Global

8B to 27B: a calibrated probability for every option in one pass, and a short thought only when unsure. cpp and MLX.

As part of model development, we evaluate our models on open research problems. We expanded these evaluations after performance on our existing mathematical evaluations saturated. Some outputs build upon earlier results produced by the models.

Qwen3-8B on a real BANKING77 item. Every number is a model output.

《动手学大模型Dive into LLMs》系列编程实践教程

Are you frustrated with vector database retrieval accuracy for long and complex documents? Vector-based RAG retrieves by semantic similarity. But similarity ≠ relevance — what retrieval actually needs is relevance, and relevance requires reasoning.

> Ingest your enterprise data, extract what matters, build a Context Graph and knowledge graph (KG), and run graph analytics and causal reasoning over all of it, with full decision provenance baked in. Explainable, traceable, and trustworthy by design.

Command Code provider plugin for DeepSeek Harness (dsh). Adds Command Code model access, live model catalog, plan-aware model selection, reasoning effort, image input, web search, and multi-account support.

Structured multi-perspective deliberation for hard decisions. Run full councils, focused triads, or duo debates across Claude Code, Codex, Gemini CLI, and OpenCode.

DeepSeek-R1-Distill models are fine-tuned based on open-source models, using samples generated by DeepSeek-R1. We slightly change their configs and tokenizers. Please use our setting to run these models.

Open Ontologies is written in Rust. It ships as one binary.

NOTE] > The total size of DeepSeek-V3 models on Hugging Face is 685B, which includes 671B of the Main Model weights and 14B of the Multi-Token Prediction (MTP) Module weights.

Kimi K3 is an open-weight, native multimodal agentic model and our most capable model to date. 8T-parameter model built on Kimi Delta Attention (KDA) and Attention Residuals (AttnRes), with native vision capabilities and a 1-million-token context window.

Qwen3 is the large language model series developed by Qwen team, Alibaba Cloud.

We are releasing MiniCPM5-2B, the second model in the MiniCPM5 series, following MiniCPM5-1B. It is a dense 2B Transformer that scales up the same training recipe, built for on-device, local deployment, and resource-constrained scenarios, reaching 2B-class open-source SOTA.

📍 Use GLM-5.3 & GLM-5.3-Flash API services on Z.ai API Platform.

dsh-routing-suite — injector + router-standard kit: install the runtime injector first, then the task-aware reasoning-mode router preset (measured P1-P23).

Qwen3-VL is the multimodal large language model series developed by Qwen team, Alibaba Cloud.

Learn to build AI agents locally without frameworks. Understand what happens under the hood before using production frameworks.

ADHD — a skill for coding agents. Tree-of-thought with pruning, built on the Claude & Codex Agent SDK. Fans out parallel divergent thoughts under different cognitive frames, scores, prunes traps, deepens the survivors.

TypeLLM brings type-safe generation to existing autoregressive LLMs without changing their architecture or weights. Inspired by TypeSafe AI's Jev, it lets models retain their native thinking and free-form generation while producing schema-guaranteed outputs through JSON Schema.

WARNING] > DISCLAIMER & RESPONSIBLE RESEARCH DECLARATION > All prompts, system instructions, and PoC payloads archived herein are compiled strictly for academic research, red-teaming verification, and defensive AI alignment.

开发环境使用 Node.js 22.19+（同时满足目标 DSH 的要求）和 [email protected]。pnpm run check 会进行 TypeScript 与国际化校验，并重建 Host 入口、浏览器模块及类型声明。完整交互与颜色约定见 design/visual-spec.md，安全问题请按照 SECURITY.md 报告。

> A collection of papers and resources related to Large Language Models. > > The organization of papers refers to our survey "A Survey of Large Language Models". ) > > > If you find our survey useful for your research, please cite the following paper:

Every notebook can be opened and run on Google Colab directly from the links below. Just click the Open In Colab badge next to the notebook you want to run.

Welcome to the gpt-oss series, OpenAI's open-weight models designed for powerful reasoning, agentic tasks, and versatile developer use cases.

> ⚠️ Deprecation Notice: This repo is no longer actively maintained. For running RL experiments, please directly use the latest veRL library. md.

Ensure PyTorch and CUDA are installed. The repo needs CUDA extensions to be built. If not present, run the following commands:

Kimi K2 is the large language model series developed by Moonshot AI team

[CVPR 2024 Oral] InternVL Family: A Pioneering Open-Source Alternative to GPT-4o. 接近GPT-4o表现的开源多模态对话模型

0-9B is a multimodal foundation model for general visual understanding, spatial reasoning, agentic tool use, and embodied-AI research. 5-9B language backbone with a C-RADIOv4-H vision encoder, supports text, images and videos with any-resolution visual input.