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Run an 80B Qwen in 4.3 GB of RAM on a Mac, and a 35B on an iPhone

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HN · launched Aug 3, 2026 · 312 upvotes (top 1%) · 0 views

Niche: llm inference engines · 133 launches, 4 in the last 7 days ▼ -33% · Explore this niche →

Category and tags

  • Horizontal
  • Model & infra
  • Developer
  • AI-native
  • Hobby / open-source project

Visit website ↗ Source listing ↗

Could you build this?

No Fitting an 80B model into 4.3 GB of RAM requires extreme sub-1-bit quantization research (such as BitNet, AQLM, or custom ternary/binary matrix multiplication kernels) and deep hardware-level optimization for Apple Silicon/Metal.

What it would actually take: This project requires custom low-level C++/Metal kernels implementing extreme quantization schemes (e.g., 0.5 to 1.58 bits per weight) alongside tailored activation memory management. The developer must have deep expertise in low-precision numerical methods, SIMD/NEON/Metal assembly optimization, and transformer inference runtime internals. Off-the-shelf vibe coding cannot produce correct or performant custom GPU/NPU kernels at this level of algorithmic complexity.

Discussion

20 comments analyzed.

Competitors mentioned: iPhone local LLMs, Ollama, TurboFieldfare, Chinese LLMs

Concerns raised: Prefill latency takes too long, Frontier labs will prevent open-weight model adoption, SSD storage solution won't be cost-effective within 10 years, Greedy pricing stalls progress and adoption, Noise and performance concerns with local inference

Feature requests: Support for Android/Linux/Windows platforms, Gemma model support, Improved prefill performance

Competitors

Other products that read as similar to this one : 864 launches clear the similarity bar, closest 8 shown.

Attention rank: #18 of 865 (itself plus its competitors, highest first, normalized so YC and Product Hunt are compared fairly).

Launched 269 days after the earliest competitor.

The niche, labels, vibe code rating and competitor comparison on this page are analysis by Nicheloom. If you use them, please credit nicheloom.com. How you may use our data.