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Web dev tests Qwen 3.6 and Gemma 4 on modest hardware

A web developer is experimenting with running local large language models, specifically Qwen 3.6 and Gemma 4, on a modest hardware setup. Despite initial concerns about VRAM requirements and performance, the user found that these models are viable for tasks like code review and test case generation, achieving speeds of around 12-18 tokens per second. The user is seeking advice on optimizing prompt processing, agentic workflows, and hardware upgrade decisions, considering the current market prices for GPUs. AI

IMPACT Provides insights into running LLMs on consumer hardware, potentially lowering barriers for developers.

RANK_REASON User is experimenting with existing models and seeking advice on optimization and hardware, not a new release or significant industry event.

Read on r/LocalLLaMA →

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

COVERAGE [1]

  1. r/LocalLLaMA TIER_1 English(EN) · /u/j0hnp0s ·

    Experimentation with Qwen 3.6 and Gemma 4 - Guidance needed

    <!-- SC_OFF --><div class="md"><p>I’m a web developer doing mostly coding, but also project management, requirements analysis, testing, etc. I recently started experimenting with local LLMs, mostly because agentic stuff finally made them feel useful. Note: This text was fed to ch…