Qwen3.5-122B model fits 64GB RAM, offering better quality at slower speeds

A user on r/LocalLLaMA shared their experience running the Qwen3.5-122B model with UD-Q2_K_XL quantizations on a system with 64GB of RAM. This setup allows the larger model to fit into memory, offering significantly better response quality and internal knowledge compared to smaller models like Qwen3 Next 80B. However, this comes at the cost of reduced generation speed, approximately 2.9 tokens/second, and a substantial decrease in prompt processing speed, making it unsuitable for agentic tasks. AI

IMPACT Demonstrates trade-offs in local LLM deployment, balancing model size and quality against performance constraints.

RANK_REASON User experience post about running a specific model configuration locally.

Read on r/LocalLLaMA →

• AMD Strix Halo
• CPU
• DDR5-5600
• Gemma 4 26B A4B
• Multi Token Prediction
• Qwen3.5-122B
• Qwen3.5 35B A3B
• Qwen3.6 35B A3B
• Qwen3 Next 80B
• UD-Q2_K_XL
• UD-Q4_K_XL

• model release

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