Compare the Top AI Coding Models for Windows as of April 2026 - Page 3

  • 1
    Qwen3.6-35B-A3B
    Qwen3.5-35B-A3B is part of the Qwen3.5 “Medium” model series, designed as a highly efficient, multimodal foundation model that balances strong reasoning ability with practical deployment requirements. It uses a Mixture-of-Experts (MoE) architecture with 35 billion total parameters but activates only about 3 billion per token, allowing it to deliver performance comparable to much larger models while significantly reducing computational cost. The model integrates a hybrid attention mechanism that combines linear attention with standard attention layers, enabling efficient long-context processing and improved scalability for complex tasks. As a native vision-language model, it can process both text and visual inputs, supporting use cases such as multimodal reasoning, coding, and agent-based workflows. It is designed to function as a general-purpose “AI agent,” capable of planning, tool use, and structured problem solving rather than just conversational responses.
    Starting Price: Free
  • 2
    Qwen3.6-27B
    Qwen3.6-27B is a dense, open source multimodal language model in the Qwen3.6 series, designed to deliver flagship-level performance in coding, reasoning, and agent-based workflows while maintaining a relatively efficient parameter size of 27 billion. It is positioned as a high-performance general model that “punches above its weight,” achieving results competitive with or superior to significantly larger models on key benchmarks, particularly in agentic coding tasks. It supports both thinking and non-thinking modes, allowing it to dynamically balance deep reasoning with fast responses depending on the task, and integrates capabilities across text and multimodal inputs such as images and video. Built as part of the Qwen3.6 family, the model emphasizes real-world usability, stability, and developer productivity, incorporating improvements driven by community feedback and practical deployment needs.
    Starting Price: Free
  • 3
    DeepSeek-V4-Pro
    DeepSeek-V4-Pro is a large-scale Mixture-of-Experts (MoE) language model designed for advanced reasoning, coding, and long-context understanding. It features 1.6 trillion total parameters with 49 billion activated parameters, enabling high performance while maintaining efficiency. The model supports an exceptionally large context window of up to one million tokens, allowing it to process extensive documents and workflows. It uses a hybrid attention architecture to optimize long-context performance and reduce computational cost. DeepSeek-V4-Pro is trained on over 32 trillion tokens, improving its knowledge and reasoning capabilities. It also includes advanced optimization techniques for stability and faster convergence during training. The model supports multiple reasoning modes, allowing users to balance speed and accuracy based on their needs. Overall, it provides a powerful open-source solution for complex AI tasks and large-scale applications.
    Starting Price: Free
  • 4
    DeepSeek-V4-Flash
    DeepSeek-V4-Flash is a high-efficiency Mixture-of-Experts (MoE) language model designed for fast, scalable reasoning and text generation. It features 284 billion total parameters with 13 billion activated parameters, delivering strong performance while optimizing computational cost. The model supports an extensive context window of up to one million tokens, enabling it to process large documents and complex workflows with ease. Its hybrid attention architecture enhances long-context efficiency by reducing memory and compute requirements. Trained on over 32 trillion tokens, DeepSeek-V4-Flash demonstrates solid capabilities across knowledge, reasoning, and coding tasks. It is designed for scenarios where speed and efficiency are critical, offering a balance between performance and resource usage. The model also supports multiple reasoning modes, allowing users to adjust between faster outputs and deeper analysis.
    Starting Price: Free
  • 5
    StarCoder

    StarCoder

    BigCode

    StarCoder and StarCoderBase are Large Language Models for Code (Code LLMs) trained on permissively licensed data from GitHub, including from 80+ programming languages, Git commits, GitHub issues, and Jupyter notebooks. Similar to LLaMA, we trained a ~15B parameter model for 1 trillion tokens. We fine-tuned StarCoderBase model for 35B Python tokens, resulting in a new model that we call StarCoder. We found that StarCoderBase outperforms existing open Code LLMs on popular programming benchmarks and matches or surpasses closed models such as code-cushman-001 from OpenAI (the original Codex model that powered early versions of GitHub Copilot). With a context length of over 8,000 tokens, the StarCoder models can process more input than any other open LLM, enabling a wide range of interesting applications. For example, by prompting the StarCoder models with a series of dialogues, we enabled them to act as a technical assistant.
    Starting Price: Free
  • 6
    Llama 2
    The next generation of our open source large language model. This release includes model weights and starting code for pretrained and fine-tuned Llama language models — ranging from 7B to 70B parameters. Llama 2 pretrained models are trained on 2 trillion tokens, and have double the context length than Llama 1. Its fine-tuned models have been trained on over 1 million human annotations. Llama 2 outperforms other open source language models on many external benchmarks, including reasoning, coding, proficiency, and knowledge tests. Llama 2 was pretrained on publicly available online data sources. The fine-tuned model, Llama-2-chat, leverages publicly available instruction datasets and over 1 million human annotations. We have a broad range of supporters around the world who believe in our open approach to today’s AI — companies that have given early feedback and are excited to build with Llama 2.
    Starting Price: Free
  • 7
    Code Llama
    Code Llama is a large language model (LLM) that can use text prompts to generate code. Code Llama is state-of-the-art for publicly available LLMs on code tasks, and has the potential to make workflows faster and more efficient for current developers and lower the barrier to entry for people who are learning to code. Code Llama has the potential to be used as a productivity and educational tool to help programmers write more robust, well-documented software. Code Llama is a state-of-the-art LLM capable of generating code, and natural language about code, from both code and natural language prompts. Code Llama is free for research and commercial use. Code Llama is built on top of Llama 2 and is available in three models: Code Llama, the foundational code model; Codel Llama - Python specialized for Python; and Code Llama - Instruct, which is fine-tuned for understanding natural language instructions.
    Starting Price: Free
  • 8
    ChatGPT Enterprise
    Enterprise-grade security & privacy and the most powerful version of ChatGPT yet. 1. Customer prompts or data are not used for training models 2. Data encryption at rest (AES-256) and in transit (TLS 1.2+) 3. SOC 2 compliant 4. Dedicated admin console and easy bulk member management 5. SSO and Domain Verification 6. Analytics dashboard to understand usage 7. Unlimited, high-speed access to GPT-4 and Advanced Data Analysis* 8. 32k token context windows for 4X longer inputs and memory 9. Shareable chat templates for your company to collaborate
    Starting Price: $60/user/month
  • 9
    GPT-5

    GPT-5

    OpenAI

    GPT-5 is OpenAI’s most advanced AI model, delivering smarter, faster, and more useful responses across a wide range of topics including math, science, finance, and law. It features built-in thinking capabilities that allow it to provide expert-level answers and perform complex reasoning. GPT-5 can handle long context lengths and generate detailed outputs, making it ideal for coding, research, and creative writing. The model includes a ‘verbosity’ parameter for customizable response length and improved personality control. It integrates with business tools like Google Drive and SharePoint to provide context-aware answers while respecting security permissions. Available to everyone, GPT-5 empowers users to collaborate with an AI assistant that feels like a knowledgeable colleague.
    Starting Price: $1.25 per 1M tokens
  • 10
    OpenAI o3
    OpenAI o3 is an advanced AI model designed to enhance reasoning capabilities by breaking down complex instructions into smaller, more manageable steps. It offers significant improvements over previous AI iterations, excelling in coding tasks, competitive programming, and achieving high scores in mathematics and science benchmarks. Available for widespread use, OpenAI o3 supports advanced AI-driven problem-solving and decision-making processes. The model incorporates deliberative alignment techniques to ensure its responses align with established safety and ethical guidelines, making it a powerful tool for developers, researchers, and enterprises seeking sophisticated AI solutions.
    Starting Price: $2 per 1 million tokens
  • 11
    Yi-Large
    Yi-Large is a proprietary large language model developed by 01.AI, offering a 32k context length with both input and output costs at $2 per million tokens. It stands out with its advanced capabilities in natural language processing, common-sense reasoning, and multilingual support, performing on par with leading models like GPT-4 and Claude3 in various benchmarks. Yi-Large is designed for tasks requiring complex inference, prediction, and language understanding, making it suitable for applications like knowledge search, data classification, and creating human-like chatbots. Its architecture is based on a decoder-only transformer with enhancements such as pre-normalization and Group Query Attention, and it has been trained on a vast, high-quality multilingual dataset. This model's versatility and cost-efficiency make it a strong contender in the AI market, particularly for enterprises aiming to deploy AI solutions globally.
    Starting Price: $0.19 per 1M input token
  • 12
    OpenAI o3-pro
    OpenAI’s o3-pro is a high-performance reasoning model designed for tasks that require deep analysis and precision. It is available exclusively to ChatGPT Pro and Team subscribers, succeeding the earlier o1-pro model. The model excels in complex fields like mathematics, science, and coding by employing detailed step-by-step reasoning. It integrates advanced tools such as real-time web search, file analysis, Python execution, and visual input processing. While powerful, o3-pro has slower response times and lacks support for features like image generation and temporary chats. Despite these trade-offs, o3-pro demonstrates superior clarity, accuracy, and adherence to instructions compared to its predecessor.
    Starting Price: $20 per 1 million tokens
  • 13
    GPT-5.1

    GPT-5.1

    OpenAI

    GPT-5.1 is the latest update in the GPT-5 series, designed to make ChatGPT dramatically smarter and more conversational. The release introduces two distinct model variants: GPT-5.1 Instant, which is described as the most-used model and is now warmer, better at following instructions, and more intelligent; and GPT-5.1 Thinking, which is the advanced reasoning engine that’s been tuned to be easier to understand, faster on straightforward tasks, and more persistent on complex ones. Users' queries are now routed automatically to the variant best-suited to the task. The update emphasizes not just improved raw intelligence but also enhanced communication style; the models are tuned to be more natural, enjoyable to talk to, and better aligned with user intents. The system card addendum notes that GPT-5.1 Instant uses “adaptive reasoning” that lets it decide when to think more deeply before responding, while GPT-5.1 Thinking adapts its thinking time accurately to the question at hand.
  • 14
    GPT-5.2 Thinking
    GPT-5.2 Thinking is the highest-capability configuration in OpenAI’s GPT-5.2 model family, engineered for deep, expert-level reasoning, complex task execution, and advanced problem solving across long contexts and professional domains. Built on the foundational GPT-5.2 architecture with improvements in grounding, stability, and reasoning quality, this variant applies more compute and reasoning effort to generate responses that are more accurate, structured, and contextually rich when handling highly intricate workflows, multi-step analysis, and domain-specific challenges. GPT-5.2 Thinking excels at tasks that require sustained logical coherence, such as detailed research synthesis, advanced coding and debugging, complex data interpretation, strategic planning, and sophisticated technical writing, and it outperforms lighter variants on benchmarks that test professional skills and deep comprehension.
  • 15
    GPT-5.2 Pro
    GPT-5.2 Pro is the highest-capability variant of OpenAI’s latest GPT-5.2 model family, built to deliver professional-grade reasoning, complex task performance, and enhanced accuracy for demanding knowledge work, creative problem-solving, and enterprise-level applications. It builds on the foundational improvements of GPT-5.2, including stronger general intelligence, superior long-context understanding, better factual grounding, and improved tool use, while using more compute and deeper processing to produce more thoughtful, reliable, and context-rich responses for users with intricate, multi-step requirements. GPT-5.2 Pro is designed to handle challenging workflows such as advanced coding and debugging, deep data analysis, research synthesis, extensive document comprehension, and complex project planning with greater precision and fewer errors than lighter variants.
  • 16
    Composer 1.5
    Composer 1.5 is the latest agentic coding model from Cursor that balances speed and intelligence for everyday code tasks by scaling reinforcement learning approximately 20x more than its predecessor, enabling stronger performance on real-world programming challenges. It’s designed as a “thinking model” that generates internal reasoning tokens to analyze a user’s codebase and plan next steps, responding quickly to simple problems and engaging deeper reasoning on complex ones, while remaining interactive and fast for daily development workflows. To handle long-running tasks, Composer 1.5 introduces self-summarization, allowing the model to compress and carry forward context when it reaches context limits, which helps maintain accuracy across varying input lengths. Internal benchmarks show it surpasses Composer 1 in coding tasks, especially on more difficult issues, making it more capable for interactive use within Cursor’s environment.
  • 17
    Qwen3.6

    Qwen3.6

    Alibaba

    Qwen3.6 is a large language model developed by Alibaba as part of its Qwen AI model family, designed for real-world applications and advanced reasoning tasks. It focuses on improving stability, usability, and performance compared to earlier versions. The model supports multimodal capabilities, allowing it to process and reason across text, images, and other data types. Qwen3.6 is particularly strong in coding and developer workflows, offering improved accuracy for complex programming tasks. It uses a mixture-of-experts architecture, enabling efficient performance while maintaining large-scale model capabilities. The model is designed to be deployable in production environments, including enterprise and cloud-based systems. It can be integrated into applications or run locally using open-weight variants. Overall, Qwen3.6 delivers a powerful, efficient, and versatile AI solution for modern use cases.
    Starting Price: Free
  • 18
    PaLM 2

    PaLM 2

    Google

    PaLM 2 is our next generation large language model that builds on Google’s legacy of breakthrough research in machine learning and responsible AI. It excels at advanced reasoning tasks, including code and math, classification and question answering, translation and multilingual proficiency, and natural language generation better than our previous state-of-the-art LLMs, including PaLM. It can accomplish these tasks because of the way it was built – bringing together compute-optimal scaling, an improved dataset mixture, and model architecture improvements. PaLM 2 is grounded in Google’s approach to building and deploying AI responsibly. It was evaluated rigorously for its potential harms and biases, capabilities and downstream uses in research and in-product applications. It’s being used in other state-of-the-art models, like Med-PaLM 2 and Sec-PaLM, and is powering generative AI features and tools at Google, like Bard and the PaLM API.
  • 19
    OpenAI o4-mini-high
    OpenAI o4-mini-high is an enhanced version of the o4-mini, optimized for higher reasoning capacity and performance. It maintains the same compact size but significantly boosts its ability to handle more complex tasks with improved efficiency. Whether you're dealing with large datasets, advanced mathematical computations, or intricate coding problems, o4-mini-high provides faster, more accurate responses, making it perfect for high-demand applications.
  • 20
    GPT-5 pro
    GPT-5 Pro is OpenAI’s most advanced AI model, designed to tackle the most complex and challenging tasks with extended reasoning capabilities. It builds on GPT-5’s unified architecture, using scaled, efficient parallel compute to provide highly comprehensive and accurate responses. GPT-5 Pro achieves state-of-the-art performance on difficult benchmarks like GPQA, excelling in areas such as health, science, math, and coding. It makes significantly fewer errors than earlier models and delivers responses that experts find more relevant and useful. The model automatically balances quick answers and deep thinking, allowing users to get expert-level insights efficiently. GPT-5 Pro is available to Pro subscribers and powers some of the most demanding applications requiring advanced intelligence.
  • 21
    GPT-5.1 Instant
    GPT-5.1 Instant is a high-performance AI model designed for everyday users that combines speed, responsiveness, and improved conversational warmth. The model uses adaptive reasoning to instantly select how much computation is required for a task, allowing it to deliver fast answers without sacrificing understanding. It emphasizes stronger instruction-following, enabling users to give precise directions and expect consistent compliance. The model also introduces richer personality controls so chat tone can be set to Default, Friendly, Professional, Candid, Quirky, or Efficient, with experiments in deeper voice modulation. Its core value is to make interactions feel more natural and less robotic while preserving high intelligence across writing, coding, analysis, and reasoning. GPT-5.1 Instant routes user requests automatically from the base interface, with the system choosing whether this variant or the deeper “Thinking” model is applied.
  • 22
    GPT-5.1 Thinking
    GPT-5.1 Thinking is the advanced reasoning model variant in the GPT-5.1 series, designed to more precisely allocate “thinking time” based on prompt complexity, responding faster to simpler requests and spending more effort on difficult problems. On a representative task distribution, it is roughly twice as fast on the fastest tasks and twice as slow on the slowest compared with its predecessor. Its responses are crafted to be clearer, with less jargon and fewer undefined terms, making deep analytical work more accessible and understandable. The model dynamically adjusts its reasoning depth, achieving a better balance between speed and thoroughness, particularly when dealing with technical concepts or multi-step questions. By combining high reasoning capacity with improved clarity, GPT-5.1 Thinking offers a powerful tool for tackling complex tasks, such as detailed analysis, coding, research, or technical explanations, while reducing unnecessary latency for routine queries.
  • 23
    OpenAI o4-mini
    The o4-mini model is a compact and efficient version of the o3 model, released following the launch of GPT-4.1. It offers enhanced reasoning capabilities, with improved performance in tasks that require complex reasoning and problem-solving. The o4-mini is designed to meet the growing demand for advanced AI solutions, serving as a more efficient alternative while maintaining the capabilities of its predecessor. This model is part of OpenAI's strategy to refine and advance their AI technologies ahead of the anticipated GPT-5 launch.
  • 24
    OpenAI o3-mini-high
    The o3-mini-high model from OpenAI advances AI reasoning by refining deep problem-solving in coding, mathematics, and complex tasks. It features adaptive thinking time with adjustable reasoning modes (low, medium, high) to optimize performance based on task complexity. Outperforming the o1 series by 200 Elo points on Codeforces, it delivers high efficiency at a lower cost while maintaining speed and accuracy. As part of the o3 family, it pushes AI problem-solving boundaries while remaining accessible, offering a free tier and expanded limits for Plus subscribers.
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