List of the Top 25 Large Language Models for Amazon Bedrock in 2026

Claude is a powerful AI assistant designed by Anthropic to support problem-solving, creativity, and productivity across a wide range of use cases. It helps users write, edit, analyze, and code by combining conversational AI with advanced reasoning capabilities. Claude allows users to work on documents, software, graphics, and structured data directly within the chat experience. Through features like Artifacts, users can collaborate with Claude to iteratively build and refine projects. The platform supports file uploads, image understanding, and data visualization to enhance how information is processed and presented. Claude also integrates web search results into conversations to provide timely and relevant context. Available on web, iOS, and Android, Claude fits seamlessly into modern workflows. Multiple subscription tiers offer flexibility, from free access to high-usage professional and enterprise plans. Advanced models give users greater depth, speed, and reasoning power for complex tasks. Claude is built with enterprise-grade security and privacy controls to protect sensitive information. Anthropic prioritizes transparency and responsible scaling in Claude’s development. As a result, Claude is positioned as a trusted AI assistant for both everyday tasks and mission-critical work.

Mistral AI is recognized as a pioneering startup in the field of artificial intelligence, with a particular emphasis on open-source generative technologies. The company offers a wide range of customizable, enterprise-grade AI solutions that can be deployed across multiple environments, including on-premises, cloud, edge, and individual devices. Notable among their offerings are "Le Chat," a multilingual AI assistant designed to enhance productivity in both personal and business contexts, and "La Plateforme," a resource for developers that streamlines the creation and implementation of AI-powered applications. Mistral AI's unwavering dedication to transparency and innovative practices has enabled it to carve out a significant niche as an independent AI laboratory, where it plays an active role in the evolution of open-source AI while also influencing relevant policy conversations. By championing the development of an open AI ecosystem, Mistral AI not only contributes to technological advancements but also positions itself as a leading voice within the industry, shaping the future of artificial intelligence. This commitment to fostering collaboration and openness within the AI community further solidifies its reputation as a forward-thinking organization.

Cohere is a powerful enterprise AI platform that enables developers and organizations to build sophisticated applications using language technologies. By prioritizing large language models (LLMs), Cohere delivers cutting-edge solutions for a variety of tasks, including text generation, summarization, and advanced semantic search functions. The platform includes the highly efficient Command family, designed to excel in language-related tasks, as well as Aya Expanse, which provides multilingual support for 23 different languages. With a strong emphasis on security and flexibility, Cohere allows for deployment across major cloud providers, private cloud systems, or on-premises setups to meet diverse enterprise needs. The company collaborates with significant industry leaders such as Oracle and Salesforce, aiming to integrate generative AI into business applications, thereby improving automation and enhancing customer interactions. Additionally, Cohere For AI, the company’s dedicated research lab, focuses on advancing machine learning through open-source projects and nurturing a collaborative global research environment. This ongoing commitment to innovation not only enhances their technological capabilities but also plays a vital role in shaping the future of the AI landscape, ultimately benefiting various sectors and industries.

Claude Sonnet 3.5 from Anthropic is a highly efficient AI model that excels in key areas like graduate-level reasoning (GPQA), undergraduate knowledge (MMLU), and coding proficiency (HumanEval). It significantly outperforms previous models in grasping nuance, humor, and following complex instructions, while producing content with a conversational and relatable tone. With a performance speed twice that of Claude Opus 3, this model is optimized for complex tasks such as orchestrating workflows and providing context-sensitive customer support.

Opus stands out as our leading model, outpacing rival systems across a variety of key metrics used to evaluate artificial intelligence, such as the assessment of undergraduate-level expertise (MMLU), graduate reasoning capabilities (GPQA), and essential mathematics skills (GSM8K), among others. Its exceptional performance is akin to human understanding and fluency when tackling complex challenges, placing it at the cutting edge of developments in general intelligence. Additionally, all Claude 3 models exhibit improved proficiency in analysis and forecasting, advanced content generation, coding, and conversing in multiple languages beyond English, including Spanish, Japanese, and French, highlighting their adaptability in communication. This remarkable versatility not only enhances user interaction but also broadens the potential applications of these models in diverse fields.

Claude Sonnet 3.7, created by Anthropic, is an innovative AI model that brings a unique approach to problem-solving by balancing rapid responses with deep reflective reasoning. This hybrid capability allows users to toggle between quick, efficient answers for everyday tasks and more thoughtful, reflective responses for complex challenges. Its advanced reasoning capabilities make it ideal for tasks like coding, natural language processing, and critical thinking, where nuanced understanding is essential. The ability to pause and reflect before providing an answer helps Claude Sonnet 3.7 tackle intricate problems more effectively, offering professionals and organizations a powerful AI tool that adapts to their specific needs for both speed and accuracy.

Claude Opus 4, the most advanced model in the Claude family, is built to handle the most complex software engineering tasks with ease. It outperforms all previous models, including Sonnet, with exceptional benchmarks in coding precision, debugging, and complex multi-step workflows. Opus 4 is tailored for developers and teams who need a high-performance AI that can tackle challenges over extended periods—perfect for real-time collaboration and long-duration tasks. Its efficiency in multi-agent workflows and problem-solving makes it ideal for companies looking to integrate AI into their development process for sustained impact. Available via the Anthropic API, Amazon Bedrock, and Gemini Enterprise Agent Platform, Opus 4 offers a robust tool for teams working on cutting-edge software development and research.

Claude Opus 4.7 represents a major step forward in AI model development, focusing on advanced reasoning, coding, and enterprise-level task execution. It improves significantly over Opus 4.6 by delivering stronger performance on complex and high-effort software engineering challenges. The model is particularly effective at managing long-running processes, maintaining consistency, and producing reliable outputs over time. Its enhanced instruction-following capabilities ensure that it interprets prompts more literally and executes tasks with greater precision. Opus 4.7 also features advanced self-checking mechanisms, enabling it to validate its own responses before completion. A major highlight is its improved multimodal support, allowing it to process high-resolution images and extract fine visual details. This capability is especially useful for tasks like analyzing technical screenshots, interpreting diagrams, and supporting computer-based workflows. The model produces high-quality professional outputs, including refined documents, presentations, and UI designs that meet business standards. It also demonstrates strong performance across industries such as finance, legal services, and data analysis. Enhanced memory capabilities allow it to retain important context across sessions, making it more efficient for ongoing projects. Opus 4.7 includes safety and alignment improvements, with systems in place to detect and block potentially harmful or restricted use cases. It introduces new controls for balancing reasoning depth and response speed, giving users flexibility based on task complexity. Widely accessible through APIs and major cloud platforms, Opus 4.7 is designed to support scalable, high-performance AI applications for modern enterprises.

DeepSeek-R1 represents a state-of-the-art open-source reasoning model developed by DeepSeek, designed to rival OpenAI's Model o1. Accessible through web, app, and API platforms, it demonstrates exceptional skills in intricate tasks such as mathematics and programming, achieving notable success on exams like the American Invitational Mathematics Examination (AIME) and MATH. This model employs a mixture of experts (MoE) architecture, featuring an astonishing 671 billion parameters, of which 37 billion are activated for every token, enabling both efficient and accurate reasoning capabilities. As part of DeepSeek's commitment to advancing artificial general intelligence (AGI), this model highlights the significance of open-source innovation in the realm of AI. Additionally, its sophisticated features have the potential to transform our methodologies in tackling complex challenges across a variety of fields, paving the way for novel solutions and advancements. The influence of DeepSeek-R1 may lead to a new era in how we understand and utilize AI for problem-solving.

Claude Sonnet 4 is a breakthrough AI model, refining the strengths of Claude Sonnet 3.7 and delivering impressive results across software engineering tasks, coding, and advanced reasoning. With a robust 72.7% on SWE-bench, Sonnet 4 demonstrates remarkable improvements in handling complex tasks, clearer reasoning, and more effective code optimization. The model’s ability to execute complex instructions with higher accuracy and navigate intricate codebases with fewer errors makes it indispensable for developers. Whether for app development or addressing sophisticated software engineering challenges, Sonnet 4 balances performance and efficiency, offering an optimal solution for enterprises and individual developers seeking high-quality AI assistance.

Claude Haiku 3.5 is the next evolution in AI, combining speed, advanced reasoning, and powerful coding capabilities—all at a cost-effective price. Compared to its predecessor, Claude Haiku 3, this model delivers faster processing while surpassing the capabilities of Claude Opus 3, the previous largest model, on key intelligence benchmarks. Developers and businesses alike will benefit from its enhanced tool use, precise reasoning, and swift task execution. With text-only capabilities currently available, and plans for image input support in the future, Haiku 3.5 is the ideal solution for those looking for rapid, reliable, and efficient AI-powered support across various platforms.

Amazon Nova 2 Pro is engineered for organizations that need frontier-grade intelligence to handle sophisticated reasoning tasks that traditional models struggle to solve. It processes text, images, video, and speech in a unified system, enabling deep multimodal comprehension and advanced analytical workflows. Nova 2 Pro shines in challenging environments such as enterprise planning, technical architecture, agentic coding, threat detection, and expert-level problem solving. Its benchmark results show competitive or superior performance against leading AI models across a broad range of intelligence evaluations, validating its capability for the most demanding use cases. With native web grounding and live code execution, the model can pull real-time information, validate outputs, and build solutions that remain aligned with current facts. It also functions as a master model for distillation, allowing teams to produce smaller, faster versions optimized for domain-specific tasks while retaining high intelligence. Its multimodal reasoning capabilities enable analysis of hours-long videos, complex diagrams, transcripts, and multi-source documents in a single workflow. Nova 2 Pro integrates seamlessly with the Nova ecosystem and can be extended using Nova Forge for organizations that want to build their own custom variants. Companies across industries—from cybersecurity to scientific research—are adopting Nova 2 Pro to enhance automation, accelerate innovation, and improve decision-making accuracy. With exceptional reasoning depth and industry-leading versatility, Nova 2 Pro stands as the most capable solution for organizations advancing toward next-generation AI systems.

Claude Opus 4.6 is an advanced AI language model developed by Anthropic, designed to handle complex reasoning, coding, and enterprise-level tasks with high accuracy. It introduces major improvements in planning, debugging, and code review, making it highly effective for software development workflows. The model is capable of sustaining long-running, agentic tasks and performing reliably across large and complex codebases. A key feature of Claude Opus 4.6 is its 1 million token context window in beta, enabling it to process vast amounts of information while maintaining coherence. It excels in knowledge work tasks such as financial analysis, research, and document creation. The model achieves state-of-the-art performance on multiple benchmarks, including coding and reasoning evaluations. Claude Opus 4.6 includes adaptive thinking, allowing it to dynamically adjust how deeply it reasons based on context. Developers can fine-tune performance using configurable effort levels that balance intelligence, speed, and cost. The model also supports context compaction, enabling longer workflows without exceeding limits. Integration with tools like Excel and PowerPoint enhances its usability for everyday business tasks. It maintains a strong safety profile with low rates of misaligned behavior and improved reliability. Overall, Claude Opus 4.6 is a powerful AI solution for advanced technical, analytical, and enterprise applications.

Claude Sonnet 4.6 is the latest evolution in Anthropic’s Sonnet model family, offering major advancements in coding, reasoning, computer interaction, and knowledge-intensive workflows. Designed as a full upgrade rather than an incremental update, it improves consistency, instruction following, and multi-step task completion across a broad range of professional applications. The model introduces a 1 million token context window in beta, enabling users to analyze entire codebases, long contracts, research archives, or complex planning documents in one cohesive session. Developers with early access reported a strong preference for Sonnet 4.6 over Sonnet 4.5 and even favored it over Opus 4.5 in many real-world coding tasks. Users highlighted its reduced overengineering tendencies, improved follow-through, and lower incidence of hallucinations during extended sessions. A major enhancement is its improved computer-use capability, allowing it to operate traditional software environments by interacting with graphical interfaces much like a human user. On benchmarks such as OSWorld, Sonnet models have shown steady gains in handling browser navigation, spreadsheets, and development tools. The model also demonstrates strategic reasoning improvements in long-horizon simulations, such as Vending-Bench Arena, where it optimizes early investments before pivoting toward profitability. On the Claude Developer Platform, Sonnet 4.6 supports adaptive thinking, extended thinking, and context compaction to maximize usable context length. API enhancements now include automated search filtering, code execution, memory, and advanced tool use capabilities for higher-quality outputs. Pricing remains consistent with Sonnet 4.5, making Opus-level performance more accessible to a broader user base. Available across Claude.ai, Cowork, Claude Code, the API, and major cloud platforms, Sonnet 4.6 becomes the new default model for Free and Pro users.

Mistral 7B is a cutting-edge language model boasting 7.3 billion parameters, which excels in various benchmarks, even surpassing larger models such as Llama 2 13B. It employs advanced methods like Grouped-Query Attention (GQA) to enhance inference speed and Sliding Window Attention (SWA) to effectively handle extensive sequences. Available under the Apache 2.0 license, Mistral 7B can be deployed across multiple platforms, including local infrastructures and major cloud services. Additionally, a unique variant called Mistral 7B Instruct has demonstrated exceptional abilities in task execution, consistently outperforming rivals like Llama 2 13B Chat in certain applications. This adaptability and performance make Mistral 7B a compelling choice for both developers and researchers seeking efficient solutions. Its innovative features and strong results highlight the model's potential impact on natural language processing projects.

In tribute to Cleopatra, whose dramatic story ended with the fateful encounter with a snake, we proudly present Codestral Mamba, a Mamba2 language model tailored for code generation and made available under an Apache 2.0 license. Codestral Mamba marks a pivotal step forward in our commitment to pioneering and refining innovative architectures. This model is available for free use, modification, and distribution, and we hope it will pave the way for new discoveries in architectural research. The Mamba models stand out due to their linear time inference capabilities, coupled with a theoretical ability to manage sequences of infinite length. This unique characteristic allows users to engage with the model seamlessly, delivering quick responses irrespective of the input size. Such remarkable efficiency is especially beneficial for boosting coding productivity; hence, we have integrated advanced coding and reasoning abilities into this model, ensuring it can compete with top-tier transformer-based models. As we push the boundaries of innovation, we are confident that Codestral Mamba will not only advance coding practices but also inspire new generations of developers. This exciting release underscores our dedication to fostering creativity and productivity within the tech community.

We are excited to unveil Mistral NeMo, our latest and most sophisticated small model, boasting an impressive 12 billion parameters and a vast context length of 128,000 tokens, all available under the Apache 2.0 license. In collaboration with NVIDIA, Mistral NeMo stands out in its category for its exceptional reasoning capabilities, extensive world knowledge, and coding skills. Its architecture adheres to established industry standards, ensuring it is user-friendly and serves as a smooth transition for those currently using Mistral 7B. To encourage adoption by researchers and businesses alike, we are providing both pre-trained base models and instruction-tuned checkpoints, all under the Apache license. A remarkable feature of Mistral NeMo is its quantization awareness, which enables FP8 inference while maintaining high performance levels. Additionally, the model is well-suited for a range of global applications, showcasing its ability in function calling and offering a significant context window. When benchmarked against Mistral 7B, Mistral NeMo demonstrates a marked improvement in comprehending and executing intricate instructions, highlighting its advanced reasoning abilities and capacity to handle complex multi-turn dialogues. Furthermore, its design not only enhances its performance but also positions it as a formidable option for multi-lingual tasks, ensuring it meets the diverse needs of various use cases while paving the way for future innovations.

The Mixtral 8x22B is our latest open model, setting a new standard in performance and efficiency within the realm of AI. By utilizing a sparse Mixture-of-Experts (SMoE) architecture, it activates only 39 billion parameters out of a total of 141 billion, leading to remarkable cost efficiency relative to its size. Moreover, it exhibits proficiency in several languages, such as English, French, Italian, German, and Spanish, alongside strong capabilities in mathematics and programming. Its native function calling feature, paired with the constrained output mode used on la Plateforme, greatly aids in application development and the large-scale modernization of technology infrastructures. The model boasts a context window of up to 64,000 tokens, allowing for precise information extraction from extensive documents. We are committed to designing models that optimize cost efficiency, thus providing exceptional performance-to-cost ratios compared to alternatives available in the market. As a continuation of our open model lineage, the Mixtral 8x22B's sparse activation patterns enhance its speed, making it faster than any similarly sized dense 70 billion model available. Additionally, its pioneering design and performance metrics make it an outstanding option for developers in search of high-performance AI solutions, further solidifying its position as a vital asset in the fast-evolving tech landscape.

This year marks the 2311th anniversary of Archimedes, and in his honor, we are thrilled to unveil our first Mathstral model, a dedicated 7B architecture crafted specifically for mathematical reasoning and scientific inquiry. With a context window of 32k, this model is made available under the Apache 2.0 license. Our goal in sharing Mathstral with the scientific community is to facilitate the tackling of complex mathematical problems that require sophisticated, multi-step logical reasoning. The introduction of Mathstral aligns with our broader initiative to bolster academic efforts, developed alongside Project Numina. Much like Isaac Newton's contributions during his lifetime, Mathstral builds upon the groundwork established by Mistral 7B, with a keen focus on STEM fields. It showcases exceptional reasoning abilities within its domain, achieving impressive results across numerous industry-standard benchmarks. Specifically, it registers a score of 56.6% on the MATH benchmark and 63.47% on the MMLU benchmark, highlighting the performance enhancements in comparison to its predecessor, Mistral 7B, and underscoring the strides made in mathematical modeling. In addition to advancing individual research, this initiative seeks to inspire greater innovation and foster collaboration within the mathematical community as a whole.

Mistral AI has introduced two state-of-the-art models aimed at on-device computing and edge applications, collectively known as "les Ministraux": Ministral 3B and Ministral 8B. These advanced models set new benchmarks for knowledge, commonsense reasoning, function-calling, and efficiency in the sub-10B category. They offer remarkable flexibility for a variety of applications, from overseeing complex workflows to creating specialized task-oriented agents. With the capability to manage an impressive context length of up to 128k (currently supporting 32k on vLLM), Ministral 8B features a distinctive interleaved sliding-window attention mechanism that boosts both speed and memory efficiency during inference. Crafted for low-latency and compute-efficient applications, these models thrive in environments such as offline translation, internet-independent smart assistants, local data processing, and autonomous robotics. Additionally, when integrated with larger language models like Mistral Large, les Ministraux can serve as effective intermediaries, enhancing function-calling within detailed multi-step workflows. This synergy not only amplifies performance but also extends the potential of AI in edge computing, paving the way for innovative solutions in various fields. The introduction of these models marks a significant step forward in making advanced AI more accessible and efficient for real-world applications.

Mistral AI has introduced two advanced models tailored for on-device computing and edge applications, collectively known as "les Ministraux": Ministral 3B and Ministral 8B. These models are particularly remarkable for their abilities in knowledge retention, commonsense reasoning, function-calling, and overall operational efficiency, all while being under the 10B parameter threshold. With support for an impressive context length of up to 128k, they cater to a wide array of applications, including on-device translation, offline smart assistants, local analytics, and autonomous robotics. A standout feature of the Ministral 8B is its incorporation of an interleaved sliding-window attention mechanism, which significantly boosts both the speed and memory efficiency during inference. Both models excel in acting as intermediaries in intricate multi-step workflows, adeptly managing tasks such as input parsing, task routing, and API interactions according to user intentions while keeping latency and operational costs to a minimum. Benchmark results indicate that les Ministraux consistently outperform comparable models across numerous tasks, further cementing their competitive edge in the market. As of October 16, 2024, these innovative models are accessible to developers and businesses, with the Ministral 8B priced competitively at $0.1 per million tokens used. This pricing model promotes accessibility for users eager to incorporate sophisticated AI functionalities into their projects, potentially revolutionizing how AI is utilized in everyday applications.

On September 17, 2024, Mistral AI announced a series of important enhancements aimed at making their AI products more accessible and efficient. Among these advancements, they introduced a free tier on "La Plateforme," their serverless platform that facilitates the tuning and deployment of Mistral models as API endpoints, enabling developers to experiment and create without any cost. Additionally, Mistral AI implemented significant price reductions across their entire model lineup, featuring a striking 50% reduction for Mistral Nemo and an astounding 80% decrease for Mistral Small and Codestral, making sophisticated AI solutions much more affordable for a larger audience. Furthermore, the company unveiled Mistral Small v24.09, a model boasting 22 billion parameters, which offers an excellent balance between performance and efficiency, suitable for a range of applications such as translation, summarization, and sentiment analysis. They also launched Pixtral 12B, a vision-capable model with advanced image understanding functionalities, available for free on "Le Chat," which allows users to analyze and caption images while ensuring strong text-based performance. These updates not only showcase Mistral AI's dedication to enhancing their offerings but also underscore their mission to make cutting-edge AI technology accessible to developers across the globe. This commitment to accessibility and innovation positions Mistral AI as a leader in the AI industry.

The Mixtral 8x7B model represents a cutting-edge sparse mixture of experts (SMoE) architecture that features open weights and is made available under the Apache 2.0 license. This innovative model outperforms Llama 2 70B across a range of benchmarks, while also achieving inference speeds that are sixfold faster. As the premier open-weight model with a versatile licensing structure, Mixtral stands out for its impressive cost-effectiveness and performance metrics. Furthermore, it competes with and frequently exceeds the capabilities of GPT-3.5 in many established benchmarks, underscoring its importance in the AI landscape. Its unique blend of accessibility, rapid processing, and overall effectiveness positions it as an attractive option for developers in search of top-tier AI solutions. Consequently, the Mixtral model not only enhances the current technological landscape but also paves the way for future advancements in AI development.

We have integrated Llama 3 into Meta AI, our smart assistant that transforms the way people perform tasks, innovate, and interact with technology. By leveraging Meta AI for coding and troubleshooting, users can directly experience the power of Llama 3. Whether you are developing agents or other AI-based solutions, Llama 3, which is offered in both 8B and 70B variants, delivers the essential features and adaptability needed to turn your concepts into reality. In conjunction with the launch of Llama 3, we have updated our Responsible Use Guide (RUG) to provide comprehensive recommendations on the ethical development of large language models. Our approach focuses on enhancing trust and safety measures, including the introduction of Llama Guard 2, which aligns with the newly established taxonomy from MLCommons and expands its coverage to include a broader range of safety categories, alongside code shield and Cybersec Eval 2. Moreover, these improvements are designed to promote a safer and more responsible application of AI technologies across different fields, ensuring that users can confidently harness these innovations. The commitment to ethical standards reflects our dedication to fostering a secure and trustworthy AI environment.

We are thrilled to introduce Codestral, our first code generation model. This generative AI system, featuring open weights, is designed explicitly for code generation tasks, allowing developers to effortlessly write and interact with code through a single instruction and completion API endpoint. As it gains expertise in both programming languages and English, Codestral is set to enhance the development of advanced AI applications specifically for software engineers. The model is built on a robust foundation that includes a diverse selection of over 80 programming languages, spanning popular choices like Python, Java, C, C++, JavaScript, and Bash, as well as less common languages such as Swift and Fortran. This broad language support guarantees that developers have the tools they need to address a variety of coding challenges and projects. Furthermore, Codestral’s rich language capabilities enable developers to work with confidence across different coding environments, solidifying its role as an essential resource in the programming community. Ultimately, Codestral stands to revolutionize the way developers approach code generation and project execution.