Best AI Coding Models - Page 5
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GPT-5.5 Pro
OpenAI
GPT-5.5 Pro is an advanced AI model designed to handle complex, real-world work with greater autonomy and efficiency. It understands user intent quickly and can execute multi-step tasks such as coding, research, data analysis, and document creation with minimal guidance. The model is built to plan, use tools, and refine its outputs until tasks are complete. It excels in knowledge work, software development, and analytical problem-solving. With strong reasoning and persistence, GPT-5.5 Pro can manage long-running workflows across tools and systems. It delivers high-quality results while maintaining speed and efficiency. Overall, it enables individuals and teams to complete demanding tasks faster and more accurately.Starting Price: $30 per 1M tokens (input) -
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Qwen3.6-27B
Alibaba
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 -
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KAT-Coder-Pro V2
StreamLake
KAT-Coder is an agentic AI coding system designed to go beyond traditional autocomplete tools by enabling end-to-end software development workflows driven by reasoning, planning, and execution. It is positioned as a flagship coding model within the KAT ecosystem, built specifically for “agentic coding,” where the model does not just generate snippets but can diagnose issues, propose fixes, run tests, and iterate across multiple files as part of a continuous development loop. It integrates directly with developer environments through API endpoints and proxy layers compatible with tools like Claude Code, allowing seamless use inside existing IDE workflows without changing the interface developers are already familiar with. KAT-Coder is trained using a multi-stage pipeline that includes supervised fine-tuning and large-scale reinforcement learning, enabling it to understand programming context, and reason over complex tasks.Starting Price: $0.30 per month -
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DeepSeek-V4-Pro
DeepSeek
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 -
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DeepSeek-V4-Flash
DeepSeek
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 -
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Laguna XS.2
Poolside
Laguna XS.2 is Poolside’s open-weight agentic coding model, built as the lightest and fastest model in the Laguna family. It is a 33B total-parameter Mixture of Experts model with 3B activated parameters, trained completely in-house on 30T tokens. As Poolside’s newest generation model open to the community, Laguna XS.2 is a second-generation architecture and the company’s first open-weight model, built on the lessons learned from training Laguna M.1 across synthetic data and reinforcement learning. The model is designed for agentic coding workflows, where it can code, act, iterate quickly, and perform best inside Poolside’s coding agent. Laguna XS.2 is positioned as a strong model for rapid agentic iteration, especially for developers and teams that need a compact, efficient coding model rather than a heavier frontier system. It is released under an Apache 2.0 license, allowing the community to evaluate, fine-tune, quantize, serve, and build on the weights.Starting Price: Free -
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Laguna M.1
Poolside
Laguna M.1 is Poolside’s most capable model for agentic coding, built and trained in-house for software development workflows. It is a 225B total-parameter Mixture of Experts model with 23B activated parameters, trained completely in-house on 30T tokens using 6,144 interconnected NVIDIA H200 GPUs. Poolside trained Laguna M.1 from scratch with its own data work, training codebase, and async on-policy reinforcement learning in its agent harness, all with agentic coding in mind. The model is designed to perform at its best inside Poolside’s coding agent, where it can reason through software tasks, interact with tools, edit code, run tests, and support longer autonomous development sessions. Laguna M.1 is built for developers and teams working on complex coding tasks that require stronger reasoning, architectural understanding, terminal use, and multi-step execution than lightweight models can provide.Starting Price: Free -
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CodeGen
Salesforce
CodeGen is an open-source model for program synthesis. Trained on TPU-v4. Competitive with OpenAI Codex.Starting Price: Free -
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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 -
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Llama 2
Meta
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 -
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Code Llama
Meta
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 -
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ChatGPT Enterprise
OpenAI
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 collaborateStarting Price: $60/user/month -
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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 -
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OpenAI o3
OpenAI
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 -
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Yi-Large
01.AI
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 -
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Grok 3 mini
xAI
Grok-3 Mini, crafted by xAI, is an agile and insightful AI companion tailored for users who need quick, yet thorough answers to their questions. This smaller version maintains the essence of the Grok series, offering an external, often humorous perspective on human affairs with a focus on efficiency. Designed for those on the move or with limited resources, Grok-3 Mini delivers the same level of curiosity and helpfulness in a more compact form. It's adept at handling a broad spectrum of questions, providing succinct insights without compromising on depth or accuracy, making it a perfect tool for fast-paced, modern-day inquiries.Starting Price: Free -
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Mercury Coder
Inception Labs
Mercury, the latest innovation from Inception Labs, is the first commercial-scale diffusion large language model (dLLM), offering a 10x speed increase and significantly lower costs compared to traditional autoregressive models. Built for high-performance reasoning, coding, and structured text generation, Mercury processes over 1000 tokens per second on NVIDIA H100 GPUs, making it one of the fastest LLMs available. Unlike conventional models that generate text one token at a time, Mercury refines responses using a coarse-to-fine diffusion approach, improving accuracy and reducing hallucinations. With Mercury Coder, a specialized coding model, developers can experience cutting-edge AI-driven code generation with superior speed and efficiency.Starting Price: Free -
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ERNIE X1 Turbo
Baidu
ERNIE X1 Turbo, developed by Baidu, is an advanced deep reasoning AI model introduced at the Baidu Create 2025 conference. Designed to handle complex multi-step tasks such as problem-solving, literary creation, and code generation, this model outperforms competitors like DeepSeek R1 in terms of reasoning abilities. With a focus on multimodal capabilities, ERNIE X1 Turbo supports text, audio, and image processing, making it an incredibly versatile AI solution. Despite its cutting-edge technology, it is priced at just a fraction of the cost of other top-tier models, offering a high-value solution for businesses and developers.Starting Price: $0.14 per 1M tokens -
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Gemini 2.5 Pro Preview (I/O Edition) by Google is an advanced AI model designed to streamline coding tasks and enhance web app development. This powerful tool allows developers to efficiently transform and edit code, reducing errors and improving function calling accuracy. With enhanced capabilities in video understanding and web app creation, Gemini 2.5 Pro Preview excels at building aesthetically pleasing and functional web applications. Available through Google’s Gemini API and AI platforms, this model provides a seamless solution for developers to create innovative applications with improved performance and reliability.Starting Price: $19.99/month
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OpenAI o3-pro
OpenAI
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 -
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GPT‑5-Codex
OpenAI
GPT-5-Codex is a version of GPT-5 further optimized for agentic coding within Codex, focusing on real-world software engineering tasks (building full projects from scratch, adding features & tests, debugging, large-scale refactors, and code reviews). Codex now moves faster, is more reliable, and works better in real-time across your development environments, whether in terminal/CLI, IDE extension, via the web, in GitHub, or even on mobile. GPT-5-Codex is the default model for cloud tasks and code review; developers can also opt to use it locally via Codex CLI or the IDE extension. It dynamically adjusts how much “reasoning time” it spends depending on task complexity; small, well-defined tasks are fast and snappy; more complex ones (refactors, large feature work) get more sustained effort. Code review is stronger; it catches critical bugs before shipping. -
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Relace
Relace
Relace offers a suite of specialized AI models purpose-built for coding workflows. Its retrieval, embedding, code-reranker, and “Instant Apply” models are designed to integrate into existing development environments and accelerate code production, merging changes at speeds over 2,500 tokens per second and handling large codebases (million-line scale) in under 2 seconds. The platform supports hosted API access and self-hosted or VPC-isolated deployments, so teams have full control of data and infrastructure. Its code-oriented embedding and reranking models identify the most relevant files for a given developer query and filter out irrelevant context, reducing prompt bloat and improving accuracy. The Instant Apply model merges AI-generated snippets into existing codebases with high reliability and low error rate, streamlining pull-request reviews, CI/CD workflows, and automated fixes.Starting Price: $0.80 per million tokens -
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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. -
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GPT-5.1-Codex-Max
OpenAI
GPT-5.1-Codex-Max is the high-capability variant of the GPT-5.1-Codex series designed specifically for software engineering and agentic code workflows. It builds on the base GPT-5.1 architecture with a focus on long-horizon tasks such as full project generation, large-scale refactoring, and autonomous multi-step bug and test management. It introduces adaptive reasoning, meaning the system dynamically allocates more compute for complex problems and less for simpler ones, to improve efficiency and output quality. It also supports tool use (IDE-integrated workflows, version control, CI/CD pipelines) and offers higher fidelity in code review, debugging, and agentic behavior than general-purpose models. Alongside Max, there are lighter variants such as Codex-Mini for cost-sensitive or scale use-cases. The GPT-5.1-Codex family is available in developer previews, including via integrations like GitHub Copilot. -
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GPT-5.2 Thinking
OpenAI
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. -
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GPT-5.2 Instant
OpenAI
GPT-5.2 Instant is the fast, capable variant of OpenAI’s GPT-5.2 model family designed for everyday work and learning with clear improvements in information-seeking questions, how-tos and walkthroughs, technical writing, and translation compared to prior versions. It builds on the warmer conversational tone introduced in GPT-5.1 Instant and produces clearer explanations that surface key information upfront, making it easier for users to get concise, accurate answers quickly. GPT-5.2 Instant delivers speed and responsiveness for typical tasks like answering queries, generating summaries, assisting with research, and helping with writing and editing, while incorporating broader enhancements from the GPT-5.2 series in reasoning, long-context handling, and factual grounding. As part of the GPT-5.2 lineup, it shares the same foundational improvements that boost overall reliability and performance across a wide range of everyday activities. -
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GPT-5.2 Pro
OpenAI
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. -
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Gemini 3 Flash
Google
Gemini 3 Flash is Google’s latest AI model built to deliver frontier intelligence with exceptional speed and efficiency. It combines Pro-level reasoning with Flash-level latency, making advanced AI more accessible and affordable. The model excels in complex reasoning, multimodal understanding, and agentic workflows while using fewer tokens for everyday tasks. Gemini 3 Flash is designed to scale across consumer apps, developer tools, and enterprise platforms. It supports rapid coding, data analysis, video understanding, and interactive application development. By balancing performance, cost, and speed, Gemini 3 Flash redefines what fast AI can achieve. -
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Composer 1.5
Cursor
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. -
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GLM-5V-Turbo
Z.ai
GLM-5V-Turbo is a multimodal coding foundation model designed for vision-based coding tasks, capable of natively processing inputs such as images, video, text, and files while producing text outputs. It is optimized for agent workflows, enabling a full loop of understanding environments, planning actions, and executing tasks, and integrates seamlessly with agent frameworks like Claude Code and OpenClaw. It supports long-context interactions with a context length of 200K tokens and up to 128K output tokens, making it suitable for complex, long-horizon tasks. It offers multiple thinking modes for different scenarios, strong vision comprehension across images and video, real-time streaming output for improved interaction, and advanced function-calling capabilities for integrating external tools. It also includes context caching to enhance performance in extended conversations. In practical use, it can reconstruct frontend projects from design mockups.
