Compare the Top Free AI Coding Models as of November 2026 - Page 2

  • 1
    Mistral Large 4
    Mistral Large 4 is a general-purpose multimodal language model available through Mistral’s hosted inference API. It combines instruction following, reasoning and agentic capabilities, and accepts image and text inputs. Developers can use it for chat completion, structured outputs, function calling, document question answering, tool-assisted workflows and other application features. Its documented use cases include conversational assistants, coding and software engineering agents, cybersecurity analysis, finance and legal workflows, scientific research, data extraction, summarization, and analysis of documents, charts and images. Mistral Large 4 is designed for developers, researchers, businesses and public-sector teams building AI-powered applications across industries such as engineering, manufacturing, finance, logistics and science.
    Starting Price: $1.36 per 1M input tokens
  • 2
    DeepSeek-V4.1-Flash-1017
    DeepSeek-V4.1-Flash-1017 is an open-weight multimodal artificial intelligence model developed by DeepSeek for advanced reasoning, software engineering, visual understanding, and autonomous AI agent workflows. Released on October 17, 2026, it builds on DeepSeek-V4.1-Flash with improvements in coding performance, agentic task execution, and reasoning efficiency. The model supports text and image inputs, tool calling, configurable reasoning effort, and multistep problem-solving. Its one-million-token context window enables developers to process lengthy documents, extensive codebases, and complex sequences of instructions. DeepSeek-V4.1-Flash-1017 also supports end-to-end software development, including application generation, debugging, automated testing, and interactive project creation. The model is available through the DeepSeek API and downloadable weights under the MIT License, supporting both hosted and self-managed deployment.
    Starting Price: Free
  • 3
    Qwen

    Qwen

    Alibaba

    Qwen is a powerful, free AI assistant built on the advanced Qwen model series, designed to help anyone with creativity, research, problem-solving, and everyday tasks. While Qwen Chat is the main interface for most users, Qwen itself powers a broad range of intelligent capabilities including image generation, deep research, website creation, advanced reasoning, and context-aware search. Its multimodal intelligence enables Qwen to understand and process text, images, audio, and video simultaneously for richer insights. Qwen is available on web, desktop, and mobile, ensuring seamless access across all devices. For developers, the Qwen API provides OpenAI-compatible endpoints, making integration simple and allowing Qwen’s intelligence to power apps, services, and automation. Whether you're chatting through Qwen Chat or building with the Qwen API, Qwen delivers fast, flexible, and highly capable AI support.
    Starting Price: Free
  • 4
    GPT-4o mini
    A small model with superior textual intelligence and multimodal reasoning. GPT-4o mini enables a broad range of tasks with its low cost and latency, such as applications that chain or parallelize multiple model calls (e.g., calling multiple APIs), pass a large volume of context to the model (e.g., full code base or conversation history), or interact with customers through fast, real-time text responses (e.g., customer support chatbots). Today, GPT-4o mini supports text and vision in the API, with support for text, image, video and audio inputs and outputs coming in the future. The model has a context window of 128K tokens, supports up to 16K output tokens per request, and has knowledge up to October 2023. Thanks to the improved tokenizer shared with GPT-4o, handling non-English text is now even more cost effective.
  • 5
    Gemini 2.0
    Gemini 2.0 is an advanced AI-powered model developed by Google, designed to offer groundbreaking capabilities in natural language understanding, reasoning, and multimodal interactions. Building on the success of its predecessor, Gemini 2.0 integrates large language processing with enhanced problem-solving and decision-making abilities, enabling it to interpret and generate human-like responses with greater accuracy and nuance. Unlike traditional AI models, Gemini 2.0 is trained to handle multiple data types simultaneously, including text, images, and code, making it a versatile tool for research, business, education, and creative industries. Its core improvements include better contextual understanding, reduced bias, and a more efficient architecture that ensures faster, more reliable outputs. Gemini 2.0 is positioned as a major step forward in the evolution of AI, pushing the boundaries of human-computer interaction.
    Starting Price: Free
  • 6
    DeepSeek R1

    DeepSeek R1

    DeepSeek

    DeepSeek-R1 is an advanced open-source reasoning model developed by DeepSeek, designed to rival OpenAI's Model o1. Accessible via web, app, and API, it excels in complex tasks such as mathematics and coding, demonstrating superior performance on benchmarks like the American Invitational Mathematics Examination (AIME) and MATH. DeepSeek-R1 employs a mixture of experts (MoE) architecture with 671 billion total parameters, activating 37 billion parameters per token, enabling efficient and accurate reasoning capabilities. This model is part of DeepSeek's commitment to advancing artificial general intelligence (AGI) through open-source innovation.
    Starting Price: Free
  • 7
    Grok 3 Think
    Grok 3 Think, the latest iteration of xAI's AI model, is designed to enhance reasoning capabilities using advanced reinforcement learning. It can think through complex problems for extended periods, from seconds to minutes, improving its answers by backtracking, exploring alternatives, and refining its approach. This model, trained on an unprecedented scale, delivers remarkable performance in tasks such as mathematics, coding, and world knowledge, showing impressive results in competitions like the American Invitational Mathematics Examination. Grok 3 Think not only provides accurate solutions but also offers transparency by allowing users to inspect the reasoning behind its decisions, setting a new standard for AI problem-solving.
    Starting Price: Free
  • 8
    Codestral Mamba
    As a tribute to Cleopatra, whose glorious destiny ended in tragic snake circumstances, we are proud to release Codestral Mamba, a Mamba2 language model specialized in code generation, available under an Apache 2.0 license. Codestral Mamba is another step in our effort to study and provide new architectures. It is available for free use, modification, and distribution, and we hope it will open new perspectives in architecture research. Mamba models offer the advantage of linear time inference and the theoretical ability to model sequences of infinite length. It allows users to engage with the model extensively with quick responses, irrespective of the input length. This efficiency is especially relevant for code productivity use cases, this is why we trained this model with advanced code and reasoning capabilities, enabling it to perform on par with SOTA transformer-based models.
    Starting Price: Free
  • 9
    Mistral NeMo

    Mistral NeMo

    Mistral AI

    Mistral NeMo, our new best small model. A state-of-the-art 12B model with 128k context length, and released under the Apache 2.0 license. Mistral NeMo is a 12B model built in collaboration with NVIDIA. Mistral NeMo offers a large context window of up to 128k tokens. Its reasoning, world knowledge, and coding accuracy are state-of-the-art in its size category. As it relies on standard architecture, Mistral NeMo is easy to use and a drop-in replacement in any system using Mistral 7B. We have released pre-trained base and instruction-tuned checkpoints under the Apache 2.0 license to promote adoption for researchers and enterprises. Mistral NeMo was trained with quantization awareness, enabling FP8 inference without any performance loss. The model is designed for global, multilingual applications. It is trained on function calling and has a large context window. Compared to Mistral 7B, it is much better at following precise instructions, reasoning, and handling multi-turn conversations.
    Starting Price: Free
  • 10
    Mixtral 8x22B

    Mixtral 8x22B

    Mistral AI

    Mixtral 8x22B is our latest open model. It sets a new standard for performance and efficiency within the AI community. It is a sparse Mixture-of-Experts (SMoE) model that uses only 39B active parameters out of 141B, offering unparalleled cost efficiency for its size. It is fluent in English, French, Italian, German, and Spanish. It has strong mathematics and coding capabilities. It is natively capable of function calling; along with the constrained output mode implemented on la Plateforme, this enables application development and tech stack modernization at scale. Its 64K tokens context window allows precise information recall from large documents. We build models that offer unmatched cost efficiency for their respective sizes, delivering the best performance-to-cost ratio within models provided by the community. Mixtral 8x22B is a natural continuation of our open model family. Its sparse activation patterns make it faster than any dense 70B model.
    Starting Price: Free
  • 11
    Tülu 3
    Tülu 3 is an advanced instruction-following language model developed by the Allen Institute for AI (Ai2), designed to enhance capabilities in areas such as knowledge, reasoning, mathematics, coding, and safety. Built upon the Llama 3 Base, Tülu 3 employs a comprehensive four-stage post-training process: meticulous prompt curation and synthesis, supervised fine-tuning on a diverse set of prompts and completions, preference tuning using both off- and on-policy data, and a novel reinforcement learning approach to bolster specific skills with verifiable rewards. This open-source model distinguishes itself by providing full transparency, including access to training data, code, and evaluation tools, thereby closing the performance gap between open and proprietary fine-tuning methods. Evaluations indicate that Tülu 3 outperforms other open-weight models of similar size, such as Llama 3.1-Instruct and Qwen2.5-Instruct, across various benchmarks.
    Starting Price: Free
  • 12
    Kimi K2

    Kimi K2

    Moonshot AI

    Kimi K2 is a state-of-the-art open source large language model series built on a mixture-of-experts (MoE) architecture, featuring 1 trillion total parameters and 32 billion activated parameters for task-specific efficiency. Trained with the Muon optimizer on over 15.5 trillion tokens and stabilized by MuonClip’s attention-logit clamping, it delivers exceptional performance in frontier knowledge, reasoning, mathematics, coding, and general agentic workflows. Moonshot AI provides two variants, Kimi-K2-Base for research-level fine-tuning and Kimi-K2-Instruct pre-trained for immediate chat and tool-driven interactions, enabling both custom development and drop-in agentic capabilities. Benchmarks show it outperforms leading open source peers and rivals top proprietary models in coding tasks and complex task breakdowns, while its 128 K-token context length, tool-calling API compatibility, and support for industry-standard inference engines.
    Starting Price: Free
  • 13
    Grok Code Fast 1
    Grok Code Fast 1 is a high-speed, economical reasoning model designed specifically for agentic coding workflows. Unlike traditional models that can feel slow in tool-based loops, it delivers near-instant responses, excelling in everyday software development tasks. Built from scratch with a programming-rich corpus and refined on real-world pull requests, it supports languages like TypeScript, Python, Java, Rust, C++, and Go. Developers can use it for everything from zero-to-one project building to precise bug fixes and codebase Q&A. With optimized inference and caching techniques, it achieves impressive responsiveness and a 90%+ cache hit rate when integrated with partners like GitHub Copilot, Cursor, and Cline. Offered at just $0.20 per million input tokens and $1.50 per million output tokens, Grok Code Fast 1 strikes a strong balance between speed, performance, and affordability.
    Starting Price: $0.20 per million input tokens
  • 14
    Kimi K2 Thinking

    Kimi K2 Thinking

    Moonshot AI

    Kimi K2 Thinking is an advanced open source reasoning model developed by Moonshot AI, designed specifically for long-horizon, multi-step workflows where the system interleaves chain-of-thought processes with tool invocation across hundreds of sequential tasks. The model uses a mixture-of-experts architecture with a total of 1 trillion parameters, yet only about 32 billion parameters are activated per inference pass, optimizing efficiency while maintaining vast capacity. It supports a context window of up to 256,000 tokens, enabling the handling of extremely long inputs and reasoning chains without losing coherence. Native INT4 quantization is built in, which reduces inference latency and memory usage without performance degradation. Kimi K2 Thinking is explicitly built for agentic workflows; it can autonomously call external tools, manage sequential logic steps (up to and typically between 200-300 tool calls in a single chain), and maintain consistent reasoning.
    Starting Price: Free
  • 15
    Mistral Large 3
    Mistral Large 3 is a next-generation, open multimodal AI model built with a powerful sparse Mixture-of-Experts architecture featuring 41B active parameters out of 675B total. Designed from scratch on NVIDIA H200 GPUs, it delivers frontier-level reasoning, multilingual performance, and advanced image understanding while remaining fully open-weight under the Apache 2.0 license. The model achieves top-tier results on modern instruction benchmarks, positioning it among the strongest permissively licensed foundation models available today. With native support across vLLM, TensorRT-LLM, and major cloud providers, Mistral Large 3 offers exceptional accessibility and performance efficiency. Its design enables enterprise-grade customization, letting teams fine-tune or adapt the model for domain-specific workflows and proprietary applications. Mistral Large 3 represents a major advancement in open AI, offering frontier intelligence without sacrificing transparency or control.
    Starting Price: Free
  • 16
    Kimi K2.5

    Kimi K2.5

    Moonshot AI

    Kimi K2.5 is a next-generation multimodal AI model designed for advanced reasoning, coding, and visual understanding tasks. It features a native multimodal architecture that supports both text and visual inputs, enabling image and video comprehension alongside natural language processing. Kimi K2.5 delivers open-source state-of-the-art performance in agent workflows, software development, and general intelligence tasks. The model offers ultra-long context support with a 256K token window, making it suitable for large documents and complex conversations. It includes long-thinking capabilities that allow multi-step reasoning and tool invocation for solving challenging problems. Kimi K2.5 is fully compatible with the OpenAI API format, allowing developers to switch seamlessly with minimal changes. With strong performance, flexibility, and developer-focused tooling, Kimi K2.5 is built for production-grade AI applications.
    Starting Price: Free
  • 17
    GLM-5

    GLM-5

    Z.ai

    GLM-5 is Z.ai’s latest large language model built for complex systems engineering and long-horizon agentic tasks. It scales significantly beyond GLM-4.5, increasing total parameters and training data while integrating DeepSeek Sparse Attention to reduce deployment costs without sacrificing long-context capacity. The model combines enhanced pre-training with a new asynchronous reinforcement learning infrastructure called slime, improving training efficiency and post-training refinement. GLM-5 achieves best-in-class performance among open-source models across reasoning, coding, and agent benchmarks, narrowing the gap with leading frontier models. It ranks highly on evaluations such as Vending Bench 2, demonstrating strong long-term planning and operational capabilities. The model is open-sourced under the MIT License.
    Starting Price: Free
  • 18
    Composer 2
    Composer 2 is an advanced AI coding model integrated into Cursor, designed to deliver high-level programming performance at a cost-efficient price. It is trained on long-horizon coding tasks, enabling it to solve complex problems that require multiple steps and actions. The model demonstrates strong improvements across key benchmarks, including Terminal-Bench and SWE-bench Multilingual. With enhanced intelligence and efficiency, it provides faster and more accurate code generation. Composer 2 combines strong performance with affordable pricing, making it accessible for developers and teams.
    Starting Price: $0.50/M input
  • 19
    GLM-5.1
    GLM-5.1 is the latest iteration of Z.ai’s GLM series, designed as a frontier-level, agent-oriented AI model optimized for coding, reasoning, and long-horizon workflows. It builds on the GLM-5 architecture, which uses a Mixture-of-Experts (MoE) design to deliver high performance while keeping inference costs efficient, and is part of a broader push toward open-weight, developer-accessible models. A core focus of GLM-5.1 is enabling agentic behavior, meaning it can plan, execute, and iterate across multi-step tasks rather than simply responding to single prompts. It is specifically designed to handle complex workflows such as debugging code, navigating repositories, and executing chained operations with sustained context. Compared to earlier models, GLM-5.1 improves reliability in long interactions, maintaining coherence across extended sessions and reducing breakdowns in multi-step reasoning.
    Starting Price: Free
  • 20
    Qwen3.6-Max-Preview
    Qwen3.6-Max-Preview is a next-generation frontier language model designed to push the limits of intelligence, instruction following, and real-world agent capabilities within the Qwen ecosystem. Building on the Qwen3 series, this preview release introduces stronger world knowledge, sharper instruction alignment, and significant improvements in agentic coding performance, enabling the model to better handle complex, multi-step tasks and software engineering workflows. It is engineered for advanced reasoning and execution scenarios, where the model not only generates responses but also interacts with tools, processes long contexts, and supports structured problem-solving across domains such as coding, research, and enterprise workflows. The architecture continues the Qwen focus on large-scale, high-efficiency models capable of handling extensive context windows and delivering consistent performance across multilingual and knowledge-intensive tasks.
    Starting Price: Free
  • 21
    Kimi K2.6

    Kimi K2.6

    Moonshot AI

    Kimi K2.6 is a next-generation agentic AI model developed by Moonshot AI, designed to push forward real-world execution, coding, and multi-step reasoning beyond earlier K2 and K2.5 versions. It builds on a Mixture-of-Experts architecture and the multimodal, agent-first foundation of the Kimi series, combining language understanding, coding, and tool use into a single system capable of planning and executing complex workflows. It introduces deeper reasoning capabilities and significantly improved agent planning, allowing it to break down tasks, coordinate tools, and handle multi-file or multi-step problems with greater accuracy and efficiency. It supports advanced tool calling with high reliability, enabling integration with external systems such as web search or APIs, and includes built-in validation mechanisms to ensure correct execution formats.
    Starting Price: Free
  • 22
    Qwen3.7-Max
    Qwen3.7-Max is Qwen’s latest proprietary model designed for the agent era, built to be a versatile agent foundation that is equally capable of writing and debugging code, automating office workflows, and sustaining autonomous browser sessions over long horizons. It reaches frontier-level coding performance, with stronger results across software engineering, terminal tasks, GUI grounding, web browsing, and agentic tool use. Qwen3.7-Max is designed to reduce the gap between model intelligence and real agent execution by supporting planning, long-context reasoning, reliable function calling, and multi-step task completion across complex workflows. It also strengthens multimodal and document-oriented work through Qwen Studio, which supports chatbot interaction, image and video understanding, image generation, document processing, presentation generation, coding assistance, deep research, and web development.
    Starting Price: Free
  • 23
    LFM3

    LFM3

    Liquid AI

    LFM3 is Liquid AI’s family of compact, open-weight foundation models for text, vision, audio, and multimodal tasks. The release includes text-generation, vision-language, audio, omni, and decision-model variants. Developers can download the model weights, adapt supported models through fine-tuning, and run them locally on edge hardware or access them through Liquid AI’s hosted API. Use cases include conversational assistants, tool calling, speech transcription and generation, image and video understanding, document extraction, classification, routing, and robotics applications. LFM3 is intended for developers, researchers, and organizations building specialized AI applications that need flexible deployment choices, including local inference. Open-weight models are available under Liquid AI’s LFM Open License; commercial eligibility and terms depend on an organization’s annual revenue.
    Starting Price: $0.08/MTok
  • 24
    GPT-J

    GPT-J

    EleutherAI

    GPT-J is a cutting-edge language model created by the research organization EleutherAI. In terms of performance, GPT-J exhibits a level of proficiency comparable to that of OpenAI's renowned GPT-3 model in a range of zero-shot tasks. Notably, GPT-J has demonstrated the ability to surpass GPT-3 in tasks related to generating code. The latest iteration of this language model, known as GPT-J-6B, is built upon a linguistic dataset referred to as The Pile. This dataset, which is publicly available, encompasses a substantial volume of 825 gibibytes of language data, organized into 22 distinct subsets. While GPT-J shares certain capabilities with ChatGPT, it is important to note that GPT-J is not designed to operate as a chatbot; rather, its primary function is to predict text. In a significant development in March 2023, Databricks introduced Dolly, a model that follows instructions and is licensed under Apache.
    Starting Price: Free
  • 25
    Stable LM

    Stable LM

    Stability AI

    Stable LM: Stability AI Language Models. The release of Stable LM builds on our experience in open-sourcing earlier language models with EleutherAI, a nonprofit research hub. These language models include GPT-J, GPT-NeoX, and the Pythia suite, which were trained on The Pile open-source dataset. Many recent open-source language models continue to build on these efforts, including Cerebras-GPT and Dolly-2. Stable LM is trained on a new experimental dataset built on The Pile, but three times larger with 1.5 trillion tokens of content. We will release details on the dataset in due course. The richness of this dataset gives Stable LM surprisingly high performance in conversational and coding tasks, despite its small size of 3 to 7 billion parameters (by comparison, GPT-3 has 175 billion parameters). Stable LM 3B is a compact language model designed to operate on portable digital devices like handhelds and laptops, and we’re excited about its capabilities and portability.
    Starting Price: Free
  • 26
    MPT-7B

    MPT-7B

    MosaicML

    Introducing MPT-7B, the latest entry in our MosaicML Foundation Series. MPT-7B is a transformer trained from scratch on 1T tokens of text and code. It is open source, available for commercial use, and matches the quality of LLaMA-7B. MPT-7B was trained on the MosaicML platform in 9.5 days with zero human intervention at a cost of ~$200k. Now you can train, finetune, and deploy your own private MPT models, either starting from one of our checkpoints or training from scratch. For inspiration, we are also releasing three finetuned models in addition to the base MPT-7B: MPT-7B-Instruct, MPT-7B-Chat, and MPT-7B-StoryWriter-65k+, the last of which uses a context length of 65k tokens!
    Starting Price: Free
  • 27
    LongLLaMA

    LongLLaMA

    LongLLaMA

    This repository contains the research preview of LongLLaMA, a large language model capable of handling long contexts of 256k tokens or even more. LongLLaMA is built upon the foundation of OpenLLaMA and fine-tuned using the Focused Transformer (FoT) method. LongLLaMA code is built upon the foundation of Code Llama. We release a smaller 3B base variant (not instruction tuned) of the LongLLaMA model on a permissive license (Apache 2.0) and inference code supporting longer contexts on hugging face. Our model weights can serve as the drop-in replacement of LLaMA in existing implementations (for short context up to 2048 tokens). Additionally, we provide evaluation results and comparisons against the original OpenLLaMA models.
    Starting Price: Free
  • 28
    Llama 3
    We’ve integrated Llama 3 into Meta AI, our intelligent assistant, that expands the ways people can get things done, create and connect with Meta AI. You can see first-hand the performance of Llama 3 by using Meta AI for coding tasks and problem solving. Whether you're developing agents, or other AI-powered applications, Llama 3 in both 8B and 70B will offer the capabilities and flexibility you need to develop your ideas. With the release of Llama 3, we’ve updated the Responsible Use Guide (RUG) to provide the most comprehensive information on responsible development with LLMs. Our system-centric approach includes updates to our trust and safety tools with Llama Guard 2, optimized to support the newly announced taxonomy published by MLCommons expanding its coverage to a more comprehensive set of safety categories, code shield, and Cybersec Eval 2.
    Starting Price: Free
  • 29
    Codestral

    Codestral

    Mistral AI

    We introduce Codestral, our first-ever code model. Codestral is an open-weight generative AI model explicitly designed for code generation tasks. It helps developers write and interact with code through a shared instruction and completion API endpoint. As it masters code and English, it can be used to design advanced AI applications for software developers. Codestral is trained on a diverse dataset of 80+ programming languages, including the most popular ones, such as Python, Java, C, C++, JavaScript, and Bash. It also performs well on more specific ones like Swift and Fortran. This broad language base ensures Codestral can assist developers in various coding environments and projects.
    Starting Price: Free
  • 30
    CodeQwen

    CodeQwen

    Alibaba

    CodeQwen is the code version of Qwen, the large language model series developed by the Qwen team, Alibaba Cloud. It is a transformer-based decoder-only language model pre-trained on a large amount of data of codes. Strong code generation capabilities and competitive performance across a series of benchmarks. Supporting long context understanding and generation with the context length of 64K tokens. CodeQwen supports 92 coding languages and provides excellent performance in text-to-SQL, bug fixes, etc. You can just write several lines of code with transformers to chat with CodeQwen. Essentially, we build the tokenizer and the model from pre-trained methods, and we use the generate method to perform chatting with the help of the chat template provided by the tokenizer. We apply the ChatML template for chat models following our previous practice. The model completes the code snippets according to the given prompts, without any additional formatting.
    Starting Price: Free