Kimi K2.6
Kimi K2.6 is an open-weight, trillion-parameter mixture of experts (MoE) large language model released by Moonshot AI on 20 April 2026 for agentic coding and long-horizon autonomous execution.
Large Language Models
Explore language models, how they work, and the techniques used to build applications with them.
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Showing 301-360 of 608 articles
Kimi K2.7-Code
Kimi K2.7-Code is an open-weight, coding-focused agentic model released by Moonshot AI on 2026-06-12.
Kimi K3
Kimi K3 is an open-weight multimodal reasoning model developed by Moonshot AI. Moonshot made the model available through its hosted products on July 16, 2026 and published the weights, code, configuration…
Kimi K3.1 Pro
Kimi K3.1 Pro is a multimodal large language model from the Chinese company Moonshot AI, announced on October 23, 2026.
Kimi Linear
Kimi Linear is a hybrid linear attention architecture published by Moonshot AI on October 30, 2025, together with a 48-billion-parameter mixture-of-experts model that activates 3 billion parameters per token.
Knowledge Editing
Knowledge editing (also called model editing) is a family of techniques for updating or correcting specific factual associations stored in the weights of a trained large language model without full retraining…
Kolibri 1
Kolibri 1 is an open-weight large language model developed by Aleph Alpha for German and English. It supports text generation, reasoning and tool calling.
LFM3
LFM3 is the third generation of Liquid Foundation Models (LFMs), a family of open-weight small language models and multimodal models released by Liquid AI on October 27, 2026.
LLM API Pricing Comparison
Every figure in this article is a US dollar list rate per 1,000,000 tokens, taken from the provider's own pricing page.
LLM Benchmark Comparison (Leaderboard Overview)
As of July 2026, no single model wins every LLM benchmark, but Anthropic's Claude Fable 5 tops the most: it currently leads MMLU-Pro (91.5%), SWE-bench Verified (95.0%), Humanity's Last Exam in both the…
LLM Compiler (Meta)
The Meta Large Language Model Compiler, usually shortened to LLM Compiler, is a family of pre-trained large language model models built by Meta AI for code and compiler optimization tasks.
LLM Context Window Comparison
As of July 2026, the largest context window ever announced belongs to Magic's LTM-2-mini at 100,000,000 tokens (100M), but it is a research prototype that has never been publicly released.
LLM Evaluation
LLM evaluation is the practice of measuring what a large language model can do, how reliably it does it, and how it behaves under adversarial or high-stakes conditions.
LLM Model Routing
LLM model routing is the selection of a large language model to handle a request from a pool of candidate models.
LLM Size and Parameter Comparison
As of July 2026, OpenAI has never officially disclosed how many parameters GPT-5 has, and no GPT-5.x version ships a public size
LLM inference engine
An LLM inference engine (also called an LLM serving engine or LLM inference server) is the systems software stack that loads trained large language model weights into GPU or CPU memory and answers user…
LLM-as-a-Verifier
LLM-as-a-Verifier is a probabilistic verification framework and open-source Python package for scoring and selecting large language model agent trajectories.
LLM-as-a-judge
LLM-as-a-judge is the practice of using a strong large language model to evaluate the outputs of other models, or of itself, in place of a human annotator.
LLM.int8()
LLM.int8() is an 8-bit matrix multiplication scheme for large language model inference that preserves accuracy across models up to 175 billion parameters by combining vector-wise quantization with a…
LLaDA (Large Language Diffusion)
LLaDA (Large Language Diffusion with mAsking) is a family of non-autoregressive large language models that generate text by iteratively denoising a sequence of mask tokens rather than predicting tokens left to…
LLaMA
LLaMA is the original name of a family of large language models developed by Meta AI.
LLaMA/Model Card
The Llama model card is the official documentation that Meta AI ships with each release of the Llama family of large language models.
LM Studio
LM Studio is a desktop application for discovering, downloading, and running large language models locally on personal hardware, available free for both personal and commercial use on macOS, Windows, and Linux.
LaMDA
LaMDA (short for Language Model for Dialogue Applications) is a family of conversational large language models developed by Google, built on the Transformer architecture and fine-tuned for open-ended dialogue…
LangChain
LangChain is an open-source software framework for applications that use large language models.
Large Language Model
A large language model (LLM) is an artificial intelligence system built on a transformer neural network with billions to trillions of parameters, trained on massive text corpora to predict the next token in a…
LayoutLM
LayoutLM is a family of pre-trained multimodal models developed by Microsoft Research for document AI, the task of automatically reading and understanding visually rich documents such as forms, invoices…
Leanstral 1.5
Leanstral 1.5 is an open-weight model from Mistral AI for formal proof engineering in Lean 4.
Least-to-Most Prompting
Least-to-Most Prompting is a few-shot prompting technique for large language models introduced by researchers at Google Brain in May 2022.
LegalBench
LegalBench is a collaboratively constructed benchmark for measuring legal reasoning in large language models (LLMs)
Ling-1T
Ling-1T is a trillion-parameter open-weight language model released by Ant Group through its Inclusion AI research group on October 9, 2025.
Ling-3.0-flash
Ling-3.0-flash is an open-weight mixture-of-experts language model from inclusionAI, the open-source AI initiative of Ant Group, and the first model of the Ling 3.0 generation.
Ling-3.1-flash
Ling-3.1-flash is a text large language model from InclusionAI, part of Ant Group's Ling family.
LiteLLM
LiteLLM is an open-source AI gateway from BerriAI that lets developers call more than 100 large language model providers (including OpenAI, Anthropic, Google Gemini, Amazon Bedrock and Azure OpenAI) through a…
Llama 2
Llama 2 is a family of open-weight large language models developed by Meta AI. Meta released pretrained and dialogue-tuned checkpoints with 7 billion, 13 billion, and 70 billion parameters on July 18, 2023.
Llama 3
Llama 3 is a family of open-weight large language models developed by Meta. Meta released the original Llama 3 checkpoints on April 18, 2024, in 8-billion-parameter and 70-billion-parameter sizes.
Llama 3.1
Llama 3.1 is a family of open-weight large language models released by Meta on July 23, 2024, in three sizes, 8 billion, 70 billion, and 405 billion parameters, each shipped in both a pre-trained base form and…
Llama 3.2
Llama 3.2 is a family of four open-weight large language models released by Meta on September 25, 2024, comprising lightweight 1 billion and 3 billion parameter text-only models for on-device AI and the 11…
Llama 3.2 Vision
Llama 3.2 Vision is the set of multimodal (image-plus-text) models in Meta's Llama 3.2 family, released on September 25, 2024 at the Meta Connect 2024 developer conference.
Llama 3.3
Llama 3.3 is an instruction-tuned, text-only large language model with 70 billion parameters that Meta released on December 6, 2024
Llama 4
Llama 4 (Large Language Model Meta AI 4) is a family of natively multimodal large language models developed by Meta and released on April 5, 2025, the first generation of the Llama series to use a mixture of…
Llama 4 Behemoth
Llama 4 Behemoth is the announced but never publicly released flagship model in the Llama 4 family from Meta AI.
Llama 4 Scout and Maverick
Llama 4 Scout and Llama 4 Maverick are open-weight, natively multimodal AI large language models developed by Meta and released on April 5, 2025.
Llama Nemotron
Llama Nemotron is a family of open reasoning large language models built by Nvidia by post-training Meta's Llama models for math, coding, and agentic tasks.
Llama-3.1-Nemotron-70B-Instruct
Llama-3.1-Nemotron-70B-Instruct is a large language model released by NVIDIA in October 2024.
LoftQ
LoftQ (short for LoRA-Fine-Tuning-aware Quantization) is a quantization and initialization framework for large language models that jointly quantizes a pre-trained backbone and initializes the attached…
Long-context language models
Long-context language models are large language models engineered to accept and reason over inputs far larger than the few-thousand-token windows used by early transformer systems, with frontier models in 2026…
LongBench
LongBench is a benchmark suite for evaluating the long-context understanding capabilities of large language models (LLMs).
LongBench v2
LongBench v2 is a benchmark for evaluating how well large language models understand and reason over long contexts.
LongCat-2.5
LongCat-2.5 is a multimodal mixture-of-experts language model developed by Meituan for coding and long-running agent tasks.
LongCat-Flash
LongCat-Flash is an open-weight large language model developed by the LongCat team at Meituan, the Chinese on-demand local-services and food-delivery company.
LongLoRA
LongLoRA is a parameter-efficient fine-tuning technique that extends the context window of pre-trained large language models with substantially lower computation than full fine-tuning.
LongRoPE
LongRoPE is a context-window extension technique for large language models (LLMs) that use rotary position embeddings (RoPE).
Longformer
Longformer is a transformer architecture for processing long documents, introduced by Iz Beltagy, Matthew E. Peters
Lookahead Decoding
Lookahead Decoding is a parallel decoding algorithm for accelerating inference in large language models, introduced in November 2023 by Yichao Fu, Peter Bailis, Ion Stoica, and Hao Zhang from the Hao AI Lab at…
Luo Fuli
Luo Fuli (Chinese: 罗福莉; also written Fuli Luo) is a Chinese AI researcher who leads the MiMo large-model team at Xiaomi.
MAI-1-preview
MAI-1-preview is a large language model developed by Microsoft AI, the consumer artificial intelligence division of Microsoft led by Mustafa Suleyman.
MBPP
MBPP (Mostly Basic Python Problems) is a code generation benchmark of 974 crowd-sourced Python programming tasks designed to be solvable by entry-level programmers, introduced by Jacob Austin, Augustus Odena…
MMLU-Pro
MMLU-Pro (Massive Multitask Language Understanding Professional) is an artificial intelligence benchmark of 12,032 ten-choice questions across 14 academic domains
MMLU-ProX
MMLU-ProX is a multilingual benchmark for evaluating reasoning and knowledge in large language models