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Story

We got 207 tok/s with Qwen3.5-27B on an RTX 3090

1 report

1 website

1 discussion

Latest report

Overview

Lucebox is an optimization hub for hand-tuned LLM inference, specifically designed for individual consumer hardware. It features kernels, speculative decoding, and quantization tailored for each target, with the first megakernel for hybrid DeltaNet/Attention LLMs achieving 1.87 tokens per joule on a 2020 GPU.

Summary from github.com.

Reports

One report so far. Additional coverage will appear here when it is linked to this story.

  1. github.com

    We got 207 tok/s with Qwen3.5-27B on an RTX 3090

    Read report →

Community reactions

Each reaction summarizes sampled comments from the linked discussion.

Hacker News · github.com

We got 207 tok/s with Qwen3.5-27B on an RTX 3090 ↗
Hacker News discussion ↗

Historical count: 5 · 5 saved in sample · Historical sample

Analysis ready

Read this discussion’s reaction

Based on 5 sampled comments from this thread. Analyzed 2026-04-21.

  • Praise: Running Qwen3.5-27B on an RTX 3090 demonstrates the potential for local AI deployment, allowing users to leverage existing hardware without vendor lock-in.
  • Praise: The ability to run models on Vulkan and Apple's hardware indicates a growing flexibility in AI infrastructure, which could enhance accessibility for developers.
  • Praise: The reported peak performance of 207.6 tok/s showcases significant advancements in model efficiency, potentially enabling faster inference for real-time applications.
  • Concern: The claim of achieving 207 tok/s is misleading, as it relies on speculative decoding, which may compromise output quality compared to traditional methods.
  • Concern: The focus on a specific GPU like the RTX 3090 raises concerns about accessibility, as it may not represent the average developer's hardware capabilities.
  • Concern: The implementation appears to prioritize speed over quality, which could lead to inferior outputs and undermine the reliability of the model's performance.