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Show HN: Open-source engine running Gemma 4 26B in 2 GB RAM on any M-series Mac

BACKGROUND
1 SIGNALFIRST DETECTED 29 July 2026
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How the story developed
Other feeds and industry voices
15 Jul
Running Gemma 4 26B at 5 tokens/SEC on a 13-year-old Xeon with no GPU

<a href="https://news.ycombinator.com/item?id=48922434">Comments</a>

REPORT · WHAT · Hacker News Best (RSS)OPEN STORY
22 Mar
Flash-Moe: Running a 397B Parameter Model on a Mac with 48GB RAM

<a href="https://news.ycombinator.com/item?id=47476422">Comments</a>

REPORT · WHAT · Hacker News Best (RSS)OPEN STORY
2 Apr
Gemma 4: Byte for byte, the most capable open models

Gemma 4: Our most intelligent open models to date, purpose-built for advanced reasoning and agentic workflows.

REPORT · HOW · Google DeepMind BlogOPEN STORY
1 Sept
Show HN: Running 104GB Qwen3.8-Flash-Next on 48GB Mac with at ~12 tok/s

<a href="https://news.ycombinator.com/item?id=49524447">Comments</a>

REPORT · WHAT · Hacker News Best (RSS)OPEN STORY
2 Apr
Gemma 4 running on Raspberry Pi5

<table> <tr><td> <a href="https://www.reddit.com/r/LocalLLaMA/comments/1sarlb8/gemma_4_running_on_raspberry_pi5/"> <img alt="Gemma 4 running on Raspberry Pi5"

OPINION · WHAT · LocalLLaMAOPEN STORY
2 Apr
Inference Engine for Apple Silicon

<a href="https://news.ycombinator.com/item?id=47615809">Comments</a>

REPORT · WHAT · Hacker News Best (RSS)OPEN STORY
8 Apr
gemma-tuner-multimodal: Fine-tune Gemma 4 with audio, images and text on Apple Silicon

<table> <tr><td> <a href="https://www.reddit.com/r/LocalLLaMA/comments/1sffz0e/gemmatunermultimodal_finetune_gemma_4_with_audio/"> <img alt="gemma-tuner-multimodal: Fine-tune

OPINION · WHAT · LocalLLaMAOPEN STORY
2 Apr
[P] Gemma 4 running on NVIDIA B200 and AMD MI355X from the same inference stack, 15% throughput gain over vLLM on Blackwell

<!-- SC_OFF --><div class="md"><p>Google DeepMind dropped Gemma 4 today:</p> <p><strong>Gemma 4 31B:</strong> dense, 256K context, redesigned architecture targeting efficiency and

OPINION · WHEN · MachineLearningOPEN STORY
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