Show HN: Bare-Metal AI – Zero-dependency, sub-millisecond AI engines
In 2026–2027, the paradigm has shifted: Zero-Bloat Architecture: Production edge AI demands sub-millisecond execution, sub-100MB memory footprints, and single-binary or zero-dependency libraries. Hardware Direct Access: Maximum performance from modern CPUs using unrolled SIMD (AVX2, AVX-512, ARM NEON) and dedicated tensor registers without heavy BLAS overhead. Local & Autonomous: AI agents require instant local episodic memory, embedded vector indexing, and token-by-token CPU inference without cloud network latency or API bills. 📊 2026–2027 Benchmark & Footprint Leaderboard Category Project Language Binary Footprint Latency / Throughput Zero External Deps?
- ▪In 2026–2027, the paradigm has shifted: Zero-Bloat Architecture: Production edge AI demands sub-millisecond execution, sub-100MB memory footprints, and single-binary or zero-dependency libraries.
- ▪Hardware Direct Access: Maximum performance from modern CPUs using unrolled SIMD (AVX2, AVX-512, ARM NEON) and dedicated tensor registers without heavy BLAS overhead.
- ▪Local & Autonomous: AI agents require instant local episodic memory, embedded vector indexing, and token-by-token CPU inference without cloud network latency or API bills. 📊 2026–2027 Benchmark & Footprint Leaderboard Category Project Lang
Hacker News (AI / LLM) files mainly under ai. We currently carry 4,781 of its stories.
Story provenance
Source · retrieval · rights · ranking — open for full record
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Story provenance
Attribution is not the same as permission. This drawer separates discovery metadata, excerpts, WeSearch-generated summaries, reuse status, and whether the publisher receives the visit. Nothing here claims a legal grant the publisher has not made.
Record
| Original publisher | GitHub |
| Canonical URL | https://github.com/eminsk/awesome-baremetal-ai |
| Publication time | Mon, 14 Sep 2026 12:05:52 +0000 |
| Retrieval time | 2026-09-14T12:16:51.165Z |
| Last seen | 2026-09-14T12:16:51.165Z |
| Headline source | Publisher (no WeSearch rewrite) |
| Excerpt source | publisher body |
| Excerpt method | First ~120 words (~800 chars) of extracted publisher body, fair-use limited. |
| Summary | WeSearch · cerebras-chat (WeSearch summarizer) |
| Summary source text | contentText |
| Citation coverage | Summary is a WeSearch-generated derivative; primary citation is the original publisher URL. |
| Cluster | IpC0uu7TPd4a · 1 stories |
| Cluster logic | Grouped by semantic title/content similarity across sources within a rolling window. Same-publisher template collisions are excluded from coverage comparison. |
| Ranking reason | Story pages are not engagement-ranked. Hub feeds use recency, with optional source-diversified chronological ordering (cap consecutive stories per source). No personalized ranking. |
| Publisher visit | Yes — open original |
| Substitutes article? | No — link-out required for full text |
Rights status (four layers)
WeSearch handling by dimension
| Indexing | May the item be indexed (stored, ranked, made findable)? | Allowed |
| Snippet | May a short excerpt of the publisher's text be shown? | Allowed |
| AI summary | May WeSearch generate its own short summary of the article? | Limited |
| Retrieval / RAG | May the content be exposed for third-party retrieval-augmented generation? | Not asserted |
| Model training | May the content be used to train AI models? | Not asserted |
| Commercial reuse | May the content be reused commercially? | Not permitted |
Basis: Derived from the published RSS/Atom feed. Contact: [email protected]. Reviewed: 2026-07-24.
Opening excerpt (first ~120 words) tap to expand
⚡ Awesome Bare-Metal AI (2026–2027) A curated leaderboard, benchmark index, and definitive guide to ultra-lightweight, zero-dependency, bare-metal AI engines written in pure C, C++, Rust, Zig, and Assembly for local LLMs, edge inference, vector search, and autonomous agents. 🎯 The Bare-Metal AI Manifesto In 2024–2025, deploying AI often meant 2GB Docker images, multi-gigabyte Python runtimes, and complex distributed clusters. In 2026–2027, the paradigm has shifted: Zero-Bloat Architecture: Production edge AI demands sub-millisecond execution, sub-100MB memory footprints, and single-binary or zero-dependency libraries. Hardware Direct Access: Maximum performance from modern CPUs using unrolled SIMD (AVX2, AVX-512, ARM NEON) and dedicated tensor registers without heavy BLAS overhead.
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Excerpt limited to ~120 words for fair-use compliance. The full article is at GitHub.