM-4.7-Flash distilled with Claude 4.5 Opus.[1][article]
Format: GGUF, optimized for local inference on platforms like Hugging Face and ModelScope.[1][article]
Dataset source: TeichAI/claude-4.5-opus-high-reasoning (specific high-reasoning subset).[1]