Open-weight LLM releases

Moonshot's open coding-focused agentic model built on K2.6, with native vision/video input, forced thinking mode, and stronger long-horizon software-engineering performance.

Z.ai's latest open flagship for long-horizon coding, agentic engineering, and million-token workflows, adding IndexShare sparse-attention reuse over GLM-5.1.

Native multimodal MiniMax model with a one-million-token context, sparse attention, and agentic coding/cowork positioning.

NVIDIA's largest Nemotron 3 open-weight hybrid Mamba-Transformer MoE, tuned for agentic reasoning, coding, planning, and tool calling.

Open-weight agentic model from MiniMax focused on real-world software engineering, office tasks, tool use, and self-improving training workflows.

Dense 27B that punches far above its weight on agentic coding — easy to self-host on a single GPU node.

Efficient V4 companion model with 284B total / 13B active parameters and the same one-million-token context window.

Preview-series sparse MoE flagship with a one-million-token context window and 1.6T total / 49B active parameters.

Tencent Hunyuan open-weight fine-grained MoE model with 80B total parameters and 13B active parameters, optimized for agentic tool use.

Z.ai agentic-engineering follow-up to GLM-5, with stronger coding performance and better long-horizon tool-use behavior.

Google DeepMind's Gemma 4 advanced-reasoning open model for personal computers, part of the April 2026 Gemma 4 family.

Moonshot's open native multimodal agentic model for long-horizon coding, visual interface generation, and autonomous tool orchestration.

Dense 128B open-weight model with a 256k context and strong coding performance for its size.

Open-weight hybrid Mamba-Transformer MoE designed for collaborative agents and high-volume enterprise workflows.

StepFun's Apache-licensed sparse MoE model for fast agentic execution, coding, math, browsing, and tool-use workflows.

Apache-licensed Indian-context MoE from Sarvam AI, optimized for reasoning, coding, agentic tasks, and 22 Indian languages.

Native vision-language MoE supporting 201 languages with a 1M-token context.

Z.ai flagship for complex systems engineering and long-horizon agentic tasks, scaling the GLM line to 744B total / 40B active parameters.

Apache-licensed Qwen3-Next coding-agent model with 80B total / 3B active parameters, 256K context, and long-horizon tool-use training.

Open multimodal Kimi model that adds native visual agentic intelligence, instant and thinking modes, and agent-swarm workflows on top of the K2 base.

Coding-focused GLM release with improved multilingual agentic coding, terminal tasks, tool use, and interface generation.

Ai2's fully open thinking model with public weights, code, data, checkpoints, and training details across the OLMo 3 pipeline.

Efficient Nemotron 3 MoE checkpoint for agentic reasoning and coding, activating about 3B parameters while supporting 1M-token contexts.

Open 106B-class vision-language model with native multimodal function calling for visual agents.

Mistral's largest open-weight MoE, aimed at frontier reasoning while remaining self-hostable.

Reasoning-first agent model that adds DeepSeek Sparse Attention and thinking directly inside tool-use workflows.

High-compute reasoning variant of V3.2, positioned for olympiad-level math, programming, and other deep reasoning tasks.

Liquid AI hybrid model for efficient CPU/GPU/NPU local deployment, using short convolutions plus attention blocks.

Open K2 reasoning-agent variant that interleaves step-by-step thinking with tool calls and supports stable 200-300 step tool-use trajectories.

MIT-licensed hybrid linear-attention model using Kimi Delta Attention, built for million-token contexts with much lower KV-cache usage.

Agentic reasoning and coding upgrade over GLM-4.5, expanding the text context window from 128K to 200K tokens.

Experimental checkpoint that introduced DeepSeek Sparse Attention as an efficiency bridge between V3.1-Terminus and V3.2.

Stability update to V3.1 focused on language consistency, code-agent reliability, and search-agent behavior.

September 2025 K2 update with stronger agentic coding, better frontend generation, and a doubled 256K context window.

Google's open multimodal model: 128k context, 140+ languages, runs on a single GPU.

Hybrid thinking/non-thinking release that upgraded tool calling, long-context training, and agent task performance.

ByteDance Seed's Apache-licensed long-context reasoning and agent model, with controllable thinking budgets and a native 512K context.

Vision-language GLM based on GLM-4.5-Air, covering image, video, document, grounding, and GUI-agent tasks.

Smaller gpt-oss reasoning model optimized for local inference on systems with about 16GB of memory.

OpenAI's larger open-weight reasoning model, a 117B-total / 5.1B-active MoE with 128K context for local and self-hosted deployment.

A hybrid attention + state-space-model (SSM) design that matches 70B-class models with fewer parameters.

Open agentic, reasoning, and coding foundation model that marked Z.ai international rebrand and MIT-licensed GLM push.

Compact GLM-4.5 companion with 106B total / 12B active parameters for efficient agentic reasoning and coding.

LG AI Research's unified model with non-reasoning and reasoning modes, agentic tool use, and English, Korean, and Spanish support.

Original open K2 post-trained model: a 1T-parameter MoE optimized for coding, reasoning, and tool-using agentic workflows.

Hugging Face's fully open 3B multilingual long-context model with optional reasoning mode and 128K context.

Baidu's open ERNIE 4.5 language MoE, part of a 10-variant Apache-licensed model family built with heterogeneous multimodal MoE training.

Baidu's largest ERNIE 4.5 vision-language MoE, supporting text, image, and video inputs with thinking and non-thinking modes.

Updated MIT-licensed Kimi-VL reasoning model with better multimodal reasoning, video understanding, high-resolution perception, and lower thinking-token use.

MIT-licensed coding LLM trained with repository-level reinforcement learning for software issue resolution.

Open Apache-licensed hybrid-attention reasoning model with 456B total / 45.9B active parameters and a native 1M-token context.

Open-weight 24B reasoning model from Mistral's Magistral family, popular for local reasoning experiments.

Major R1 reasoning update with stronger math, programming, general logic, function calling, and reduced hallucinations.

Sarvam's medium-scale open model for multilingual Indian-language chat, reasoning, and translation tasks.

Phi-4 reasoning-specialized model family for math, science, and chain-of-thought style tasks.

Granite 3.3 text update for enterprise chat, RAG, and instruction-following workflows.

Largest open Qwen3 MoE, introducing hybrid thinking/non-thinking modes and 119-language coverage.

Open audio foundation model for audio understanding, generation, speech recognition, audio QA, captioning, and speech conversation.

Efficient MIT-licensed vision-language MoE for OCR, image/video understanding, long documents, and OS-style agent tasks.

Meta's flagship open-weight MoE; highest MMLU among open models at release.

Efficient open-weight MoE designed for very long context on modest hardware.

Open Llama Nemotron reasoning model from NVIDIA's 2025 Nemotron family.

Local omni-modal Qwen model that supports text, image, audio, video, and speech generation in a 7B package.

Post-R1 V3 update with improved reasoning, front-end coding, Chinese writing, search, and function calling.

Apache-licensed Small update adding vision and a 128K context window to the efficient 24B line.

A fully open model — weights, data, and training code all public — and the first such to beat GPT-3.5 / GPT-4o mini.

Enterprise-grade model tuned for RAG, tool use, and multilingual business workloads.

Granite 3.2 update with reasoning controls and multimodal/document-oriented Granite variants.

MIT-licensed 16B/3B-active MoE trained with Moonshot's scalable Muon optimizer experiments.

Nous reasoning-oriented Hermes model trained to combine concise answers with optional deep reasoning traces.

Popular local assistant model tuned for coding, math, function calling, and agentic workflows.

A latency-optimized 24B dense model under Apache-2.0 — a popular local-deployment workhorse.

Vision-language Qwen2.5 model for image, document, video, and agentic visual grounding tasks.

Breakout open reasoning model trained with large-scale reinforcement learning and released with weights under MIT.

Open MiniMax generation with MiniMax-Text-01 and MiniMax-VL-01 long-context models.

The 671B/37B-active MoE release that made DeepSeek a central open-model lab before the R1 breakthrough.

IBM's enterprise-focused open model with a 128k context, Apache-2.0 licensed.

UAE's TII open model designed to run on light infrastructure, including laptops.

Cohere's smallest, fastest R-series model, tuned for RAG and tool use on modest hardware.

A 14B dense model that rivals far larger ones on math and reasoning, under a permissive MIT license.

EXAONE 3.5 32B open-weight model for bilingual reasoning, coding, and long-context tasks.

Late-2024 70B Llama update delivering much of the 405B instruction-following quality at lower serving cost.

Qwen's first public reasoning-preview model, aimed at math, coding, and deliberate problem solving.

Ai2's post-trained open instruction model line, scaling the Tulu recipe to Llama 3.1 405B.

Code-specialized Qwen2.5 model family, with the 32B checkpoint as the flagship open coding model.

Tencent's 389B total / 52B active open-weight Transformer MoE, released with a 256K pretraining context and 128K instruct context.

Compact on-device model family trained on 11T tokens, popular for lightweight local chat and experimentation.

Sarvam's 2B open model trained for ten major Indian languages.

Apache-licensed Granite 3.0 text model, part of IBM's push toward enterprise-friendly open models.

NVIDIA-tuned Llama 3.1 70B instruction model optimized with Nemotron reward and alignment recipes.

First Llama family release with native vision models, alongside smaller edge-oriented 1B and 3B text models.

Open multimodal model family trained for strong image understanding, pointing, and visual grounding.

Broad Qwen2.5 foundation-model update spanning general, coding, math, and multimodal descendants.

Mistral's first open multimodal model, adding image understanding to a Mistral text backbone.

01.AI's compact code model trained for repository-scale programming and code completion tasks.

Unified DeepSeek V2 generation combining general-chat and coding strengths before the V3 series.

Fully open sparse MoE model with 7B total and about 1B active parameters.

Israel's AI21 hybrid Mamba-Transformer MoE, with a 256k context and strong long-document throughput.

Phi-3.5 mixture-of-experts model, scaling Microsoft's small-model line while preserving efficient active parameters.

Large Hermes 3 instruction-tuned model built on Meta's Llama 3.1 405B.

LG's first open-weight EXAONE model, a compact bilingual instruction model for Korean and English.

8B vision-language model for local image, multi-image, OCR, and video understanding, with llama.cpp and Ollama support.

Meta's first frontier-scale open Llama model, with 405B parameters, 128K context, multilingual support, and tool-use improvements.

Apache-licensed 12B model co-developed with NVIDIA, including a 128K context window and strong multilingual tokenization.

Second-generation Gemma model, improving open-weight quality and efficiency at 9B and 27B sizes.

Open code-focused MoE built from DeepSeek-V2, expanding programming-language coverage and coding benchmark performance.

NVIDIA's large open model family for synthetic data generation and reward modeling.

Qwen2's largest dense model, introducing stronger multilingual support, coding/math gains, and long-context variants.

Open GLM-4 9B model family, covering chat, long-context, and code-oriented variants.

Mistral's first code-specialized model, trained for code generation, fill-in-the-middle, and multi-language programming tasks.

Open multilingual research model covering 23 languages, released by Cohere For AI.

Yi 1.5 update with stronger instruction following, coding, math, and multilingual performance.

Falcon 2 generation, including text and vision-language 11B models under a permissive TII license.

DeepSeek's first major MoE general model with Multi-head Latent Attention and low-cost API positioning.

Apache-2.0 code model from IBM's Granite Code family, used for local code generation and enterprise coding assistants.

Apache-2.0 enterprise LLM with 480B total / 17B active parameters, optimized for SQL, code, and instruction following.

3.8B-parameter Phi-3 model released as a phone-capable small model with 4K and 128K variants.

First Llama 3 release, with 8B and 70B open models and a stronger tokenizer, data mix, and post-training stack.

Larger open Mixtral sparse MoE with 141B total and 39B active parameters, released under Apache-2.0.

Microsoft's WizardLM-2 MoE chat model, widely mirrored and run locally after its model-card release.

Open code-specialized Gemma model for local code completion, generation, and instruction-following.

First Jamba hybrid Transformer-Mamba MoE model with open weights and a 256K context length.

Databricks' 132B-total / 36B-active open MoE model for code, math, RAG, and enterprise self-hosted workloads.

Next-generation BigCode code model trained on 4T+ tokens and 600+ programming languages, with 16K context.

First Gemma open-weight text model family, derived from the same research lineage as Gemini.

Largest Qwen1.5 model, released as the bridge from the original Qwen line to Qwen2.

Ai2's first fully open language model release, including weights, training data, code, logs, and intermediate checkpoints.

Small multilingual Stable LM release built for low hardware barriers and local experimentation.

Early DeepSeek sparse MoE research model that foreshadowed the later V2/V3 architecture direction.

Nous instruction-tuned Mixtral model with strong open-chat and tool-use adoption.

Compact Mistral-based local chat model trained with C-RLFT, popular in early 2024 local leaderboards.

Compact Llama-style 1.1B chat model trained for local experimentation and low-memory deployments.

2.7B-parameter Phi model showing strong reasoning and language understanding at small scale.

Sarvam AI's first open Indic language model, adapted from Llama 2 for Hindi and Indian-language work.

The open sparse Mixture-of-Experts that brought MoE efficiency to the open ecosystem.

Alibaba's first major open Qwen model and the start of a prolific open-weight line.

First general DeepSeek language model family, with 7B and 67B base/chat checkpoints.

01.AI's strong bilingual open model, with a 200k-context variant.

xAI's first Grok model, later released as open weights with a 314B-parameter MoE checkpoint.

DeepSeek's first public code-model family, released before the general DeepSeek LLM line.

Open vision-language assistant and one of the most widely run early local multimodal models.

The 7B that punched far above its weight and put Mistral on the map.

Second open Qwen size, expanding the first-generation Qwen language-model lineup.

IBM's early Granite foundation model family for enterprise language and code tasks.

At launch the largest openly available model, from the UAE's TII.

Meta's first code-specialized Llama model family, released in base, Python, and instruction-tuned variants.

Alibaba's first open Qwen checkpoint and the start of the Qwen open-model line.

Early Nous Hermes instruction model on Llama 2, widely used in the open-model fine-tuning ecosystem.

The release that made capable open-weight models genuinely usable for production.

Second open ChatGLM generation, improving long context, inference efficiency, and bilingual chat quality.

Microsoft's first Phi small-language-model release, demonstrating strong code performance from textbook-quality synthetic data.

TII's breakout open Falcon model, released before Falcon 180B and trained on the RefinedWeb corpus.

MosaicML's permissively licensed 7B model, an early favorite for commercial local fine-tuning and long-context variants.

LMSYS instruction-tuned LLaMA model that became a landmark early local ChatGPT-style assistant.

Zhipu AI and Tsinghua KEG's first widely used open bilingual ChatGLM checkpoint.

Meta's first LLaMA, released to researchers; its leak catalyzed the open-weight movement.

A science-focused model whose public demo was withdrawn after just three days over confidently wrong outputs — an early, instructive retraction.

An open, multilingual 176B model (46 languages) from a global research collaboration.

Initially withheld over misuse fears, then fully released in Nov 2019 — an early 'limited release' debate.

The bidirectional encoder that reshaped NLP and seeded the transformer era.