Chatbot Arena +
This leaderboard is based on the following benchmarks. Chatbot Arena - a crowdsourced, randomized battle platform for large language models (LLMs). We use 3.5M+ user votes to compute Elo ratings. AAII - Artificial Analysis Intelligence Index aggregating 8 challenging evaluations. ARC-AGI - Artificial General Intelligence benchmark v2 to measure fluid intelligence.
GPT OSS
Welcome to the gpt-oss series, OpenAI’s open-weight models designed for powerful reasoning, agentic tasks, and versatile developer use cases. We’re releasing two flavors of these open models: gpt-oss-120b — for production, general purpose, high reasoning use cases that fit into a single H100 GPU (117B parameters with 5.1B active parameters) gpt-oss-20b — for lower latency, and local or specialized use cases (21B parameters with 3.6B active parameters)
GLM-4.5
The GLM-4.5 series models are foundation models designed for intelligent agents. GLM-4.5 has 355 billion total parameters with 32 billion active parameters, while GLM-4.5-Air adopts a more compact design with 106 billion total parameters and 12 billion active parameters. GLM-4.5 models unify reasoning, coding, and intelligent agent capabilities to meet the complex demands of intelligent agent applications.
MTP in SGLang
SGLang is the first and only open-source serving framework to support Multiple Token Prediction (MTP) in combination with Large-Scale Expert Parallelism (EP) and Prefill-Decode disaggregation. This integration delivers up to 60% higher output throughput through a new decoding paradigm, better parallelism, and more efficient resource utilization without sacrificing generation quality.
Open R1
A fully open reproduction of DeepSeek-R1. The goal of this repo is to build the missing pieces of the R1 pipeline such that everybody can reproduce and build on top of it.
Large-Scale Expert Parallelism
DeepSeek is a popular open-source large language model (LLM) praised for its strong performance. However, its large size and unique architecture, which uses Multi-head Latent Attention (MLA) and Mixture of Experts (MoE), require an advanced system for efficient serving at scale. In this blog, we explain how we match DeepSeek’s inference system performance using prefill-decode disaggregation and large-scale expert parallelism (EP) with SGLang.
Qwen3
We are excited to announce the release of Qwen3, the latest addition to the Qwen family of large language models. These models represent our most advanced and intelligent systems to date, improving from our experience in building QwQ and Qwen2.5. We are making the weights of Qwen3 available to the public, including both dense and Mixture-of-Expert (MoE) models.
Qwen2.5-Omni
We release Qwen2.5-Omni, the new flagship end-to-end multimodal model in the Qwen series. Designed for comprehensive multimodal perception, it seamlessly processes diverse inputs including text, images, audio, and video, while delivering real-time streaming responses through both text generation and natural speech synthesis.