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Qwen3.6-27B model shows strong performance on 4x 20GB 3080 GPUs

A user on Vast AI conducted benchmarks for code generation using the Qwen3.6-27B model on four 20GB 3080 graphics cards. The tests revealed impressive performance, with the setup achieving 69 tokens per second at near-maximum context length and a prefill speed of 893 tokens per second with the prompt cache disabled. The user suggests that this hardware configuration, costing around $2,000 for GPUs and supporting components, offers a cost-effective solution for a powerful code generation machine. AI

IMPACT Demonstrates cost-effective hardware solutions for running large language models locally for code generation tasks.

RANK_REASON User-conducted benchmark of an open-source model on consumer hardware. [lever_c_demoted from research: ic=1 ai=0.7]

Read on r/LocalLLaMA →

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

Qwen3.6-27B model shows strong performance on 4x 20GB 3080 GPUs

COVERAGE [1]

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

    I benched quad 20GB 3080s on Vast AI for code generation with Qwen3.6-27B so you don't have to (it's even better than quad 5060Tis)

    <table> <tr><td> <a href="https://www.reddit.com/r/LocalLLaMA/comments/1v414ll/i_benched_quad_20gb_3080s_on_vast_ai_for_code/"> <img alt="I benched quad 20GB 3080s on Vast AI for code generation with Qwen3.6-27B so you don't have to (it's even better than quad 5060Tis)" src="http…