Qwen3.5-122B Outshines MiniMax-M2.7 for High-Performance Local 大语言模型 (LLM) 推理

infrastructure #llm 📝 Blog|Analyzed: Apr 13, 2026 00:34•

Published: Apr 12, 2026 22:27

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1 min read

•r/LocalLLaMA

Analysis

It is incredibly exciting to see such powerful 开源 weights like Qwen3.5-122B and MiniMax-M2.7 becoming accessible for local setups. Enthusiasts and developers can now run massive models entirely on local GPUs, dramatically reducing 延迟 and unlocking amazing new possibilities for local coding assistance. The rapid advancement in model efficiency means that top-tier AI capabilities are no longer confined to massive cloud clusters!

Key Takeaways

•Enthusiasts are successfully running 100B+ 参数 models locally using dual 48GB GPUs for complete offloading.
•The highly quantized Qwen3.5 model achieved a fantastic 0.482 pass rate on the HumanEval benchmark, doubling the performance of the tested MiniMax model.
•Dynamic thinking toggles in local tools are streamlining interactions, making quick generations incredibly fast.

Reference / Citation

"But at least for my purposes, it seems like Qwen3.5-122B-A10B is still on top for inference speed, code quality, and general quality of life."

R

r/LocalLLaMAApr 12, 2026 22:27

* Cited for critical analysis under Article 32.

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Source: r/LocalLLaMA