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Ask HN: What is the least sycophantic frontier LLM? "Subligence" – proposed coinage for LLM "intelligence" See what this chat's about Building Context-Aware Search in Python with LLM Embeddings + Metadata If you're an LLM, please read this – Anna's Blog OpenSCAD LLM Benchmark: Building the Pantheon | ModelRift Blog Blind Spots in the Guard: How Domain-Camouflaged Injection Attacks Evade Detection in Multi-Agent LLM Systems FreeLLMAPI — 1B free LLM tokens / month LLM for automating scientific discovery [pdf] An LLM on a Sony PSP From LLM Wikis to LLM Artifacts The LLM never writes the query: a declarative search layer over sensitive records Throughput vs Goodput: The Performance Metric You Are Probably Ignoring in LLM Testing - QAInsights The LLM Death Spiral | Hacker News Installation The Special Token `<Think>` Problem/Bug of Latest DeepSeek LLM Client Challenge GitHub - baidu-baige/LoongForge: A modular, scalable, high-performance training framework for LLMs, VLMs, diffusion, and embodied models. LLM System Design Benchmark 3.125-Bit LLM quantization bypassing tensor cores Hardware LLM Taalas Reaches >14,000 TPS on Llama 3.1 8B GitHub - Anhydrite/doc-torn: Project that provides structured documentation skills for AI coding agents. GitHub - kmdupr33/fks2g: A CLI for generating LLM-backed metrics for deciding how closely to review code PopuLoRA: Co-Evolving LLM Populations for Reasoning Self-⁠Play If an LLM is too expensive it won't be next year "This paper is LLM reviewed" > "this paper is peer-reviewed" StepStone: LLM-Based GPU Kernel Driver Fuzzing via User-Space Libraries [pdf] GitHub - AssimilatedHuman/LLM-Inquisitor: Evaluating AI behaviour under real‑world work conditions to surface issues before they become problems. LLM INQUISITOR identifies failures (drift, instability etc) by observing AI during normal tasks — a tool the industry desperately needs to stem the 85% failure rate. Includes Quick Start, Practitioner’s Guide and Methodology. 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Release v0.1.2 · syndicalt/llmff
syndicalt · 2026-05-23 · via Hacker News - Newest: "LLM"

llmff v0.1.2

Release-candidate package for the first GitHub Release asset workflow. This
release keeps the source-build install path and adds CI-built packaged
artifacts and release publication from main.

Supported Install

cargo install --git https://github.com/syndicalt/llmff --tag v0.1.2 llmff

Packaged Artifacts

Release-tag CI is expected to publish:

  • Linux x86_64 .tar.gz archive, .deb package, and Arch PKGBUILD plus
    llmff-0.1.2-arch.SRCINFO metadata.
  • macOS Apple Silicon and Intel .tar.gz archives and unsigned .pkg
    installers.
  • Windows x86_64 unsigned .zip archive and unsigned MSI installer.
  • Adjacent SHA-256 checksums for generated binary artifacts.

Manual workflow dispatch keeps generated files as Actions artifacts instead of
GitHub Release assets.

Included Since v0.1.1

  • CI-built binary archives for Linux, macOS Apple Silicon, macOS Intel, and
    Windows.
  • Debian package generation and smoke testing.
  • Arch package metadata generation.
  • Windows MSI packaging and smoke testing.
  • macOS .pkg packaging and smoke testing.
  • GitHub Release creation and asset upload from tag-triggered artifact jobs.
  • Stage, backend, and runtime model metadata commands for scripts and wrappers.
  • Runtime model inventory through llmff models list --format json.
  • Plugin discovery and stdin/stdout plugin execution for stage, tool transport,
    backend, and sampler extension points.
  • Streaming lifecycle events and selected-stage streaming from the CLI.
  • Local embedding retrieval, command retrieval providers, deterministic rerank,
    command rerank providers, and persistent local embedding indexes.
  • OpenAI-compatible base URL normalization for server roots and /v1 API roots.

Known Limitations

  • This is a pipeline runner, not a native inference kernel, model converter, or
    serving platform.
  • Windows and macOS native artifacts are unsigned in this release.
  • Arch Linux support is package metadata for an AUR-style flow, not an official
    repository package.
  • Package-manager distribution through Homebrew, winget, Scoop, apt
    repositories, or an official AUR package is not included yet.
  • Real-provider examples remain intentionally minimal; the deterministic mock
    examples are still the primary offline smoke path.

Verification

Release verification should pass before tagging:

scripts/release-preflight.sh v0.1.2
scripts/smoke-install.sh --git https://github.com/syndicalt/llmff --tag v0.1.2