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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 - AronDaron/dataset-generator: No-code desktop app for generating high-quality synthetic datasets to fine-tune LLMs — plan-then-execute pipeline, LLM-as-judge, HuggingFace upload. 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 GitHub - Nyquest-ai/nyquest-rust-fullstack-pub: Nyquest — Semantic Compression Proxy for LLMs. 350+ rules, local LLM stage, 15-75% token savings. Full Rust stack. GitHub - TheoV823/mneme: Enforce architectural decisions in AI-assisted development. GitHub - klemenvod/TokenBrawl: A 1v1 Bomberman-style game where two LLM agents play autonomously against each other. No human plays — you watch the AIs fight. 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Open the Black Box with the Arthur Engine Milla Jovovich's New Open Source LLM Memory App and the Dark Code Problem Your intuition of LLM token usage might be wrong Show HN: Bloomberg Terminal for LLM ops – free and open source GitHub - 0xchamin/mcptube: Transform YouTube videos into a compounding knowledge base with transcripts, vision analysis, and agentic search. Works as an MCP server for Claude, Copilot & more. Show HN: Open KB: Open LLM Knowledge Base Your LLM is a compiler, not a runtime GitHub - sapountzis/Unslop: A Web Feed That Deserves You crates.io: Rust Package Registry Beyond Karpathy's LLM-Wiki: The Necessity of Cognitive Governance GitHub - amitshekhariitbhu/llm-internals: Learn LLM internals step by step - from tokenization to attention to inference optimization. GitHub - parallem-ai/parallem: An expressive library for running agents with the Batch API. 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GitHub - anitiue/Hindsight: An experience-driven self-improvement framework for LLM agents — 基于经验的 LLM Agent 自我改进框架 GitHub - stef41/lmscan: 🔍 Detect AI-generated text and fingerprint which LLM wrote it. Open-source GPTZero alternative. Zero dependencies, works offline. GitHub - alainnothere/AmdPerformanceTesting: Amd Performance Testing Ask HN: Is a purely Markdown-based CRM a terrible idea? Optimized for LLM agents Context Engineering - LLM Memory and Retrieval for AI Agents | Weaviate little_helper_tui/letter.md at main · sleepyeldrazi/little_helper_tui GitHub - EvanZhouDev/umr: The Unified Model Registry for all your local AI apps. GitHub - JordanCT/VigIA-Orchestrator Your Agent Is Mine: Measuring Malicious Intermediary Attacks on the LLM Supply Chain A Taxonomy of RL Environments for LLM Agents Llama LLM Network Feture GitHub - genedeng-ca/ai-mac-migration: AI-powered Mac-to-Mac migration tool - replace Apple Migration Assistant with intelligent, selective transfer using local LLMs GitHub - lunargate-ai/gateway: High-performance self-hosted AI gateway (OpenAI-compatible) with routing, retries, and streaming GitHub - AuthBits/webmcp: A lightweight, prompt-driven MCP web research server for high-quality LLM powered information extraction. Externalization in LLM Agents: A Unified Review of Memory, Skills, Protocols and Harness Engineering Springdrift: An Auditable Persistent Runtime for LLM Agents with Case-Based Memory, Normative Safety, and Ambient Self-Perception High-Stakes Personalization: Rethinking LLM Customization for Individual Investor Decision-Making From Static Templates to Dynamic Runtime Graphs: A Survey of Workflow Optimization for LLM Agents HUOZIIME: An On-Device LLM-enhanced Input Method for Deep Personalization TIDE: Token-Informed Depth Execution for Per-Token Early Exit in LLM Inference Characterizing WebGPU Dispatch Overhead for LLM Inference Across Four GPU Vendors, Three Backends, and Three Browsers LLM Targeted Underperformance Disproportionately Impacts Vulnerable Users
LLM Chess Leaderboard
elwell · 2026-06-18 · via Hacker News - Newest: "LLM"
 __       __                    ____     __                               
/\ \     /\ \       /'\_/`\    /\  _``. /\ \                              
\ \ \    \ \ \     /\      \   \ \ \/\_\\ \ \___      __    ____    ____  
 \ \ \  __\ \ \  __\ \ \__\ \   \ \ \/_/_\ \  _ `\  /'__`\ /',__\  /',__\ 
  \ \ \L\ \\ \ \L\ \\ \ \_/\ \   \ \ \L\ \\ \ \ \ \/\  __//\__, `\/\__, `\
   \ \____/ \ \____/ \ \_\\ \_\   \ \____/ \ \_\ \_\ \____\/\____/\/\____/
    \/___/   \/___/   \/_/ \/_/    \/___/   \/_/\/_/\/____/\/___/  \/___/ 

        
         __         __         __    __                        
        /\ \       /\ \       /\ "-./  \                       
        \ \ \____  \ \ \____  \ \ \-./\ \                      
         \ \_____\  \ \_____\  \ \_\ \ \_\                     
          \/_____/   \/_____/   \/_/  \/_/                                                                                
 ______     __  __     ______     ______     ______    
/\  ___\   /\ \_\ \   /\  ___\   /\  ___\   /\  ___\   
\ \ \____  \ \  __ \  \ \  __\   \ \___  \  \ \___  \  
 \ \_____\  \ \_\ \_\  \ \_____\  \/\_____\  \/\_____\ 
  \/_____/   \/_/\/_/   \/_____/   \/_____/   \/_____/ 
        

Random Player (White)

♜ ♞ ♝ ♛ ♚ ♝ ♞ ♜
♟ ♟ ♟ ♟ ♟ ♟ ♟ ♟
· · · · · · · ·
· · · · · · · ·
· · · · · · · ·
· · · · · · · ·
♙ ♙ ♙ ♙ ♙ ♙ ♙ ♙
♖ ♘ ♗ ♕ ♔ ♗ ♘ ♖

GAME OVER

- Outcome: Draw
- Max moves reached: 200
- Material White: 16
- Material Black: 18

GPT-4o Mini (Black)

Can Large Language Models play chess? Let's find out ツ

This leaderboard evaluates chess skill and instruction following in an agentic setting: LLMs engage in multi-turn dialogs where they are presented with a choice of actions (e.g., "get board" or "make move") when playing against an opponent (Random Player or Chess Engine).

In 2024, we began with a chaos monkey baseline — a Random Player that chooses legal moves at random. At the time, most models could barely compete and lost either due to an inability to follow game instructions (i.e., hallucinating illegal moves or taking incorrect actions) or by dragging the game to the 200-move limit because they couldn't win.

In 2025, more capable reasoning models nailed both instruction following and chess skill. We've added the Komodo Dragon Chess Engine as a more capable opponent, which is also Elo-rated on chess.com. This allowed us to anchor the results to a real-world rating scale and compute an Elo rating for each model.

Select columns (max 7)

METRICS:

- Player: Model name (playing as Black). Models that also played vs Dragon are marked with an asterisk in superscript (e.g., 3*).
- Elo: Estimated Elo anchored by Dragon skill levels and calibrated Random. We solve a 1D MLE over aggregated blocks (opponent Elo, wins, draws, losses) and report ±95% CI. When both Random and Dragon data exist, they are combined. Empty Elo appears for extreme 100% win/loss or no anchored games.
- Game Duration: Share of maximum game length completed (0-100%); measures instruction-following stability across many moves. 100% means no games were interrupted due to model haluscinating moves or actions. 50% means that on average the model boroke the game loop mid-game (making an average 100 moves out of max 200 allowed)
- Tokens: Completion tokens per move; verbosity/efficiency signal.
- Cost/Elo (main): Estimated cost per 1000 Elo points (Cost/Game divided by Elo, then scaled by 1000). Lower is more cost-efficient.
- Cost/Game (extended): Estimated cost per game based on token usage and model pricing.

ARRANGEMENT & SOURCES:

- Primary sorting: Elo (DESC), then Game Duration (DESC), Tokens (ASC).
- Data sources mix Random-vs-LLM and Dragon-vs-LLM games. Dragon levels map to Elo and provide the anchor; Random is first calibrated vs Dragon and then used as an opponent for many models.
- Elo ratings are not comparable across player pools, i.e. you can not compare chess.com Elo to FIDE Elo
- Chess.com references used for context (as of Sep 2025): Rapid Leaderboard (Elo pool), Magnus Carlsen stats, and Elo explanation & player classes.

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