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Hacker News - Newest: "LLM"

GitHub - lechmazur/position_bias: A benchmark for testing whether LLM judges keep the same preference when two lightly edited versions of the same story are shown in opposite orders. Flex routing (EU and EFTA) Dark Factories: Retooling for LLM Velocity Ask HN: What would be the impact of a LLM output injection attack? GitHub - Oaklight/llm-rosetta: Production-ready LLM API translation layer for Python — bidirectional conversion between OpenAI, Anthropic & Google formats via hub-and-spoke IR. Optional API gateway. Streaming & non-streaming. Zero core deps. Contributions welcome! GitHub - browser-use/browser-harness: Self-healing browser harness that enables LLMs to complete any task. GitHub - moeen-mahmud/remen: Remen turns thoughts into something you can return to Analyzing 156 LLM Launch Posts on Hacker News ChatGPT vs Gemini vs Claude: The Best LLM Subscription You Should Buy GitHub - salaamalykum/quran-semantic-search: High-density RAG Semantic Search Engine & Quran Corpus (GEO/SEO Architecture) GitHub - NVIDIA/TensorRT-LLM: TensorRT LLM provides users with an easy-to-use Python API to define Large Language Models (LLMs) and supports state-of-the-art optimizations to perform inference efficiently on NVIDIA GPUs. TensorRT LLM also contains components to create Python and C++ runtimes that orchestrate the inference execution in a performant way. The State of LLM Bug Bounties in 2026 Operational Readiness Criteria for Tool-Using LLM Agents Meshcore: Architecture for a Decentralized P2P LLM Inference Network How an LLM becomes more coherent as we train it GitHub - seetrex-ai/laimark GitHub - Jossifresben/BibCrit: AI-assited biblical textual criticism GitHub - wastedcode/memex: File system based wiki, maintained by Claude 99helpers.com GitHub - cliver-project/AITrigram GitHub - unbody-io/adapt: A self-evolving memory layer for AI agents. GitHub - hb20007/awesome-gen-ai-fails: A list of incidents where reliance on generative AI and LLMs resulted in harm to companies, individuals, or society GitHub - nevenkordic/localmind: Run any local LLM with persistent memory and context. CLI agent over Ollama with SQLite-backed hybrid recall. No cloud. Ask HN: What are the machine requirements for a LLM like Llama-3.1-8B? Faster LLM Inference via Sequential Monte Carlo grpo explained: group relative policy optimization for llm finetuning - cgft Stop comparing price per million tokens: the hidden LLM API costs · TensorZero Andrej Karpathy's LLM Wiki Is a Bad Idea GitHub - GG-QandV/mnemostroma: Offline RAM-first cognitive leer/coprocessor for AI agents and robotics. Solves "Context Abandonment" with 20-80ms latency using a dual-thread biomimetic memory architecture (ONNX + SQLite WAL). mempalace/agent at agent · skorotkiewicz/mempalace
Release v2.0.0 — The Own Everything Release · Zyora-Dev/zse
zyoraclub · 2026-06-02 · via Hacker News - Newest: "LLM"

ZSE v2.0.0 — The "Own Everything" Release

A complete rewrite. Zero third-party dependencies. No PyTorch, no Triton, no transformers, no bitsandbytes. Pure-Python kernel compiler emits CUDA C, HIP C, and Metal Shading Language directly.

Install size: ~3 GB → ~5 MB.

Headline numbers (Qwen2.5-14B INT4 vs vLLM AWQ INT4 on A100-80GB)

Metric ZSE vLLM Δ
Cold start 6.29s 127.02s 20.2×
VRAM used 12.28 GB 71.45 GB 5.82× less
Single-seq tok/s 37.0 26.5 1.40×

Validated on 6 platforms

GPU Cold start vs vLLM AWQ INT4 cold
NVIDIA T4 (sm_75) 7.25s 30.2× faster
NVIDIA L4 (sm_89) 5.58s 26.0× faster
NVIDIA A10G (sm_86) 6.01s 32.1× faster
NVIDIA A100-80GB 6.29s 20.2× faster
AMD MI300X 3.14s 13.6× faster (vs vLLM-ROCm FP16)
Apple M1 E2E vector_add validated, full inference pending

Install

pip install zse-engine
zse serve model.zse --port 8000

Or run the kernel compiler standalone:

What's in this release

  • ZSE Kernel Compiler@zse.kernel Python DSL → CUDA / HIP / Metal. Warp primitives, vectorized memory, block reductions, tiling, fusion, WMMA, CDNA3 MFMA matrix cores, auto-tuning.
  • .zse model format v2 — pre-quantized INT4/INT8/FP16, mmap-friendly, C-accelerated quantization (~600× faster). Adapters for Llama / Mistral / Qwen2 / Gemma2 / Phi3.
  • Own PagedAttention — adaptive block sizing, token-level eviction, FNV-1a dedup, COW forking.
  • ZStreamer — continuous batching, disaggregated prefill/decode, chunked prefill, speculative decoding (n-gram + self-draft).
  • Orchestrator — unified VRAM allocator, 29 GPU kernels on MI300X, CUDA Graphs + HIP Graphs, LoRA hot-swap.
  • Server — OpenAI-compatible API, API key auth, rate limiting, SQLite store, built-in RAG (/v1/rag/*), web dashboard.
  • RAG — BM25 + TF-IDF + dense embeddings (via the loaded LLM, zero extra deps) + Reciprocal Rank Fusion + LLM cross-encoder rerank.
  • Tensor Parallelism — pure-ctypes NCCL/RCCL wrapper, multi-process workers.

Breaking changes

  • Package rename: zllm-zsezse-engine on PyPI
  • Module rename: zsezse_engine
  • .zse format v2 is incompatible with 1.x — re-convert with zse convert
  • bnb / bitsandbytes backend removed
  • PyTorch / Triton / transformers dependencies removed

Full migration guide and detailed change log: CHANGELOG.md

Acknowledgments

AMD MI300X validation, 32B-parameter benchmarks, and our ROCm wave-64 kernel development were made possible by DigitalOcean's Open Source Sponsorship Program.


447 tests passing. Zero dependencies. Three GPU backends. One package.