Qwen2.5-Math
Qwen2.5-Math is a family of mathematics-specialized large language models developed by the Qwen team at Alibaba Cloud and released in September 2024.
Large Language Models
Explore language models, how they work, and the techniques used to build applications with them.
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Qwen3
Qwen3 is the third-generation family of large language models developed by the Qwen Team at Alibaba Cloud (also known as Tongyi Qianwen lab).
Qwen3 Embedding
Qwen3 Embedding is a family of open text embedding and reranking models released by Alibaba's Qwen team in June 2025.
Qwen3-Coder
Qwen3-Coder is a family of open-weight large language models specialized for software engineering, developed by Alibaba's Qwen team (Tongyi Lab) and released under the Apache 2.0 license.
Qwen3-Max
Qwen3-Max is a large language model in Alibaba's Qwen series, the flagship of the Qwen3 generation and the first Qwen model to cross one trillion parameters, released in preview on September 5, 2025 and…
Qwen3-Next
Qwen3-Next is an efficiency-focused large language model and model architecture released in September 2025 by the Qwen team at Alibaba Cloud.
Qwen3-Omni
Qwen3-Omni is a natively end-to-end omni-modal foundation model developed by the Qwen team at Alibaba Cloud, capable of understanding text, images, audio, and video and generating both text and natural speech…
Qwen3-VL
Qwen3-VL is a family of open-weight vision-language models built by the Qwen team at Alibaba Cloud, first released in September 2025.
Qwen3.5
Qwen3.5 is a family of open-weight large language models developed by the Qwen team at Alibaba, the successor to the Qwen3 series.
Qwen3.6
Qwen3.6 is a generation of large language models from the Qwen team at Alibaba, released in April 2026 as the successor to Qwen3.5.
Qwen3.7-Max
Qwen3.7-Max is a closed-weight frontier large language model developed by Alibaba's Qwen team, announced in May 2026 as the flagship of the Qwen3.7 generation.
Qwen3.8
Qwen3.8 is the name Qwen uses for a model generation that includes hosted services and downloadable checkpoints.
Qwen3.8-Flash-Next
Qwen3.8-Flash-Next is an experimental open-weight multimodal large language model released by Alibaba Group's Qwen team on August 26, 2026.
Qwen3.8-Max
Qwen3.8-Max is a 2.4-trillion-parameter mixture-of-experts large language model developed by Alibaba's Qwen team and released on August 3, 2026 under the title "Qwen3.8-Max: A New Bar for Coding and Cowork".
RULER (benchmark)
RULER is a synthetic benchmark from NVIDIA that measures the real, usable context window of large language models (LLMs) by testing them on 13 tasks across four categories (retrieval, multi-hop tracing…
RWKV-7 (Goose)
RWKV-7, codenamed Goose, is an attention-free, RNN-style large-language-model architecture introduced in March 2025 that runs inference in linear time with constant memory per token while still training in…
Reasoning (artificial intelligence)
Reasoning in artificial intelligence is the ability of an AI system to draw inferences, solve problems, and make decisions through structured, multi-step thought rather than a single immediate response.
Reasoning models
Reasoning models are large language models that are post-trained or configured to spend additional inference-time computation on intermediate steps before returning an answer.
RecurrentGemma
RecurrentGemma is a family of open-weight language models released by Google DeepMind that is built on the Griffin architecture rather than the standard Transformer.
Recursive Flint
Recursive Flint is a text-only large language model developed by Recursive Superintelligence for coding agents and announced on October 21, 2026.
Recursive language model
A recursive language model (RLM) is an inference strategy in which a large language model does not read its input prompt directly.
RefinedWeb
RefinedWeb is a large-scale English pretraining dataset for large language models, built from filtered and deduplicated Common Crawl web data alone and released in June 2023 by the Technology Innovation…
Reflection AI
Reflection AI (which brands itself simply as Reflection) is an American artificial intelligence company that builds open-weight foundation models and the software around them.
Refusal direction
The refusal direction is a finding from mechanistic interpretability research that the refusal behavior of safety fine-tuned chat language models is mediated by a single
Reka AI
Reka AI (commonly referred to as Reka) is an artificial intelligence research and product company founded in 2022 by former Google DeepMind, Google Brain, Meta FAIR, and Baidu researchers.
Reka Core
Reka Core is a frontier class multimodal foundation model developed by Reka AI, a research and product company founded in 2022 by former scientists from DeepMind, Google Brain, Meta FAIR, and Baidu.
Reka Edge
Reka Edge is a 7-billion-parameter multimodal language model developed by Reka AI, introduced in April 2024 as the smallest member of the company's first publicly described model family.
Reka Flash
Reka Flash is a family of multimodal large language models developed by Reka AI, a San Francisco Bay Area research company founded in 2022 by former researchers from Google DeepMind, Meta FAIR, and Google.
Retrieval-Augmented Generation
Retrieval-augmented generation (RAG) is a family of methods that retrieves information from an external collection and conditions a generative model on that information when producing an output.
Revolution Labs
Revolution Labs is an artificial intelligence startup founded in 2026 by Nando de Freitas, a machine learning researcher who worked at Google DeepMind for about a decade before a period at Microsoft.
Ring-1T
Ring-1T is an open-weight reasoning model released in October 2025 by inclusionAI, the open-source research initiative associated with Ant Group
Ripple-65B Preview
Ripple-65B Preview is an open-weight, text-based large language model from Ricursive Intelligence.
Rotary Position Embedding
Rotary Position Embedding (RoPE) is a positional encoding method for transformer models that encodes a token's absolute position by rotating its query and key vectors in two-dimensional subspaces
SGLang
SGLang (short for Structured Generation Language) is a high-performance, open-source serving framework for large language models and multimodal models, originally developed at UC Berkeley's Sky Computing Lab…
SPADE (Self-Play in Adaptive Synthetic Executable Environments)
SPADE, short for Self-Play in Adaptive Synthetic Executable Environments, is a reinforcement-learning framework in which one language model alternates between designing executable training environments and…
SPIN (Self-Play Fine-Tuning)
SPIN (Self-Play fIne-tuNing) is a post-training method for large language models introduced by researchers at the University of California, Los Angeles (UCLA) in January 2024.
Salesforce AI
Salesforce AI is the suite of artificial intelligence products, research initiatives, and platform capabilities developed by Salesforce, the San Francisco-based enterprise software company, organized around…
SantaCoder
SantaCoder is a 1.1 billion parameter large language model for code generation, released in early 2023 by the BigCode project, an open scientific collaboration co-led by Hugging Face and ServiceNow Research.
Sarvam AI
Sarvam AI, which brands itself simply as Sarvam and is legally Axonwise Private Limited, is a Bengaluru-based artificial intelligence company that builds large language models, speech, translation and document…
Scaling Laws
Neural scaling laws are empirical relationships that describe how a measured outcome changes as a neural network, its training data, or the computation used to train it becomes larger.
Scaling Laws for Neural Language Models
Scaling Laws for Neural Language Models is a landmark research paper published by OpenAI on January 23, 2020 (arXiv:2001.08361) that established that the test loss of a neural language model falls as a smooth…
SciBERT
SciBERT is a BERT-based language model pretrained from scratch on a large corpus of scientific papers, built by the Allen Institute for AI (AI2).
Self-Discover prompting
Self-Discover is a prompting framework for large language models in which the model first composes a task-specific reasoning structure from a library of atomic reasoning modules
Self-Instruct
Self-Instruct is a semi-automated framework for aligning a pretrained large language model with instruction-following behavior by bootstrapping its training data from the model itself, introduced in December…
Self-Refine
Self-Refine is an inference-time prompting framework in which a single large language model iteratively improves its own output by alternating between generating natural-language feedback on a draft and…
Self-Rewarding Language Models
Self-Rewarding Language Models (SRLM) is an iterative alignment method in which a single large language model alternately plays the role of policy (generating candidate responses to user prompts) and reward…
Self-consistency
Self-consistency is a decoding strategy for large language models that samples multiple chain-of-thought reasoning paths for the same question and returns the answer that the majority of those paths agree on
SenseNova
SenseNova (Chinese: 日日新) is the family of foundation models developed by the Hong Kong-listed AI company SenseTime.
SimPO
SimPO (Simple Preference Optimization) is a reference-free offline preference learning algorithm for aligning large language models with human preferences.
Skywork-R1V
Skywork-R1V (also written Skywork R1V) is a family of open-weight multimodal vision-language models built for chain-of-thought reasoning, developed by Skywork AI, the AGI and AIGC division of the Chinese…
SlimPajama
SlimPajama is a 627-billion-token English-language pre-training corpus for large language models, produced by Cerebras Systems in collaboration with the Opentensor Foundation by extensively cleaning and…
Small language model
A small language model (SLM) is a compact large language model, typically under about 10 billion parameters, built to run efficiently on a single consumer GPU, a laptop, or a smartphone rather than in a data…
SmolLM
SmolLM is a family of small, fully open language models released by Hugging Face on July 16, 2024 in three sizes, 135 million, 360 million, and 1.7 billion parameters, all trained on a curated open dataset…
SmolLM 2
SmolLM 2 is a family of compact open-weight language models released by Hugging Face on November 1, 2024.
SmolLM 3
SmolLM 3 is a fully open 3 billion parameter language model released by Hugging Face on July 8, 2025, trained on 11.2 trillion tokens and designed as a small, multilingual, long-context reasoner.
SmoothQuant
SmoothQuant is a training-free, accuracy-preserving post-training quantization (PTQ) method that enables 8-bit weight and 8-bit activation (W8A8) integer inference for large language models without retraining…
Snowflake AI
Snowflake AI is the suite of artificial intelligence and machine learning capabilities built into the Snowflake AI Data Cloud, anchored by Cortex AI (managed generative AI services callable in SQL), the…
Snowflake Arctic
Snowflake Arctic is an open large language model released by Snowflake AI Research on April 24, 2024.
SparDA
SparDA (Sparse Decoupled Attention) is an add-on architecture for long-context large language model inference proposed by researchers at NVIDIA in a paper posted to arXiv on 3 June 2026.
Spark-X2.6-4B
Spark-X2.6-4B is a large language model released by SparkLLM under the XHToken organization for local text generation and AI agent applications.