Best AI Tools for AI Open Source

AI-powered IDE built as a fork of Visual Studio Code, designed with an 'agent-first' paradigm where autonomous AI agents plan, execute, and validate code. Features two primary views: Editor View (traditional IDE with agent sidebar) and Manager View (control center for orchestrating multiple parallel agents across workspaces). Agents generate verifiable 'Artifacts' including task lists, implementation plans, screenshots, and browser recordings. Supports multiple AI models including Gemini 3 Pro, Gemini 3 Deep Think, Gemini 3 Flash, Claude Sonnet 4.5, and open-source GPT variants. Agents have direct access to editor, terminal, and integrated browser, and learn from previous interactions.

Firecrawl is the industry-standard tool for turning entire websites into clean, LLM-ready markdown. It handles all the 'messy' parts of web scraping, including JavaScript rendering, proxy rotation, and anti-bot bypass, automatically. Designed specifically for AI developers, it can crawl entire domains and output structured data that is perfectly formatted for RAG (Retrieval-Augmented Generation) or fine-tuning. It acts as the bridge between the unstructured web and the structured needs of modern AI agents.

Moltbot (also known as Clawdbot) is the spearhead of the 'Invisible OS' movement, a shift away from fragmented apps and toward pure, autonomous execution via messaging. Operating entirely through WhatsApp and Telegram, Moltbot uses advanced reasoning to manage your digital life without a traditional UI. It handles complex, multi-service tasks like clearing your inbox, coordinating calendars, and managing travel logistics (including flight check-ins) autonomously. With persistent memory and a deep 'Persona Onboarding' process, it learns your work patterns and preferences, acting as a unified reasoning layer across your existing services.

Crawl4AI is an open-source, high-performance web crawling and scraping engine specifically optimized for large language models. It provides a robust, asynchronous architecture that can handle complex JavaScript-heavy websites, dynamic content, and multi-page crawls with ease. Unlike traditional scrapers, Crawl4AI focuses on 'semantic extraction', automatically identifying the core content of a page and converting it into structured markdown or JSON that is ready for RAG pipelines. It is designed to be deeply integrated into Python-based AI workflows, offering native support for Playwright and advanced proxy management.

ComfyUI is an open-source node-based interface for diffusion models. Instead of a prompt box, a generation is a graph: loaders, samplers, conditioning, upscalers and masks wired together, each step inspectable and re-runnable. Workflows save as JSON and can be shared, which is why most published Stable Diffusion and FLUX pipelines circulate as ComfyUI graphs.

Provides API access to thousands of machine learning models hosted on the Hugging Face Hub. Supports models for text generation, image generation, audio synthesis, computer vision, and more. Simple REST API for easy integration. Pay-per-use pricing based on model and compute requirements. Includes both open-source and proprietary models. Suitable for developers wanting access to the vast Hugging Face model ecosystem without local deployment. Offers inference endpoints for production use and serverless inference for quick testing.

High-performance inference platform providing ultra-fast API access to large language models and other AI models. Optimized for speed using custom hardware (LPU - Language Processing Unit). Supports popular open-source models including Llama, Mixtral, Mistral, and Gemma. Offers REST API with streaming support and extremely low latency. Focuses on speed optimization, making it ideal for real-time applications. Provides dedicated endpoints for specific models and shared infrastructure. Suitable for developers needing fast inference for production applications, chatbots, and real-time AI interactions. Pay-per-use pricing with competitive rates.

Kimi K3 is Moonshot AI's open-weight model released July 16, 2026, built at roughly 2.8 trillion parameters. It's available now via kimi.com, Kimi Work, Kimi Code, and the Kimi API, priced at $0.30 per million input tokens (cached), $3.00 per million (uncached), and $15.00 per million output tokens. Moonshot published the full open weights on Hugging Face on July 27, 2026, as promised at launch. Moonshot positions it as approaching Anthropic Fable 5-tier performance at a fraction of the cost, though the company acknowledges a tendency toward 'excessive proactivity' on long-running tasks.

Invoke is an open-source generative image platform combining a unified canvas with inpainting, outpainting and layer control, plus a node editor for building repeatable workflows. It can be self-hosted or used through a commercial hosted tier aimed at studios.

DeepSeek is the architect of the 'DeepSeek movement,' a fundamental shift in AI development that prioritizes extreme efficiency over raw compute. Founded by High-Flyer Quant, they proved that architectural innovations like Multi-head Latent Attention (MLA) and DeepSeekMoE could match the performance of $100B models like GPT-4o and Claude 3.5 while costing 95% less to train and run. Their ecosystem includes the flagship DeepSeek-V3, the reasoning-heavy DeepSeek-R1, and the state-of-the-art DeepSeek-VL2 for high-fidelity OCR and vision tasks. DeepSeek is committed to the open-source community, regularly releasing model weights and technical papers that have democratized frontier-level AI for developers globally.

Llama is Meta AI's open-source large language model family with multiple versions: Llama (February 2023), Llama 2 (July 2023), Llama 3 (April 2024), Llama 3.1 405B (405B parameters, July 2024), Llama 3.3 (December 2024), Llama 4 Maverick (April 2026), and Llama 4 Scout (April 2026). Designed for research and commercial use with strong performance across text generation, reasoning, and code tasks. Available in various sizes from 7B to 405B parameters. Supports multiple languages and extended context windows. Available through Meta's official channels, Hugging Face, and various cloud providers. Open-source licensing allows for local deployment and customization.

Mistral AI provides high-performance large language models with both open-source and commercial offerings. Models include Mistral 7B, Mistral 8x7B (Mixtral), Mistral Large, Mistral Large 2.1, Mistral Small, Pixtral (multimodal, 123B parameters), and the Magistral family (June 2026) - reasoning models designed for enhanced accuracy through increased computational power during inference. Designed for efficiency and performance with strong multilingual capabilities, particularly for European languages. Offers both open-source models for local deployment and commercial API access. Available through Mistral AI's platform, Hugging Face, and various cloud providers. Strong focus on European data privacy and compliance.

Qwen is Alibaba Cloud's family of large language models with multiple versions: Qwen-1.5 (February 2024), Qwen2 (2024), Qwen2.5 (January 3, 2026) with seven dense models from 0.5B to 72B parameters plus MoE variants, and Qwen3 (April 29, 2026) with variants Qwen3-Next, Qwen3-Max, and Qwen3-Omni focusing on context length scaling and parameter efficiency. Designed for multilingual applications with strong support for Chinese, English, and other languages. Excels at code generation, mathematical problem-solving, and structured data understanding. Pre-trained on significantly larger datasets than predecessors. Available through Alibaba Cloud API (DashScope), Hugging Face, and open-source model weights for local deployment. Offers both commercial API access and open-source licensing.

Microsoft Phi is a family of small, efficient language models designed for high performance with minimal parameters. Available models include Phi-1, Phi-2 (December 2023, 2.7B parameters), Phi-3 (April 2024), Phi-3.5, and Phi-4 (2026, 14B parameters) with variants: Phi-4-base, Phi-4-reasoning, Phi-4-reasoning-plus, and Phi-4-mini. Marketed as 'small language models' specializing in complex reasoning tasks. Optimized for reasoning tasks, code generation, and efficient inference. Released under MIT license for unrestricted use and modification. Available through Azure OpenAI Service, Hugging Face, and open-source model weights. Designed for edge devices, mobile applications, and cost-effective deployments.

SERA is a family of open-source coding agents developed by the Allen Institute for AI (AI2). It allows developers to customize and fine-tune models on private codebases without exposing sensitive data to external servers. SERA uses synthetic training data to achieve performance comparable to much larger proprietary models at a significantly lower cost.

Gemma is Google DeepMind's family of open-source large language models, serving as lightweight versions of Gemini. Available models include Gemma 1 (February 2024), Gemma 2 (June 2024), and Gemma 3 (March 2026) with variants like PaliGemma for vision-language tasks and MedGemma for medical applications. Available in multiple sizes (2B, 7B, and larger variants). Designed for research, education, and commercial applications with permissive licensing. Trained on similar data and methods as Gemini models but optimized for open-source deployment. Available through Hugging Face, Kaggle, and Google Cloud Vertex AI.

Kimi k1.5 is a multimodal large language model from Moonshot AI, specifically engineered for high-fidelity technical reasoning and long-context processing. It is a key player in the 'DeepSeek movement,' matching the reasoning performance of frontier models like GPT-5.2 Codex and Claude 4.5 while remaining significantly more cost-effective. It features a massive 2 million token context window and joint text-vision reasoning, making it ideal for complex coding, mathematical proofs, and large-scale document analysis. The model is built using advanced Reinforcement Learning (RL) to achieve deep 'Chain-of-Thought' capabilities.

Qwen 2.5-VL is Alibaba's state-of-the-art open-weight multimodal model, designed to bridge the gap between open source and proprietary vision-language models. It features advanced 'NaViVi' (Native Dynamic Resolution) architecture, allowing it to process images of any resolution and videos of any length with extreme precision. It excels at complex visual reasoning, document understanding (OCR), and real-time video analysis, matching or exceeding GPT-4o in many multimodal benchmarks while remaining fully open for the community to build upon.

DBRX is a mixture-of-experts transformer model developed by Databricks and Mosaic ML. Released on March 27, 2024, with 132 billion total parameters (36B active parameters per token). Available in base and instruction-tuned (dbrx-instruct) variants. Outperforms other open-source models in various benchmarks including language understanding, programming, and mathematics. Uses fine-grained mixture-of-experts (MoE) architecture with 16 experts and 4 active per token for efficient inference. Trained at approximately $10 million cost. Released under Databricks Open Model License (permissive for research and commercial use). Available through Databricks Foundation Models API, Hugging Face, and open-source model weights.

Llama 3.2 Vision is Meta's first open-weight multimodal model family, bringing high-fidelity image reasoning to the Llama ecosystem. It integrates vision and text into a unified transformer architecture, enabling it to understand images, charts, and diagrams with the same ease as text. Available in 11B and 90B versions, it is designed for efficiency and edge deployment, making it the industry standard for developers building open multimodal applications that require deep reasoning and broad community support.

Pixtral Large is Mistral AI's flagship 124B parameter multimodal model, designed to compete directly with GPT-4o and Claude 3.5 Sonnet. Built on the Mistral Large 2 foundation, it features a native vision encoder that allows it to reason across text and images with extreme precision. It excels at complex diagram understanding, mathematical reasoning with visual context, and high-fidelity image captioning. Pixtral Large is released under the Mistral Research License, allowing developers to explore frontier-level vision-language capabilities with open weights.

InternVL 2.5 is a world-class open-source multimodal large language model (MLLM) that consistently tops the leaderboards for open-weight vision reasoning. It features a powerful 78B parameter architecture with a specialized vision-language alignment that excels at OCR, document understanding, and complex visual Q&A. It is designed to bridge the gap between open models and GPT-4V, offering exceptional performance across a wide range of multimodal benchmarks while remaining fully open for community development.

OpenCode is an open-source terminal-based coding agent that connects to multiple language models and performs autonomous software engineering tasks from the command line. It edits files, runs tests, manages git workflows, and iterates on code with minimal human intervention. The v1.17.8 release from June 2026 improves tool calling reliability, multi-file refactoring, and support for local and remote model backends.

DeepSeek V4-Pro is a high-performance language model from DeepSeek. The model itself was released on April 24, 2026, and permanent pricing was announced on May 31, 2026. It offers strong reasoning and coding performance at a competitive price point, with open weights available for local deployment.

Generates high-quality videos with motion diversity from images using Wan 2.1 open-source model. Supports LoRA customization for fine-tuned control, enabling advanced users to adapt the model for specific styles and use cases. Provides full source code availability, allowing self-hosting, customization, and integration into custom workflows. Enables fine-tuning with LoRA (Low-Rank Adaptation) for specialized motion styles, character consistency, or domain-specific video generation.

High-quality image-to-video generation from Tencent using open-source Hunyuan Video models. Produces realistic motion, coherent scene dynamics, and production-ready video output with full source code availability. Provides open-source alternative with strong quality for self-hosting and customization. Supports both research and production use cases with comprehensive documentation and active community support. Enables complete control over the generation pipeline for advanced users.

Generates high-quality images from text prompts using Alibaba's Tongyi Qianwen 20-billion parameter MMDiT model. Excels at complex text rendering with commercial-grade quality, supporting multi-line layouts and paragraph-level text generation in both Chinese and English. Provides advanced image editing capabilities including style transfer, object insertion/removal, and detail enhancement. Ranks first in multiple public benchmark tests, surpassing similar open-source models with superior prompt understanding and visual quality.

FLUX.2 Pro is the definitive answer to closed-source image generators like Midjourney. Developed by Black Forest Labs (the original creators of Stable Diffusion), it represents the pinnacle of high-fidelity, open-weight image generation. It features a massive 12B parameter 'Flow' architecture that produces photorealistic textures, perfect human anatomy, and industry-leading text rendering. Unlike its competitors, FLUX is built for the open-source community, supporting LoRA training, ControlNet, and local deployment, allowing creators to maintain full control over their artistic style and data.

Alibaba's latest open-weight model specialized for coding. At 80B parameters, it matches proprietary performance for local development and autonomous coding agents.

An open-source research stack spanning Python, JS, C++, and CUDA, engineered from the ground up by autonomous AI coding agents. Optimized for high-performance tensor operations.

Supabase provides a unified backend stack including a Postgres database, authentication, and storage. Their native Vector support makes it the premier choice for building RAG-based AI applications.

Now integrated with Cloudflare's global network, Replicate allows you to run and fine-tune open-source models (Flux, Llama, Whisper) with a single API call and zero infrastructure management.

SAM3D v2 leverages Meta's latest Segment Anything technology to reconstruct 3D geometry from single or multiple images with extreme precision. It is the industry standard for research-grade 3D reconstruction.

Qwen 3 is a 2025 open-weight Mixture-of-Experts model family from Alibaba Cloud, ranging from 0.6B to 235B parameters. It supports both thinking and non-thinking modes, strong multilingual performance, and agentic tool use, and is released under permissive licenses.

Qwen 2.5-Coder is a code-focused open-weight model from Alibaba, available in sizes from 1.5B to 32B parameters. It is optimized for code generation, completion, and debugging across many programming languages and is competitive with closed coding models.

Qwen-Math is a family of open-weight models specialized for mathematical reasoning and problem solving, derived from Qwen 2.5 and optimized on math datasets. It is available in several sizes and is competitive on math benchmarks.

Wan 2.0 is an earlier open-source video generation model from Alibaba, predecessor to Wan 2.1. It supports text-to-video and image-to-video generation and laid the groundwork for the Wan family's open-source release.

FLUX.2 [schnell] is the fastest open-weights FLUX.2 variant, designed for 4-8 step local inference on consumer hardware. It retains strong prompt adherence and text rendering while being freely available for local and commercial use.

FLUX.2 [dev] is an open-weight FLUX.2 model from Black Forest Labs, released for non-commercial and commercial research. It offers a strong balance of quality and efficiency, making it the base for many fine-tunes and community LoRAs.

BRIA FIBO is an 8B-parameter DiT text-to-image model trained on long structured JSON captions. It turns short prompts into detailed structured schemas and generates images with precise, reproducible control over composition, lighting, camera, and color. It is also available in an image-to-image 'Inspire' mode and is trained entirely on licensed data for commercial safety.

BRIA FIBO Lite is a lightweight variant of the FIBO image generation pipeline. It pairs an open-source FIBO-VLM bridge with a smaller FIBO Lite model to enable rapid inference and fully local, on-prem deployment for privacy-critical environments.

DeepSeek V4-Flash is the efficient sibling of V4-Pro, offering a 1M-token context window and configurable thinking modes at a fraction of the API cost. It is optimized for high-throughput chat, classification, bulk extraction, and agentic coding workloads, with a July 2026 update that boosted agent and coding benchmarks.

DeepSeek R1 is a 671B-parameter open-weight reasoning model that matches o1-class performance on math, code, and logic benchmarks through reinforcement learning on verifiable tasks. It exposes chain-of-thought reasoning and is available as MIT-licensed local weights and via API, with the R1-0528 update in May 2025 further improving math and code reasoning.

DeepSeek V3.2 is a 128K-context mixture-of-experts model that unified thinking and non-thinking modes in the V3 line and introduced DeepSeek Sparse Attention. It served as the December 2025 flagship before V4 and remains available for self-hosting and as a historical comparison point.

GLM-5 is Zhipu AI's (Z.ai) first 2026 flagship, a 744B-parameter sparse mixture-of-experts model with roughly 40B active parameters per token. It is built for high-intelligence reasoning, agentic planning, and long-context execution, with a 200K context window and 128K maximum output.

GLM-5.1 is Z.ai's refinement flagship released in April 2026, a 744B-parameter MoE model with 40B active parameters per token. It targets long-horizon agentic coding, multi-file refactoring, and terminal work, sustaining up to 8-hour autonomous tasks through a 200K context window and 128K maximum output.

Gemma 3 is an open-weights family of multimodal models from Google, ranging from 1B to 27B parameters. It supports text and image input, a 128K context window, and is released under a permissive license for research and commercial use.

Open-source Transformer-based Mixture-of-Experts language model with 389 billion total parameters and 52 billion active parameters. Supports instruction-tuned and long-context pretraining checkpoints up to 256K tokens, distributed via Hugging Face and GitHub.

A 200K-context open-weight Hunyuan model optimized for speed while maintaining strong performance on general chat, coding, and agentic tasks. It also serves as the base for the Hunyuan T1 reasoning model.

Open-weight instruction-tuned variant of Tencent's Hunyuan 2.0 series, offering a 131K-token context window and strong everyday performance for chat, content creation, coding, and enterprise workflows.

Open-weight reasoning variant of Hunyuan 2.0 with a 131K context window, designed for complex problem-solving, math, and long-context reasoning workflows.

A compact open-weight MoE instruction model with a 131K context window, listed as a cost-efficient everyday Hunyuan option via OpenRouter and Tencent Cloud.

Open-weight preview of Hunyuan 3 (Hy3), a 295B-parameter MoE model with 21B active parameters and a 262K context window. Supports reasoning, function calling, and tool use, and is available via OpenRouter and Tencent Cloud TI Platform.

Open-source text-to-image diffusion transformer with fine-grained Chinese and English understanding, multi-turn prompt refinement, ControlNet, LoRA, and IP-Adapter support. Available via Hugging Face, Diffusers, ComfyUI, and a web demo.

Native multimodal MoE image generation model with 80 billion total parameters and 13 billion active parameters. It unifies multimodal understanding and generation within an autoregressive framework, supports image editing and multi-image fusion, and is released as the largest open-source image generation model.

Generates explorable, interactive 3D worlds from text prompts or images using panoramic proxies and semantic layering. Supports mesh export for game engines, VR/AR, and interactive content creation.

Open-source system for generating high-resolution textured 3D assets from text or images. Includes a shape-generation diffusion transformer, texture synthesis pipeline, PBR support, and a Blender add-on, with mini and multiview variants for different hardware.

Kimi K2.5 is Moonshot AI's open-weight multimodal model released January 27, 2026. It supports text, image, and video input, thinking and non-thinking modes, and a 256K context window, with strong performance on agent, coding, and vision tasks. Moonshot announced the kimi-k2.5 API will be retired on August 31, 2026, so production workloads should plan a migration path to K2.6 or K3.

Kimi K2.6 is Moonshot AI's open-weight multimodal model released April 21, 2026. It supports text, image, and video input, thinking and non-thinking modes, and a 256K context window, with improved long-context coding stability and agent-task performance.

Llama 4 Maverick is Meta's flagship open-weight model, released in April 2025 as part of the Llama 4 family. It uses a Mixture-of-Experts architecture with 17B active parameters and around 400B total parameters, natively understands text and images, and supports a 1M-token context window.

Llama 4 Scout is Meta's efficient Llama 4 variant, released in April 2025. It is a Mixture-of-Experts model with 17B active parameters and 109B total parameters across 16 experts, natively multimodal for text and images, and supports an industry-leading 10M-token context window.

Llama 3.3 is Meta's 70B-parameter multilingual instruction-tuned model, released in December 2024. It delivers text-only performance comparable to the much larger Llama 3.1 405B model while running far more efficiently, with a 128K-token context window and broad language support.

Llama 3.1 405B is Meta's 405-billion-parameter dense open-weight model, released in July 2024. It was the first openly available model to reach frontier-level performance on reasoning, coding, and multilingual tasks, with a 128K-token context window and native tool-use support.

A 675B-parameter sparse mixture-of-experts model with 41B active parameters and a 262K context window, released under Apache 2.0. It handles text and vision tasks, supports strong multilingual performance, and is designed for both research and enterprise deployment.

A 119B-parameter MoE model with 6B active parameters and a 256K context window, released under Apache 2.0. It unifies instruct, reasoning, multimodal, and agentic coding capabilities in a single efficient model with configurable reasoning effort.

A family of 3B, 8B, and 14B parameter dense models released under Apache 2.0, optimized for performance-to-cost ratio at the edge. The 14B variant includes reasoning capabilities, making the family suitable for on-device and local deployments.

A family of open-weight speech models including a 24B production variant and a 3B edge variant, released under Apache 2.0. It supports transcription, audio understanding, summarization, Q&A, and function calling from voice with multilingual support.

A 30B total / 3B active parameter hybrid Mamba-2 + Transformer MoE language model built for efficient on-device and edge agentic tasks. It features a 1M-token context window, reasoning ON/OFF modes with configurable thinking budgets, and up to 4× faster throughput than its predecessor.

A 120B total / 12B active parameter hybrid Mamba-Transformer MoE language model with LatentMoE, multi-token prediction, and native NVFP4 pretraining. Optimized for complex multi-agent applications with a 1M-token context window and up to 5× higher throughput than the previous Nemotron Super.

An 8B-class physical-AI omni-model (8B reasoner + 8B generator) optimized for efficient inference on workstation-grade NVIDIA hardware such as the RTX PRO 6000. It unifies vision reasoning, world generation, and action prediction for robotics and physical AI prototyping.

A 4B-class physical-AI omni-model (2B reasoner + 2B generator) optimized for real-time robotic policy and visual reasoning at the edge. It unifies world generation, vision reasoning, and action prediction in a compact form factor for embedded deployment.

A 253B-parameter variant of Llama 3.1 fine-tuned by NVIDIA using the HelpSteer2 datasets to improve helpfulness and instruction adherence. It is the largest member of the Llama-3.1-Nemotron family of community collaboration models.

A 49B-parameter variant of Llama 3.1 fine-tuned by NVIDIA using the HelpSteer2 datasets to improve helpfulness and instruction adherence. It is the mid-size member of the Llama-3.1-Nemotron family, optimized for a strong performance-to-size ratio.

An 8B-parameter variant of Llama 3.1 fine-tuned by NVIDIA using the HelpSteer2 datasets to improve helpfulness and instruction adherence. It is the smallest member of the Llama-3.1-Nemotron family, optimized for efficient on-device and edge deployment.

NVIDIA's open foundation model for humanoid robot reasoning and control, combining an Eagle-based vision-language backbone with a diffusion transformer (DiT) action head for language-conditioned manipulation across diverse embodiments.

Stable Diffusion 1.5 is the landmark open-source latent diffusion model released by Stability AI in 2022. It established the open image generation ecosystem and remains the base for countless fine-tunes, LoRAs, and ControlNet models.

Stable Diffusion XL (SDXL) is a 2023 open-source text-to-image model that generates higher-quality, higher-resolution images than SD 1.5. It uses a two-stage base-plus-refiner pipeline and is widely used for production image workflows.

Stable Diffusion XL Turbo is a distilled, fast variant of SDXL that can generate images in a single step or a few steps. It is optimized for low-latency applications and real-time interactive generation.

Stable Diffusion 3 Medium is a 2B-parameter version of SD3 designed to run well on consumer GPUs. It offers a balance of SD3 quality and efficiency, making it accessible for local creators.

Stable Diffusion 3.5 Large is an 8B-parameter open-weights model in the SD 3.5 family, offering the highest quality and best prompt adherence of the 3.5 series for demanding image generation tasks.

TRELLIS Mini is a smaller, faster variant of the TRELLIS family from Microsoft Research, designed for efficient image-to-3D generation on limited hardware while preserving the core architecture's quality.

TRELLIS Large is the larger, higher-quality variant of the TRELLIS family, producing detailed 3D assets from single images with better geometry and texture fidelity than the smaller variants.

TripoSR is an open-source, feed-forward image-to-3D model developed by Stability AI and Tripo AI. It generates textured 3D meshes from a single image in under a second on a single GPU and is released under an MIT license.

NanoClaw is an open-source personal AI agent runtime built by Gavriel Cohen as a smaller, auditable alternative to OpenClaw. Each agent session runs in its own Docker container with scoped permissions and self-destructs when the task ends. In August 2026 it added a Slack integration that lets you provision persistent AI agent teams and colleagues from a single message, running on customer infrastructure.

Generates images from text with open-source flexibility and community support using Stable Diffusion 3.5 model. Provides extensive customization options, community models, LoRA support, and self-hosting capabilities for complete workflow control. Latest version of the Stable Diffusion ecosystem with improved quality, better prompt understanding, and enhanced capabilities. Supports local deployment, API access, and extensive community ecosystem with thousands of custom models and tools.

TRELLIS 2 is an open-source image-to-3D generation model from Microsoft Research, released in 2026. It reconstructs 3D assets from single images or text prompts and is designed for research and experimentation.

Publishes the FLUX family of state-of-the-art image generation models including FLUX.1, FLUX.1-dev, FLUX.2, and specialized variants. Provides open-source models with exceptional quality and prompt adherence for modern image generation workflows. FLUX models represent cutting-edge diffusion technology with superior text rendering, style control, and image quality. Offers multiple model variants optimized for different use cases including speed, quality, and specialized applications.

NVIDIA Cosmos 3 is an open physical-AI omnimodel released around May 31 to June 1, 2026. It generates video, 3D, and physical-world simulations to train and evaluate robotics and autonomous vehicle systems without expensive real-world data collection.

Snowflake AI Gateway is an enterprise inference routing layer released September 2026. It intelligently routes queries to the most cost-effective model that meets quality requirements. Users define acceptable accuracy/latency thresholds, and the gateway automatically chooses between Claude, GPT, Gemini, or open-source alternatives based on current pricing and performance. Uses machine learning to predict which model is optimal for each query pattern. Integrated directly into Snowflake SQL and Python notebooks.

Alibaba released a 7-billion parameter language model optimized for consumer laptop deployment, released August 2026. Quantized to 4-bit with custom ONNX optimization for CPU/GPU inference. Competitive response to Meta's on-device model strategy, targeting Windows/Mac laptops with 8GB+ RAM. Open weights under OpenMDW-1.1 license. Achieves reasonable performance on everyday tasks (email drafting, code generation) while running entirely offline without cloud dependency.

LTX-2.5 is an open-weights video and world model from Lightricks (LTX company spun out of Lightricks), released August 2026. Generates 10-second video clips from images in 6.8 seconds on Nvidia superchips. Features multi-shot support, diffusion decoder for higher quality, new conditioning modes, and autoregressive models for real-time use and robotics. Weights freely available on Hugging Face under OpenMDW-1.1 license. 33 million downloads, most-used open world model line on the market. Free for organizations under $10 million annual revenue; larger companies negotiate licenses.

Google Gemma is a family of open-source language models available in 2B, 7B, and 27B parameter sizes. Trained on 6 trillion tokens of high-quality data, designed for efficient local deployment. Includes standard and instruction-tuned variants. Reached 1 billion total downloads across Hugging Face, Kaggle, and GitHub by August 2026. Has spawned 100,000+ community derivatives (finetuned versions, specialized variants, quantizations). Available under Google DeepMind's permissive license for commercial and research use.

Generates 3D objects from text prompts or images using OpenAI's Shap-E model, a conditional generative model for 3D assets. Produces high-quality 3D meshes, point clouds, and neural radiance fields (NeRFs) from natural language descriptions. Supports both text-to-3D and image-to-3D workflows, generating detailed 3D models with realistic geometry and textures suitable for game assets, product visualization, and 3D printing applications. Open-source model with comprehensive documentation and active community support, making it ideal for research, prototyping, and educational use.

Muse Glimmer is Meta's 30 billion parameter open-weight model released August 2026, designed to run autonomous AI agents directly on consumer hardware without cloud dependency. It ships under the permissive Apache 2.0 license (Meta's first fully open release since moving to proprietary Muse Spark in April), quantized to roughly 4 bits with block-level speculative decoding for fast local inference. Drops the 700M monthly user restriction that hampered prior Llama releases.

Laguna S 2.1 is a 118 billion parameter Mixture-of-Experts model from Poolside AI, released August 2026. Activates only 8 billion parameters per token, supports context windows up to 1 million tokens, runs under permissive OpenMDW-1.1 license. Benchmarks: 70.2% on Terminal-Bench 2.1 (beating DeepSeek-V4-Pro-Max, Nvidia Nemotron 3 Ultra), 78.5% on SWE-Bench Multilingual. Trained in under 9 weeks on 4,096 Nvidia H200 GPUs.

Baidu ERNIE 4.5 (Enhanced Representation through Knowledge Integration) is a family of large language models released by Baidu in November 2026. The ERNIE 4.5 model family includes 10 variants ranging from 0.3 billion to 424 billion total parameters, utilizing a Mixture-of-Experts (MoE) architecture for efficient inference. Open-sourced under the Apache 2.0 license in June 2026, ERNIE 4.5 demonstrates strong performance in Chinese natural language processing, multimodal understanding, and various AI benchmarks. The model excels in common-sense reasoning, optical character recognition, and Chinese language tasks. Available through ERNIE Bot (web interface) and Baidu's Qianfan platform (API access), with open-source model weights available for local deployment.

GLM-4.5 (General Language Model) is Zhipu AI's latest large language model in the ChatGLM/GLM series, released in 2026. Building on the success of previous GLM models, GLM-4.5 offers enhanced reasoning capabilities, improved multilingual support (with strong Chinese and English capabilities), and advanced instruction-following. The model is designed for both chat and completion tasks, with support for long context windows and fine-tuned variants for specific use cases. GLM-4.5 maintains Zhipu AI's focus on efficient inference and cost-effective deployment. Available through Zhipu AI's platform (web interface and API) with options for local deployment of open-source variants.

GLM-5.3 is Z.ai's flagship coding and agentic model, released 14 August 2026. It uses the same 743B-parameter mixture-of-experts base as GLM-5.2, with Z.ai attributing the gains to scaled post-training rather than a new pre-training run. It targets long-horizon agentic coding, business-process automation, defensive security work and tasks that span many steps. The model supports three reasoning-effort levels and a 1M-token route for coding plans.

Hymotion 1.0 (also known as HY-Motion 1.0 or Hunyuan Motion 1.0) is Tencent's open-source, billion-parameter text-to-3D motion generation model released in December 2026. Built on a Diffusion Transformer (DiT) architecture with flow matching, it generates high-fidelity, smooth, and diverse 3D character animations from natural language descriptions. Trained on over 3,000 hours of diverse motion data covering 200+ motion categories including locomotion, sports, fitness, social interactions, and daily activities. The model employs a three-stage training paradigm: large-scale pretraining, high-quality fine-tuning with 400 hours of curated text-motion pairs, and reinforcement learning for physical plausibility. Supports standard 3D formats (FBX, BVH, GLTF) for seamless integration with...

Nemotron 3 Ultra is the largest member of NVIDIA's Nemotron 3 family, released 4 June 2026 at Computex. It is a 550B-parameter hybrid latent mixture of experts with roughly 55B parameters active per token, combining Mamba and Transformer blocks, and trained in NVIDIA's 4-bit NVFP4 format on Blackwell hardware. It ships under the NVIDIA Open Model License, which permits commercial use, and NVIDIA published training data, reinforcement learning environments and post-training recipes alongside the weights rather than the weights alone. Weights are on Hugging Face as nvidia/NVIDIA-Nemotron-3-Ultra-550B-A55B in both BF16 and NVFP4, and it is served through OpenRouter, Together AI, Baseten, DeepInfra, Fireworks and NVIDIA NIM.

FLUX 3 is Black Forest Labs' multimodal foundation model, announced 23 July 2026. Unlike the FLUX.1 and FLUX.2 image models before it, FLUX 3 learns jointly across images, video and audio in a single unified architecture: it generates video with native synchronised audio, edits images, renders readable text, and, via a FLUX-mimic variant, predicts robot actions, all from the same weights. Video generation runs up to 20 seconds. At launch, video is available through a gated early-access programme, with image generation stated to follow and an open-weight FLUX 3 Dev backbone planned later.

Qwen 3.8-Max is Alibaba's largest model yet, announced July 19, 2026, at 2.4 trillion total parameters using a sparse Mixture-of-Experts design. It's multimodal (text, images, video, documents) with a context window in the ~1M-token range (983,616 tokens per Qwen Cloud metadata) and a 131,072-token max output. It's live now as qwen3.8-max-preview through Alibaba's Token Plan, Qoder, and QoderWork at 10% of eventual standard pricing, targeting coding, agentic workflows, and long-horizon 'professional cowork' tasks. Alibaba says open weights are coming but hasn't published a date, license, model card, or full benchmark table yet; the independent number available is Artificial Analysis, which places the preview at 53.4 on its Intelligence Index, rank 11.

GLM-5.2 is Zhipu AI's (Z.ai) flagship open-weight model, released 13 June 2026 under an MIT licence with weights published on Hugging Face at zai-org/GLM-5.2. It is a 753B-parameter mixture-of-experts model activating roughly 40B parameters per token, with a 1M-token context window and 128K maximum output. The headline architectural change is IndexShare, which reuses the same indexer across every four sparse attention layers; Z.ai reports this cuts per-token compute by about 2.9x at full 1M context. It targets long-horizon agentic coding, multi-file refactors, terminal work, and tasks that run for many steps rather than single completions.

Inkling is the first open-weights model from Thinking Machines Lab, released 15 July 2026 under Apache 2.0. It is a 975B-parameter mixture of experts with 41B active per token, trained from scratch on 45 trillion tokens of text, images, audio and video, with a context window up to 1M tokens. The architecture uses 256 routed experts plus 2 shared experts per layer with 6 routed experts active per token, a sigmoid router, and interleaved sliding-window and global attention at a 5:1 ratio. It accepts text, image and audio input natively and returns text. Weights are on Hugging Face in both the original format and an NVFP4 checkpoint for Blackwell hardware. A distilled Inkling-Small followed on 31 July.