Best AI Coding Models - Page 3
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GLM-5.1
Zhipu AI
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 -
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Qwen3.6-Max-Preview
Alibaba
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 -
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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 -
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Composer 2.5
Cursor
Composer 2.5 is the latest AI coding model released by Cursor, offering major improvements in intelligence, collaboration, and long-task performance compared to Composer 2. The model is designed to follow complex instructions more accurately while providing a smoother and more natural user experience during coding sessions. Cursor enhanced Composer 2.5 through larger-scale training, more advanced reinforcement learning environments, and improved behavioral tuning focused on communication and effort calibration. The model uses targeted reinforcement learning with textual feedback to correct specific mistakes during training, helping it avoid issues like invalid tool calls or poor coding behavior. Composer 2.5 was also trained using significantly more synthetic coding tasks, enabling it to handle increasingly difficult programming challenges and real-world development scenarios.Starting Price: $0.50/M input -
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Qwen3.7-Max
Alibaba
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 -
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MiniMax M3
MiniMax
MiniMax M3 is a rumored next-generation AI model expected to succeed the MiniMax M2 series with stronger reasoning, multimodal intelligence, and agent-based capabilities. Although the model has generated significant discussion in AI communities, MiniMax has not officially released M3 or published confirmed specifications, benchmarks, or API access. Reports suggest that MiniMax M3 may focus on advanced creative reasoning, coding, automation, and multimodal workflows involving text, images, audio, and video. The model is expected to build on MiniMax’s existing AI ecosystem, which already includes language models, speech generation, video creation, and multimodal systems. Industry speculation points to improvements in long-context processing, intelligent agent orchestration, and enterprise-grade AI task execution. As of now, the latest officially available flagship model from MiniMax remains MiniMax M2.7, while M3 continues to be treated as an anticipated future release.Starting Price: Free -
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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 -
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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 -
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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 -
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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 -
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Llama 3
Meta
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 -
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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 -
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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 -
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Mistral Large
Mistral AI
Mistral Large is Mistral AI's flagship language model, designed for advanced text generation and complex multilingual reasoning tasks, including text comprehension, transformation, and code generation. It supports English, French, Spanish, German, and Italian, offering a nuanced understanding of grammar and cultural contexts. With a 32,000-token context window, it can accurately recall information from extensive documents. The model's precise instruction-following and native function-calling capabilities facilitate application development and tech stack modernization. Mistral Large is accessible through Mistral's platform, Azure AI Studio, and Azure Machine Learning, and can be self-deployed for sensitive use cases. Benchmark evaluations indicate that Mistral Large achieves strong results, making it the world's second-ranked model generally available through an API, next to GPT-4.Starting Price: Free -
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IBM Granite
IBM
IBM® Granite™ is a family of artificial intelligence (AI) models purpose-built for business, engineered from scratch to help ensure trust and scalability in AI-driven applications. Open source Granite models are available today. We make AI as accessible as possible for as many developers as possible. That’s why we have open-sourced core Granite Code, Time Series, Language, and GeoSpatial models and made them available on Hugging Face under permissive Apache 2.0 license that enables broad, unencumbered commercial usage. All Granite models are trained on carefully curated data, with industry-leading levels of transparency about the data that went into them. We have also open-sourced the tools we use to ensure the data is high quality and up to the standards that enterprise-grade applications demand.Starting Price: Free -
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Granite Code
IBM
We introduce the Granite series of decoder-only code models for code generative tasks (e.g., fixing bugs, explaining code, documenting code), trained with code written in 116 programming languages. A comprehensive evaluation of the Granite Code model family on diverse tasks demonstrates that our models consistently reach state-of-the-art performance among available open source code LLMs. The key advantages of Granite Code models include: All-rounder Code LLM: Granite Code models achieve competitive or state-of-the-art performance on different kinds of code-related tasks, including code generation, explanation, fixing, editing, translation, and more. Demonstrating their ability to solve diverse coding tasks. Trustworthy Enterprise-Grade LLM: All our models are trained on license-permissible data collected following IBM's AI Ethics principles and guided by IBM’s Corporate Legal team for trustworthy enterprise usage.Starting Price: Free -
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Qwen2
Alibaba
Qwen2 is the large language model series developed by Qwen team, Alibaba Cloud. Qwen2 is a series of large language models developed by the Qwen team at Alibaba Cloud. It includes both base language models and instruction-tuned models, ranging from 0.5 billion to 72 billion parameters, and features both dense models and a Mixture-of-Experts model. The Qwen2 series is designed to surpass most previous open-weight models, including its predecessor Qwen1.5, and to compete with proprietary models across a broad spectrum of benchmarks in language understanding, generation, multilingual capabilities, coding, mathematics, and reasoning.Starting Price: Free -
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Grok 2
xAI
Grok-2, the latest iteration in AI technology, is a marvel of modern engineering, designed to push the boundaries of what artificial intelligence can achieve. Inspired by the wit and wisdom of the Hitchhiker's Guide to the Galaxy and the efficiency of JARVIS from Iron Man, Grok-2 is not just another AI; it's a companion in the truest sense. With an expanded knowledge base that stretches up to the recent past, Grok-2 offers insights with a touch of humor and an outside perspective on humanity, making it uniquely engaging. Its capabilities include answering nearly any question with maximum helpfulness, often providing solutions that are both innovative and outside the conventional box. Grok-2's design emphasizes truthfulness, avoiding the pitfalls of woke culture, and strives to be maximally truthful, making it a reliable source of information and entertainment in an increasingly complex world.Starting Price: Free -
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Sky-T1
NovaSky
Sky-T1-32B-Preview is an open source reasoning model developed by the NovaSky team at UC Berkeley's Sky Computing Lab. It matches the performance of proprietary models like o1-preview on reasoning and coding benchmarks, yet was trained for under $450, showcasing the feasibility of cost-effective, high-level reasoning capabilities. The model was fine-tuned from Qwen2.5-32B-Instruct using a curated dataset of 17,000 examples across diverse domains, including math and coding. The training was completed in 19 hours on eight H100 GPUs with DeepSpeed Zero-3 offloading. All aspects of the project, including data, code, and model weights, are fully open-source, empowering the academic and open-source communities to replicate and enhance the model's performance.Starting Price: Free -
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DeepSeek-V2
DeepSeek
DeepSeek-V2 is a state-of-the-art Mixture-of-Experts (MoE) language model introduced by DeepSeek-AI, characterized by its economical training and efficient inference capabilities. With a total of 236 billion parameters, of which only 21 billion are active per token, it supports a context length of up to 128K tokens. DeepSeek-V2 employs innovative architectures like Multi-head Latent Attention (MLA) for efficient inference by compressing the Key-Value (KV) cache and DeepSeekMoE for cost-effective training through sparse computation. This model significantly outperforms its predecessor, DeepSeek 67B, by saving 42.5% in training costs, reducing the KV cache by 93.3%, and enhancing generation throughput by 5.76 times. Pretrained on an 8.1 trillion token corpus, DeepSeek-V2 excels in language understanding, coding, and reasoning tasks, making it a top-tier performer among open-source models.Starting Price: Free -
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Falcon 3
Technology Innovation Institute (TII)
Falcon 3 is an open-source large language model (LLM) developed by the Technology Innovation Institute (TII) to make advanced AI accessible to a broader audience. Designed for efficiency, it operates seamlessly on lightweight devices, including laptops, without compromising performance. The Falcon 3 ecosystem comprises four scalable models, each tailored to diverse applications, and supports multiple languages while optimizing resource usage. This latest iteration in TII's LLM series achieves state-of-the-art results in reasoning, language understanding, instruction following, code, and mathematics tasks. By combining high performance with resource efficiency, Falcon 3 aims to democratize access to AI, empowering users across various sectors to leverage advanced technology without the need for extensive computational resources.Starting Price: Free -
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Qwen2.5-Max
Alibaba
Qwen2.5-Max is a large-scale Mixture-of-Experts (MoE) model developed by the Qwen team, pretrained on over 20 trillion tokens and further refined through Supervised Fine-Tuning (SFT) and Reinforcement Learning from Human Feedback (RLHF). In evaluations, it outperforms models like DeepSeek V3 in benchmarks such as Arena-Hard, LiveBench, LiveCodeBench, and GPQA-Diamond, while also demonstrating competitive results in other assessments, including MMLU-Pro. Qwen2.5-Max is accessible via API through Alibaba Cloud and can be explored interactively on Qwen Chat.Starting Price: Free -
23
SmolLM2
Hugging Face
SmolLM2 is a collection of state-of-the-art, compact language models developed for on-device applications. The models in this collection range from 1.7B parameters to smaller 360M and 135M versions, designed to perform efficiently even on less powerful hardware. These models excel in text generation tasks and are optimized for real-time, low-latency applications, providing high-quality results across various use cases, including content creation, coding assistance, and natural language processing. SmolLM2's flexibility makes it a suitable choice for developers looking to integrate powerful AI into mobile devices, edge computing, and other resource-constrained environments.Starting Price: Free -
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QwQ-Max-Preview
Alibaba
QwQ-Max-Preview is an advanced AI model built on the Qwen2.5-Max architecture, designed to excel in deep reasoning, mathematical problem-solving, coding, and agent-related tasks. This preview version offers a sneak peek at its capabilities, which include improved performance in a wide range of general-domain tasks and the ability to handle complex workflows. QwQ-Max-Preview is slated for an official open-source release under the Apache 2.0 license, offering further advancements and refinements in its full version. It also paves the way for a more accessible AI ecosystem, with the upcoming launch of the Qwen Chat app and smaller variants of the model like QwQ-32B, aimed at developers seeking local deployment options.Starting Price: Free -
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Mistral Large 2
Mistral AI
Mistral AI has launched the Mistral Large 2, an advanced AI model designed to excel in code generation, multilingual capabilities, and complex reasoning tasks. The model features a 128k context window, supporting dozens of languages including English, French, Spanish, and Arabic, as well as over 80 programming languages. Mistral Large 2 is tailored for high-throughput single-node inference, making it ideal for large-context applications. Its improved performance on benchmarks like MMLU and its enhanced code generation and reasoning abilities ensure accuracy and efficiency. The model also incorporates better function calling and retrieval, supporting complex business applications.Starting Price: Free -
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EXAONE Deep
LG
EXAONE Deep is a series of reasoning-enhanced language models developed by LG AI Research, featuring parameter sizes of 2.4 billion, 7.8 billion, and 32 billion. These models demonstrate superior capabilities in various reasoning tasks, including math and coding benchmarks. Notably, EXAONE Deep 2.4B outperforms other models of comparable size, EXAONE Deep 7.8B surpasses both open-weight models of similar scale and the proprietary reasoning model OpenAI o1-mini, and EXAONE Deep 32B shows competitive performance against leading open-weight models. The repository provides comprehensive documentation covering performance evaluations, quickstart guides for using EXAONE Deep models with Transformers, explanations of quantized EXAONE Deep weights in AWQ and GGUF formats, and instructions for running EXAONE Deep models locally using frameworks like llama.cpp and Ollama.Starting Price: Free -
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Llama 4 Maverick
Meta
Llama 4 Maverick is one of the most advanced multimodal AI models from Meta, featuring 17 billion active parameters and 128 experts. It surpasses its competitors like GPT-4o and Gemini 2.0 Flash in a broad range of benchmarks, especially in tasks related to coding, reasoning, and multilingual capabilities. Llama 4 Maverick combines image and text understanding, enabling it to deliver industry-leading results in image-grounding tasks and precise, high-quality output. With its efficient performance at a reduced parameter size, Maverick offers exceptional value, especially in general assistant and chat applications.Starting Price: Free -
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GPT-4.1 mini
OpenAI
GPT-4.1 mini is a compact version of OpenAI’s powerful GPT-4.1 model, designed to provide high performance while significantly reducing latency and cost. With a smaller size and optimized architecture, GPT-4.1 mini still delivers impressive results in tasks such as coding, instruction following, and long-context processing. It supports up to 1 million tokens of context, making it an efficient solution for applications that require fast responses without sacrificing accuracy or depth.Starting Price: $0.40 per 1M tokens (input) -
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GPT-4.1 nano
OpenAI
GPT-4.1 nano is the smallest and most efficient version of OpenAI's GPT-4.1 model, optimized for low-latency, cost-effective AI processing. Despite its compact size, GPT-4.1 nano delivers strong performance with a 1 million token context window, making it ideal for applications like classification, autocompletion, and smaller-scale tasks that require fast responses. It provides a highly efficient solution for businesses and developers who need an AI model that balances speed, cost, and performance.Starting Price: $0.10 per 1M tokens (input) -
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Qwen3
Alibaba
Qwen3, the latest iteration of the Qwen family of large language models, introduces groundbreaking features that enhance performance across coding, math, and general capabilities. With models like the Qwen3-235B-A22B and Qwen3-30B-A3B, Qwen3 achieves impressive results compared to top-tier models, thanks to its hybrid thinking modes that allow users to control the balance between deep reasoning and quick responses. The platform supports 119 languages and dialects, making it an ideal choice for global applications. Its pre-training process, which uses 36 trillion tokens, enables robust performance, and advanced reinforcement learning (RL) techniques continue to refine its capabilities. Available on platforms like Hugging Face and ModelScope, Qwen3 offers a powerful tool for developers and researchers working in diverse fields.Starting Price: Free
