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Qwen3.6-35B-A3B model optimized for single RTX 3090 GPU

A user on Reddit shared their process for optimizing the Qwen3.6-35B-A3B model on a single RTX 3090 GPU. They aimed for maximum quality and speed with a 128k context window. Benchmarks indicate that the `ik_llama` engine with the `I-Compact` APEX model offers the fastest generation speeds, while the `spiritbuun` engine with `I-Quality` and a TurboQuant cache provides comparable speed with potentially higher quality. The `I-Quality` model shows strong performance metrics, closely matching higher-quality benchmarks while being significantly smaller and faster than the reference BF16 model. AI

IMPACT Provides insights into efficient deployment of large language models on consumer-grade hardware, potentially lowering barriers to entry for advanced AI use.

RANK_REASON User-generated guide on optimizing a specific model on consumer hardware.

Read on r/LocalLLaMA →

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

Qwen3.6-35B-A3B model optimized for single RTX 3090 GPU

COVERAGE [1]

  1. r/LocalLLaMA TIER_1 English(EN) · /u/old-mike ·

    Qwen3.6-35B-A3B APEX on a Single RTX 3090 - Getting the Most Out of It

    <!-- SC_OFF --><div class="md"><p>Resources I used: - <a href="https://github.com/ikawrakow/ik_llama.cpp">https://github.com/ikawrakow/ik_llama.cpp</a> - as the reference llama.cpp fork - <a href="https://github.com/spiritbuun/buun-llama-cpp">https://github.com/spiritbuun/buun-ll…