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AI Coder's Lesson: 8-bit Quantization Outperforms 4-bit for Agentic Tasks

A user on Mastodon shared their experience with AI models for agentic coding, recommending against the use of Q4 models. They found that Qwen3.6-35B-A3B and Ornithogalum-1.5-35B-A3B perform well, particularly when using 8-bit quantization variants, highlighting a significant difference compared to 4-bit quantization. AI

IMPACT Highlights the practical impact of quantization on AI model performance for coding tasks.

RANK_REASON User experience and opinion on model performance.

Read on Mastodon — mastodon.social →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

AI Coder's Lesson: 8-bit Quantization Outperforms 4-bit for Agentic Tasks

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COVERAGE [1]

  1. Mastodon — mastodon.social TIER_1 English(EN) · [email protected] ·

    @ LouisR85 So, my lesson learned is: do not use Q4 models for agentic coding. Qwen3.6-35B-A3B is working well in OpenCode and it's staying focused so is Ornith-

    @ LouisR85 So, my lesson learned is: do not use Q4 models for agentic coding. Qwen3.6-35B-A3B is working well in OpenCode and it's staying focused so is Ornith-1.5-35B-A3B as long as I stick to the 8bit variants. It's a huge difference between 8bit and 4bit quantisation. # AI # L…