Compare the Top Free AI Models as of November 2025 - Page 6

  • 1
    Hermes 4

    Hermes 4

    Nous Research

    Hermes 4 is the latest evolution in Nous Research’s line of neutrally aligned, steerable foundational models, featuring novel hybrid reasoners that can dynamically shift between expressive, creative responses and efficient, standard replies based on user prompts. The model is designed to respond to system and user instructions, rather than adhering to any corporate ethics framework, producing interactions that feel more humanistic, less lecturing or sycophantic, and encouraging roleplay and creativity. By incorporating a special tag in prompts, users can trigger deeper, internally token-intensive reasoning when tackling complex problems, while retaining prompt efficiency when such depth isn't required. Trained on a dataset 50 times larger than that of Hermes 3, much of which was synthetically generated using Atropos, Hermes 4 shows significant performance improvements.
    Starting Price: Free
  • 2
    K2 Think

    K2 Think

    Institute of Foundation Models

    K2 Think is an open source advanced reasoning model developed collaboratively by the Institute of Foundation Models at MBZUAI and G42. Despite only having 32 billion parameters, it delivers performance comparable to flagship models with many more parameters. It excels in mathematical reasoning, achieving top scores on competitive benchmarks such as AIME ’24/’25, HMMT ’25, and OMNI-Math-HARD. K2 Think is part of a suite of UAE-developed open models, alongside Jais (Arabic), NANDA (Hindi), and SHERKALA (Kazakh), and builds on the foundation laid by K2-65B, the fully reproducible open source foundation model released in 2024. The model is designed to be open, fast, and flexible, offering a web app interface for exploration, and with its efficiency in parameter positioning, it is a breakthrough in compact architectures for advanced AI reasoning.
    Starting Price: Free
  • 3
    Ray3

    Ray3

    Luma AI

    Ray3 is an advanced video generation model by Luma Labs, built to help creators tell richer visual stories with pro-level fidelity. It introduces native 16-bit High Dynamic Range (HDR) video generations, enabling more vibrant color, deeper contrasts, and overall pro studio pipelines. The model incorporates sophisticated physics and improved consistency (motion, anatomy, lighting, reflections), supports visual controls, and has a draft mode that lets you explore ideas quickly before up-rendering selected pieces into high-fidelity 4K HDR output. Ray3 can interpret prompts with nuance, reason about intent, self-evaluate early drafts, and adjust to satisfy the articulation of scene and motion more accurately. Other features include support for keyframes, loop and extend functions, upscaling, and export of frames for seamless integration into professional workflows.
    Starting Price: $9.99 per month
  • 4
    DeepSeek-V3.1-Terminus
    DeepSeek has released DeepSeek-V3.1-Terminus, which enhances the V3.1 architecture by incorporating user feedback to improve output stability, consistency, and agent performance. It notably reduces instances of mixed Chinese/English character output and unintended garbled characters, resulting in cleaner, more consistent language generation. The update upgrades both the code agent and search agent subsystems to yield stronger, more reliable performance across benchmarks. DeepSeek-V3.1-Terminus is also available as an open source model, and its weights are published on Hugging Face. The model structure remains the same as DeepSeek-V3, ensuring compatibility with existing deployment methods, with updated inference demos provided for community use. While trained at a scale of 685B parameters, the model includes FP8, BF16, and F32 tensor formats, offering flexibility across environments.
    Starting Price: Free
  • 5
    gpt-4o-mini Realtime
    The gpt-4o-mini-realtime-preview model is a compact, lower-cost, realtime variant of GPT-4o designed to power speech and text interactions with low latency. It supports both text and audio inputs and outputs, enabling “speech in, speech out” conversational experiences via a persistent WebSocket or WebRTC connection. Unlike larger GPT-4o models, it currently does not support image or structured output modalities, focusing strictly on real-time voice/text use cases. Developers can open a real-time session via the /realtime/sessions endpoint to obtain an ephemeral key, then stream user audio (or text) and receive responses in real time over the same connection. The model is part of the early preview family (version 2024-12-17), intended primarily for testing and feedback rather than full production loads. Usage is subject to rate limits and may evolve during the preview period. Because it is multimodal in audio/text only, it enables use cases such as conversational voice agents.
    Starting Price: $0.60 per input
  • 6
    Hunyuan-Vision-1.5
    HunyuanVision is a cutting-edge vision-language model developed by Tencent’s Hunyuan team. It uses a mamba-transformer hybrid architecture to deliver strong performance and efficient inference in multimodal reasoning tasks. The version Hunyuan-Vision-1.5 is designed for “thinking on images,” meaning it not only understands vision+language content, but can perform deeper reasoning that involves manipulating or reflecting on image inputs, such as cropping, zooming, pointing, box drawing, or drawing on the image to acquire additional knowledge. It supports a variety of vision tasks (image + video recognition, OCR, diagram understanding), visual reasoning, and even 3D spatial comprehension, all in a unified multilingual framework. The model is built to work seamlessly across languages and tasks and is intended to be open sourced (including checkpoints, technical report, inference support) to encourage the community to experiment and adopt.
    Starting Price: Free
  • 7
    Gemini Enterprise
    Gemini Enterprise is a comprehensive AI platform built by Google Cloud designed to bring the full power of Google’s advanced AI models, agent-creation tools, and enterprise-grade data access into everyday workflows. The solution offers a unified chat interface that lets employees interact with internal documents, applications, data sources, and custom AI agents. At its core, Gemini Enterprise comprises six key components: the Gemini family of large multimodal models, an agent orchestration workbench (formerly Google Agentspace), pre-built starter agents, robust data-integration connectors to business systems, extensive security and governance controls, and a partner ecosystem for tailored integrations. It is engineered to scale across departments and enterprises, enabling users to build no-code or low-code agents that automate tasks, such as research synthesis, customer support response, code assist, contract analysis, and more, while operating within corporate compliance standards.
    Starting Price: $21 per month
  • 8
    Claude Haiku 4.5
    Anthropic has launched Claude Haiku 4.5, its latest small-language model designed to deliver near-frontier performance at significantly lower cost. The model provides similar coding and reasoning quality as the company’s mid-tier Sonnet 4, yet it runs at roughly one-third of the cost and more than twice the speed. In benchmarks cited by Anthropic, Haiku 4.5 meets or exceeds Sonnet 4’s performance in key tasks such as code generation and multi-step “computer use” workflows. It is optimized for real-time, low-latency scenarios such as chat assistants, customer service agents, and pair-programming support. Haiku 4.5 is made available via the Claude API under the identifier “claude-haiku-4-5” and supports large-scale deployments where cost, responsiveness, and near-frontier intelligence matter. Claude Haiku 4.5 is available now on Claude Code and our apps. Its efficiency means you can accomplish more within your usage limits while maintaining premium model performance.
    Starting Price: $1 per million input tokens
  • 9
    MiniMax M2

    MiniMax M2

    MiniMax

    MiniMax M2 is an open source foundation model built specifically for agentic applications and coding workflows, striking a new balance of performance, speed, and cost. It excels in end-to-end development scenarios, handling programming, tool-calling, and complex, long-chain workflows with capabilities such as Python integration, while delivering inference speeds of around 100 tokens per second and offering API pricing at just ~8% of the cost of comparable proprietary models. The model supports “Lightning Mode” for high-speed, lightweight agent tasks, and “Pro Mode” for in-depth full-stack development, report generation, and web-based tool orchestration; its weights are fully open source and available for local deployment with vLLM or SGLang. MiniMax M2 positions itself as a production-ready model that enables agents to complete independent tasks, such as data analysis, programming, tool orchestration, and large-scale multi-step logic at real organizational scale.
    Starting Price: $0.30 per million input tokens
  • 10
    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
  • 11
    RoBERTa
    RoBERTa builds on BERT’s language masking strategy, wherein the system learns to predict intentionally hidden sections of text within otherwise unannotated language examples. RoBERTa, which was implemented in PyTorch, modifies key hyperparameters in BERT, including removing BERT’s next-sentence pretraining objective, and training with much larger mini-batches and learning rates. This allows RoBERTa to improve on the masked language modeling objective compared with BERT and leads to better downstream task performance. We also explore training RoBERTa on an order of magnitude more data than BERT, for a longer amount of time. We used existing unannotated NLP datasets as well as CC-News, a novel set drawn from public news articles.
    Starting Price: Free
  • 12
    ESMFold
    ESMFold shows how AI can give us new tools to understand the natural world, much like the microscope, which enabled us to see into the world at an infinitesimal scale and opened up a whole new understanding of life. AI can help us understand the immense scope of natural diversity, and see biology in a new way. Much of AI research has focused on helping computers understand the world in a way similar to how humans do. The language of proteins is one that is beyond human comprehension and has eluded even the most powerful computational tools. AI has the potential to open up this language to our understanding. Studying AI in new domains such as biology can also give insight into artificial intelligence more broadly. Our work reveals connections across domains: large language models that are behind advances in machine translation, natural language understanding, speech recognition, and image generation are also able to learn deep information about biology.
    Starting Price: Free
  • 13
    XLNet

    XLNet

    XLNet

    XLNet is a new unsupervised language representation learning method based on a novel generalized permutation language modeling objective. Additionally, XLNet employs Transformer-XL as the backbone model, exhibiting excellent performance for language tasks involving long context. Overall, XLNet achieves state-of-the-art (SOTA) results on various downstream language tasks including question answering, natural language inference, sentiment analysis, and document ranking.
    Starting Price: Free
  • 14
    Hume AI

    Hume AI

    Hume AI

    Our platform is developed in tandem with scientific innovations that reveal how people experience and express over 30 distinct emotions. Expressive understanding and communication is critical to the future of voice assistants, health tech, social networks, and much more. Applications of AI should be supported by collaborative, rigorous, and inclusive science. AI should be prevented from treating human emotion as a means to an end. The benefits of AI should be shared by people from diverse backgrounds. People affected by AI should have enough data to make decisions about its use. AI should be deployed only with the informed consent of the people whom it affects.
    Starting Price: $3/month
  • 15
    FreedomGPT

    FreedomGPT

    Age of AI

    FreedomGPT is a 100% uncensored and private AI chatbot launched by Age of AI, LLC. Our VC firm invests in startups that will define the age of Artificial Intelligence and we hold openness as core. We believe AI will dramatically improve the lives of everyone on this planet if it is deployed responsibly with individual freedom as paramount. It was created to showcase the inevitability and necessity of unbiased and censor free AI. Most importantly it is 100% private. If generative AI is going to be an extension of the human psyche it must not be involuntarily exposed to others. A central Age of AI investing thesis is that everyone and every organization will need their own private LLM. We strive to invest in companies that make this a reality across numerous industry verticals.
    Starting Price: Free
  • 16
    CodeGen

    CodeGen

    Salesforce

    CodeGen is an open-source model for program synthesis. Trained on TPU-v4. Competitive with OpenAI Codex.
    Starting Price: Free
  • 17
    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
  • 18
    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
  • 19
    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
  • 20
    Command R+

    Command R+

    Cohere AI

    Command R+ is Cohere's newest large language model, optimized for conversational interaction and long-context tasks. It aims at being extremely performant, enabling companies to move beyond proof of concept and into production. We recommend using Command R+ for those workflows that lean on complex RAG functionality and multi-step tool use (agents). Command R, on the other hand, is great for simpler retrieval augmented generation (RAG) and single-step tool use tasks, as well as applications where price is a major consideration.
    Starting Price: Free
  • 21
    TinyLlama

    TinyLlama

    TinyLlama

    The TinyLlama project aims to pretrain a 1.1B Llama model on 3 trillion tokens. With some proper optimization, we can achieve this within a span of "just" 90 days using 16 A100-40G GPUs. We adopted exactly the same architecture and tokenizer as Llama 2. This means TinyLlama can be plugged and played in many open-source projects built upon Llama. Besides, TinyLlama is compact with only 1.1B parameters. This compactness allows it to cater to a multitude of applications demanding a restricted computation and memory footprint.
    Starting Price: Free
  • 22
    Pixtral Large

    Pixtral Large

    Mistral AI

    Pixtral Large is a 124-billion-parameter open-weight multimodal model developed by Mistral AI, building upon their Mistral Large 2 architecture. It integrates a 123-billion-parameter multimodal decoder with a 1-billion-parameter vision encoder, enabling advanced understanding of documents, charts, and natural images while maintaining leading text comprehension capabilities. With a context window of 128,000 tokens, Pixtral Large can process at least 30 high-resolution images simultaneously. The model has demonstrated state-of-the-art performance on benchmarks such as MathVista, DocVQA, and VQAv2, surpassing models like GPT-4o and Gemini-1.5 Pro. Pixtral Large is available under the Mistral Research License for research and educational use, and under the Mistral Commercial License for commercial applications.
    Starting Price: Free
  • 23
    Liquid AI

    Liquid AI

    Liquid AI

    Our goal at Liquid is to build the most capable AI systems to solve problems at every scale, such that users can build, access, and control their AI solutions. This is to ensure that AI will be meaningfully, reliably, and efficiently integrated at all enterprises. Long term, Liquid will create and deploy frontier-AI-powered solutions that are available to everyone. We build white-box models within a white-box organization.
  • 24
    MiniMax

    MiniMax

    MiniMax AI

    MiniMax is an advanced AI company offering a suite of AI-native applications for tasks such as video creation, speech generation, music production, and image manipulation. Their product lineup includes tools like MiniMax Chat for conversational AI, Hailuo AI for video storytelling, MiniMax Audio for lifelike speech creation, and various models for generating music and images. MiniMax aims to democratize AI technology, providing powerful solutions for both businesses and individuals to enhance creativity and productivity. Their self-developed AI models are designed to be cost-efficient and deliver top performance across a variety of use cases.
    Starting Price: $14
  • 25
    Qwen2.5-1M

    Qwen2.5-1M

    Alibaba

    Qwen2.5-1M is an open-source language model developed by the Qwen team, designed to handle context lengths of up to one million tokens. This release includes two model variants, Qwen2.5-7B-Instruct-1M and Qwen2.5-14B-Instruct-1M, marking the first time Qwen models have been upgraded to support such extensive context lengths. To facilitate efficient deployment, the team has also open-sourced an inference framework based on vLLM, integrated with sparse attention methods, enabling processing of 1M-token inputs with a 3x to 7x speed improvement. Comprehensive technical details, including design insights and ablation experiments, are available in the accompanying technical report.
    Starting Price: Free
  • 26
    Grok 3 mini
    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
  • 27
    DeepSeek R2

    DeepSeek R2

    DeepSeek

    DeepSeek R2 is the anticipated successor to DeepSeek R1, a groundbreaking AI reasoning model launched in January 2025 by the Chinese AI startup DeepSeek. Building on R1’s success, which disrupted the AI industry with its cost-effective performance rivaling top-tier models like OpenAI’s o1, R2 promises a quantum leap in capabilities. It is expected to deliver exceptional speed and human-like reasoning, excelling in complex tasks such as advanced coding and high-level mathematical problem-solving. Leveraging DeepSeek’s innovative Mixture-of-Experts architecture and efficient training methods, R2 aims to outperform its predecessor while maintaining a low computational footprint, potentially expanding its reasoning abilities to languages beyond English.
    Starting Price: Free
  • 28
    Selene 1
    Atla's Selene 1 API offers state-of-the-art AI evaluation models, enabling developers to define custom evaluation criteria and obtain precise judgments on their AI applications' performance. Selene outperforms frontier models on commonly used evaluation benchmarks, ensuring accurate and reliable assessments. Users can customize evaluations to their specific use cases through the Alignment Platform, allowing for fine-grained analysis and tailored scoring formats. The API provides actionable critiques alongside accurate evaluation scores, facilitating seamless integration into existing workflows. Pre-built metrics, such as relevance, correctness, helpfulness, faithfulness, logical coherence, and conciseness, are available to address common evaluation scenarios, including detecting hallucinations in retrieval-augmented generation applications or comparing outputs to ground truth data.
  • 29
    Mercury Coder

    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
  • 30
    Gemma 3

    Gemma 3

    Google

    Gemma 3, introduced by Google, is a new AI model built on the Gemini 2.0 architecture, designed to offer enhanced performance and versatility. This model is capable of running efficiently on a single GPU or TPU, making it accessible for a wide range of developers and researchers. Gemma 3 focuses on improving natural language understanding, generation, and other AI-driven tasks. By offering scalable, powerful AI capabilities, Gemma 3 aims to advance the development of AI systems across various industries and use cases.
    Starting Price: Free