Alternatives to Mathstral
Compare Mathstral alternatives for your business or organization using the curated list below. SourceForge ranks the best alternatives to Mathstral in 2026. Compare features, ratings, user reviews, pricing, and more from Mathstral competitors and alternatives in order to make an informed decision for your business.
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1
Solar Pro 2
Upstage AI
Solar Pro 2 is Upstage’s latest frontier‑scale large language model, designed to power complex tasks and agent‑like workflows across domains such as finance, healthcare, and legal. Packaged in a compact 31 billion‑parameter architecture, it delivers top‑tier multilingual performance, especially in Korean, where it outperforms much larger models on benchmarks like Ko‑MMLU, Hae‑Rae, and Ko‑IFEval, while also excelling in English and Japanese. Beyond superior language understanding and generation, Solar Pro 2 offers next‑level intelligence through an advanced Reasoning Mode that significantly boosts multi‑step task accuracy on challenges ranging from general reasoning (MMLU, MMLU‑Pro, HumanEval) to complex mathematics (Math500, AIME) and software engineering (SWE‑Bench Agentless), achieving problem‑solving efficiency comparable to or exceeding that of models twice its size. Enhanced tool‑use capabilities enable the model to interact seamlessly with external APIs and data sources.Starting Price: $0.1 per 1M tokens -
2
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 -
3
Galactica
Meta
Information overload is a major obstacle to scientific progress. The explosive growth in scientific literature and data has made it ever harder to discover useful insights in a large mass of information. Today scientific knowledge is accessed through search engines, but they are unable to organize scientific knowledge alone. Galactica is a large language model that can store, combine and reason about scientific knowledge. We train on a large scientific corpus of papers, reference material, knowledge bases and many other sources. We outperform existing models on a range of scientific tasks. On technical knowledge probes such as LaTeX equations, Galactica outperforms the latest GPT-3 by 68.2% versus 49.0%. Galactica also performs well on reasoning, outperforming Chinchilla on mathematical MMLU by 41.3% to 35.7%, and PaLM 540B on MATH with a score of 20.4% versus 8.8%. -
4
Mistral NeMo
Mistral AI
Mistral NeMo, our new best small model. A state-of-the-art 12B model with 128k context length, and released under the Apache 2.0 license. Mistral NeMo is a 12B model built in collaboration with NVIDIA. Mistral NeMo offers a large context window of up to 128k tokens. Its reasoning, world knowledge, and coding accuracy are state-of-the-art in its size category. As it relies on standard architecture, Mistral NeMo is easy to use and a drop-in replacement in any system using Mistral 7B. We have released pre-trained base and instruction-tuned checkpoints under the Apache 2.0 license to promote adoption for researchers and enterprises. Mistral NeMo was trained with quantization awareness, enabling FP8 inference without any performance loss. The model is designed for global, multilingual applications. It is trained on function calling and has a large context window. Compared to Mistral 7B, it is much better at following precise instructions, reasoning, and handling multi-turn conversations.Starting Price: Free -
5
Mistral Medium 3.1
Mistral AI
Mistral Medium 3.1 is the latest frontier-class multimodal foundation model released in August 2025, designed to deliver advanced reasoning, coding, and multimodal capabilities while dramatically reducing deployment complexity and costs. It builds on the highly efficient architecture of Mistral Medium 3, renowned for offering state-of-the-art performance at up to 8-times lower cost than leading large models, enhancing tone consistency, responsiveness, and accuracy across diverse tasks and modalities. The model supports deployment across hybrid environments, on-premises systems, and virtual private clouds, and it achieves competitive performance relative to high-end models such as Claude Sonnet 3.7, Llama 4 Maverick, and Cohere Command A. Ideal for professional and enterprise use cases, Mistral Medium 3.1 excels in coding, STEM reasoning, language understanding, and multimodal comprehension, while maintaining broad compatibility with custom workflows and infrastructure. -
6
Magistral
Mistral AI
Magistral is Mistral AI’s first reasoning‑focused language model family, released in two sizes: Magistral Small, a 24 B‑parameter open‑weight model under Apache 2.0 (downloadable on Hugging Face), and Magistral Medium, a more capable enterprise version available via Mistral’s API, Le Chat platform, and major cloud marketplaces. Built for domain‑specific, transparent, multilingual reasoning across tasks like math, physics, structured calculations, programmatic logic, decision trees, and rule‑based systems, Magistral produces chain‑of‑thought outputs in the user’s language that you can follow and verify. This launch marks a shift toward compact yet powerful transparent AI reasoning. Magistral Medium is currently available in preview on Le Chat, the API, SageMaker, WatsonX, Azure AI, and Google Cloud Marketplace. Magistral is ideal for general-purpose use requiring longer thought processing and better accuracy than with non-reasoning LLMs. -
7
DeepSeekMath
DeepSeek
DeepSeekMath is a specialized 7B parameter language model developed by DeepSeek-AI, designed to push the boundaries of mathematical reasoning in open-source language models. It starts from the DeepSeek-Coder-v1.5 7B model and undergoes further pre-training with 120B math-related tokens sourced from Common Crawl, alongside natural language and code data. DeepSeekMath has demonstrated remarkable performance, achieving a 51.7% score on the competition-level MATH benchmark without external tools or voting techniques, closely competing with the likes of Gemini-Ultra and GPT-4. The model's capabilities are enhanced by a meticulous data selection pipeline and the introduction of Group Relative Policy Optimization (GRPO), which optimizes both mathematical reasoning and memory usage. DeepSeekMath is available in base, instruct, and RL versions, supporting both research and commercial use, and is aimed at those looking to explore or apply advanced mathematical problem-solving in AI contexts.Starting Price: Free -
8
Claude Opus 3
Anthropic
Opus, our most intelligent model, outperforms its peers on most of the common evaluation benchmarks for AI systems, including undergraduate level expert knowledge (MMLU), graduate level expert reasoning (GPQA), basic mathematics (GSM8K), and more. It exhibits near-human levels of comprehension and fluency on complex tasks, leading the frontier of general intelligence. All Claude 3 models show increased capabilities in analysis and forecasting, nuanced content creation, code generation, and conversing in non-English languages like Spanish, Japanese, and French.Starting Price: Free -
9
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 -
10
Mistral Small 4
Mistral AI
Mistral Small 4 is an advanced open-source AI model developed by Mistral AI that combines reasoning, coding, and multimodal capabilities into a single system. It unifies the strengths of previous models such as Magistral for reasoning, Pixtral for multimodal processing, and Devstral for agentic coding tasks. The model can handle both text and image inputs, allowing it to perform tasks ranging from conversational chat to visual analysis and document understanding. Built with a mixture-of-experts architecture, Mistral Small 4 delivers efficient performance while scaling to complex workloads. It also features a configurable reasoning parameter that allows users to switch between fast responses and deeper analytical outputs. With a large context window and optimized inference performance, the model supports long-form interactions and complex workflows.Starting Price: Free -
11
Ministral 3B
Mistral AI
Mistral AI introduced two state-of-the-art models for on-device computing and edge use cases, named "les Ministraux": Ministral 3B and Ministral 8B. These models set a new frontier in knowledge, commonsense reasoning, function-calling, and efficiency in the sub-10B category. They can be used or tuned for various applications, from orchestrating agentic workflows to creating specialist task workers. Both models support up to 128k context length (currently 32k on vLLM), and Ministral 8B features a special interleaved sliding-window attention pattern for faster and memory-efficient inference. These models were built to provide a compute-efficient and low-latency solution for scenarios such as on-device translation, internet-less smart assistants, local analytics, and autonomous robotics. Used in conjunction with larger language models like Mistral Large, les Ministraux also serve as efficient intermediaries for function-calling in multi-step agentic workflows.Starting Price: Free -
12
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 -
13
Claude Sonnet 3.5
Anthropic
Claude Sonnet 3.5 sets new industry benchmarks for graduate-level reasoning (GPQA), undergraduate-level knowledge (MMLU), and coding proficiency (HumanEval). It shows marked improvement in grasping nuance, humor, and complex instructions, and is exceptional at writing high-quality content with a natural, relatable tone. Claude Sonnet 3.5 operates at twice the speed of Claude Opus 3. This performance boost, combined with cost-effective pricing, makes Claude Sonnet 3.5 ideal for complex tasks such as context-sensitive customer support and orchestrating multi-step workflows. Claude Sonnet 3.5 is now available for free on Claude.ai and the Claude iOS app, while Claude Pro and Team plan subscribers can access it with significantly higher rate limits. It is also available via the Anthropic API, Amazon Bedrock, and Google Cloud’s Vertex AI. The model costs $3 per million input tokens and $15 per million output tokens, with a 200K token context window.Starting Price: Free -
14
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 -
15
DeepScaleR
Agentica Project
DeepScaleR is a 1.5-billion-parameter language model fine-tuned from DeepSeek-R1-Distilled-Qwen-1.5B using distributed reinforcement learning and a novel iterative context-lengthening strategy that gradually increases its context window from 8K to 24K tokens during training. It was trained on ~40,000 carefully curated mathematical problems drawn from competition-level datasets like AIME (1984–2023), AMC (pre-2023), Omni-MATH, and STILL. DeepScaleR achieves 43.1% accuracy on AIME 2024, a roughly 14.3 percentage point boost over the base model, and surpasses the performance of the proprietary O1-Preview model despite its much smaller size. It also posts strong results on a suite of math benchmarks (e.g., MATH-500, AMC 2023, Minerva Math, OlympiadBench), demonstrating that small, efficient models tuned with RL can match or exceed larger baselines on reasoning tasks.Starting Price: Free -
16
Codestral Mamba
Mistral AI
As a tribute to Cleopatra, whose glorious destiny ended in tragic snake circumstances, we are proud to release Codestral Mamba, a Mamba2 language model specialized in code generation, available under an Apache 2.0 license. Codestral Mamba is another step in our effort to study and provide new architectures. It is available for free use, modification, and distribution, and we hope it will open new perspectives in architecture research. Mamba models offer the advantage of linear time inference and the theoretical ability to model sequences of infinite length. It allows users to engage with the model extensively with quick responses, irrespective of the input length. This efficiency is especially relevant for code productivity use cases, this is why we trained this model with advanced code and reasoning capabilities, enabling it to perform on par with SOTA transformer-based models.Starting Price: Free -
17
MathGPT.ai
MathGPT.ai
MathGPT.ai is an AI-driven, cheat-proof math tutoring and course management platform that seamlessly combines a smart course creator with an AI tutor and assignment manager. Educators can integrate pre-loaded OER content, upload custom textbooks, lecture notes, or other resources, then deliver interactive learning experiences as students work directly “within” their materials. The platform guides students through problems using step-by-step reasoning, personalized coaching, and real-time feedback to build deep understanding and confidence. Its proprietary, deterministic AI model is specifically optimized for high accuracy in mathematical reasoning, avoiding typical LLM approximations. Trusted by classrooms, it also features live demos that show how it solves problems and adapts to learning styles, while reinforcing STEM education through curriculum-aligned, infinitely patient instruction.Starting Price: $25 per month -
18
Phi-4-reasoning-plus
Microsoft
Phi-4-reasoning-plus is a 14-billion parameter open-weight reasoning model that builds upon Phi-4-reasoning capabilities. It is further trained with reinforcement learning to utilize more inference-time compute, using 1.5x more tokens than Phi-4-reasoning, to deliver higher accuracy. Despite its significantly smaller size, Phi-4-reasoning-plus achieves better performance than OpenAI o1-mini and DeepSeek-R1 at most benchmarks, including mathematical reasoning and Ph.D. level science questions. It surpasses the full DeepSeek-R1 model (with 671 billion parameters) on the AIME 2025 test, the 2025 qualifier for the USA Math Olympiad. Phi-4-reasoning-plus is available on Azure AI Foundry and HuggingFace. -
19
Qwen2.5-VL-32B
Alibaba
Qwen2.5-VL-32B is a state-of-the-art AI model designed for multimodal tasks, offering advanced capabilities in both text and image reasoning. It builds upon the earlier Qwen2.5-VL series, improving response quality with more human-like, formatted answers. The model excels in mathematical reasoning, fine-grained image understanding, and complex, multi-step reasoning tasks, such as those found in MathVista and MMMU benchmarks. Its superior performance has been demonstrated in comparison to other models, outperforming the larger Qwen2-VL-72B in certain areas. With improved image parsing and visual logic deduction, Qwen2.5-VL-32B provides a detailed, accurate analysis of images and can generate responses based on complex visual inputs. It has been optimized for both text and image tasks, making it ideal for applications requiring sophisticated reasoning and understanding across different media. -
20
Chat Stream
Chat Stream
Chat Stream provides access to two powerful language models from DeepSeek: Model Capabilities Utilizes DeepSeek V3 and R1 models with 671B parameters (37B activated per token) Achieves exceptional benchmark scores: MMLU (87.1%), BBH (87.5%) Features 128K context window length Supports code generation, mathematical computation, and multilingual processing Technical Features Advanced MoE (Mixture-of-Experts) architecture Multi-head Latent Attention (MLA) Auxiliary-loss-free load balancing Multi-token prediction objective Deployment Options Web-based chat interface with instant access One-click website integration via iframe Mobile apps for iOS and Android platforms Compatible with NVIDIA, AMD GPUs, and Huawei Ascend NPUs Supports both local inference and cloud deployment Access Methods Free chat access without registration Website embedding capabilities Mobile applications Premium subscription for ad-free experience -
21
Phi-4-mini-reasoning
Microsoft
Phi-4-mini-reasoning is a 3.8-billion parameter transformer-based language model optimized for mathematical reasoning and step-by-step problem solving in environments with constrained computing or latency. Fine-tuned with synthetic data generated by the DeepSeek-R1 model, it balances efficiency with advanced reasoning ability. Trained on over one million diverse math problems spanning multiple levels of difficulty from middle school to Ph.D. level, Phi-4-mini-reasoning outperforms its base model on long sentence generation across various evaluations and surpasses larger models like OpenThinker-7B, Llama-3.2-3B-instruct, and DeepSeek-R1. It features a 128K-token context window and supports function calling, enabling integration with external tools and APIs. Phi-4-mini-reasoning can be quantized using Microsoft Olive or Apple MLX Framework for deployment on edge devices such as IoT, laptops, and mobile devices. -
22
ThinkUp!
Mentoring Minds
We've built an end-to-end solution that brings the ThinkUp! Standards Mastery System fully into the digital realm, and weaves the 9 Traits of Critical Thinking™ into every aspect of teaching and learning. ThinkUp! equips educators with resources that support a school-wide thinking culture and deepen student engagement with CCSS-aligned content. ThinkUp! Math and ELA were designed to develop students who can process and evaluate information at deeper levels, make informed decisions, solve complex problems, and find reasonable solutions-resulting in mastery of concepts and improved performance. ThinkUp! Math offers consistent opportunities for students to think critically, to apply mathematical reasoning and problem-solving skills, and to participate in learning activities that place emphasis on mathematical processes as well as the final solution.Starting Price: $19.95 per student per year -
23
Mistral Large 3
Mistral AI
Mistral Large 3 is a next-generation, open multimodal AI model built with a powerful sparse Mixture-of-Experts architecture featuring 41B active parameters out of 675B total. Designed from scratch on NVIDIA H200 GPUs, it delivers frontier-level reasoning, multilingual performance, and advanced image understanding while remaining fully open-weight under the Apache 2.0 license. The model achieves top-tier results on modern instruction benchmarks, positioning it among the strongest permissively licensed foundation models available today. With native support across vLLM, TensorRT-LLM, and major cloud providers, Mistral Large 3 offers exceptional accessibility and performance efficiency. Its design enables enterprise-grade customization, letting teams fine-tune or adapt the model for domain-specific workflows and proprietary applications. Mistral Large 3 represents a major advancement in open AI, offering frontier intelligence without sacrificing transparency or control.Starting Price: Free -
24
MiniMax M1
MiniMax
MiniMax‑M1 is a large‑scale hybrid‑attention reasoning model released by MiniMax AI under the Apache 2.0 license. It supports an unprecedented 1 million‑token context window and up to 80,000-token outputs, enabling extended reasoning across long documents. Trained using large‑scale reinforcement learning with a novel CISPO algorithm, MiniMax‑M1 completed full training on 512 H800 GPUs in about three weeks. It achieves state‑of‑the‑art performance on benchmarks in mathematics, coding, software engineering, tool usage, and long‑context understanding, matching or outperforming leading models. Two model variants are available (40K and 80K thinking budgets), with weights and deployment scripts provided via GitHub and Hugging Face. -
25
DeepSeek R1
DeepSeek
DeepSeek-R1 is an advanced open-source reasoning model developed by DeepSeek, designed to rival OpenAI's Model o1. Accessible via web, app, and API, it excels in complex tasks such as mathematics and coding, demonstrating superior performance on benchmarks like the American Invitational Mathematics Examination (AIME) and MATH. DeepSeek-R1 employs a mixture of experts (MoE) architecture with 671 billion total parameters, activating 37 billion parameters per token, enabling efficient and accurate reasoning capabilities. This model is part of DeepSeek's commitment to advancing artificial general intelligence (AGI) through open-source innovation.Starting Price: Free -
26
DeepSeek-V3.2-Speciale
DeepSeek
DeepSeek-V3.2-Speciale is a high-compute variant of the DeepSeek-V3.2 model, created specifically for deep reasoning and advanced problem-solving tasks. It builds on DeepSeek Sparse Attention (DSA), a custom long-context attention mechanism that reduces computational overhead while preserving high performance. Through a large-scale reinforcement learning framework and extensive post-training compute, the Speciale variant surpasses GPT-5 on reasoning benchmarks and matches the capabilities of Gemini-3.0-Pro. The model achieved gold-medal performance in the International Mathematical Olympiad (IMO) 2025 and International Olympiad in Informatics (IOI) 2025. DeepSeek-V3.2-Speciale does not support tool-calling, making it purely optimized for uninterrupted reasoning and analytical accuracy. Released under the MIT license, it provides researchers and developers an open, state-of-the-art model focused entirely on high-precision reasoning.Starting Price: Free -
27
Mistral Small 3.1
Mistral
Mistral Small 3.1 is a state-of-the-art, multimodal, and multilingual AI model released under the Apache 2.0 license. Building upon Mistral Small 3, this enhanced version offers improved text performance, and advanced multimodal understanding, and supports an expanded context window of up to 128,000 tokens. It outperforms comparable models like Gemma 3 and GPT-4o Mini, delivering inference speeds of 150 tokens per second. Designed for versatility, Mistral Small 3.1 excels in tasks such as instruction following, conversational assistance, image understanding, and function calling, making it suitable for both enterprise and consumer-grade AI applications. Its lightweight architecture allows it to run efficiently on a single RTX 4090 or a Mac with 32GB RAM, facilitating on-device deployments. It is available for download on Hugging Face, accessible via Mistral AI's developer playground, and integrated into platforms like Google Cloud Vertex AI, with availability on NVIDIA NIM andStarting Price: Free -
28
MathGPT
MathGPT
MathGPT is an AI-powered math solver and homework assistant designed to help students tackle mathematical problems across various subjects, including algebra, geometry, calculus, and statistics. By allowing users to upload images or PDFs of math problems, MathGPT provides step-by-step solutions, enhancing understanding and learning. MathGPT serves as an on-demand AI math tutor, offering clear explanations to help students grasp complex concepts and build confidence in their mathematical abilities. Trusted by over 2 million students, MathGPT is a free and user-friendly platform that supports learners in improving their math skills. -
29
Ministral 8B
Mistral AI
Mistral AI has introduced two advanced models for on-device computing and edge applications, named "les Ministraux": Ministral 3B and Ministral 8B. These models excel in knowledge, commonsense reasoning, function-calling, and efficiency within the sub-10B parameter range. They support up to 128k context length and are designed for various applications, including on-device translation, offline smart assistants, local analytics, and autonomous robotics. Ministral 8B features an interleaved sliding-window attention pattern for faster and more memory-efficient inference. Both models can function as intermediaries in multi-step agentic workflows, handling tasks like input parsing, task routing, and API calls based on user intent with low latency and cost. Benchmark evaluations indicate that les Ministraux consistently outperforms comparable models across multiple tasks. As of October 16, 2024, both models are available, with Ministral 8B priced at $0.1 per million tokens.Starting Price: Free -
30
Olmo 3
Ai2
Olmo 3 is a fully open model family spanning 7 billion and 32 billion parameter variants that delivers not only high-performing base, reasoning, instruction, and reinforcement-learning models, but also exposure of the entire model flow, including raw training data, intermediate checkpoints, training code, long-context support (65,536 token window), and provenance tooling. Starting with the Dolma 3 dataset (≈9 trillion tokens) and its disciplined mix of web text, scientific PDFs, code, and long-form documents, the pre-training, mid-training, and long-context phases shape the base models, which are then post-trained via supervised fine-tuning, direct preference optimisation, and RL with verifiable rewards to yield the Think and Instruct variants. The 32 B Think model is described as the strongest fully open reasoning model to date, competitively close to closed-weight peers in math, code, and complex reasoning.Starting Price: Free -
31
Math AI
Math AI
Unlock the picture math solver for your inquiries with Math AI, the ultimate Chrome extension designed to help you with your homework. Whether you're dealing with basic calculations, algebra, linear algebra, or physics, our extension is here to assist you in handling equations and concepts with ease. Key Features and Benefits: ● Picture Math Solver: Easily solve math problems by taking a picture with Math AI, saving you time and effort. ● Education Modes: Choose from different modes for tailored assistance—detailed steps for complex problems, quick answers for simple ones, or an interactive AI tutor for personalized guidance. ● Not only math: This tool is not limited to mathematics. It can also be used for subjects like physics, chemistry, biology, and a wide range of other homework tasks. ● 21 Languages: Accessible to a global audience with support for 21 different languages. -
32
Devstral Small 2
Mistral AI
Devstral Small 2 is the compact, 24 billion-parameter variant of the new coding-focused model family from Mistral AI, released under the permissive Apache 2.0 license to enable both local deployment and API use. Alongside its larger sibling (Devstral 2), this model brings “agentic coding” capabilities to environments with modest compute: it supports a large 256K-token context window, enabling it to understand and make changes across entire codebases. On the standard code-generation benchmark (SWE-Bench Verified), Devstral Small 2 scores around 68.0%, placing it among open-weight models many times its size. Because of its reduced size and efficient design, Devstral Small 2 can run on a single GPU or even CPU-only setups, making it practical for developers, small teams, or hobbyists without access to data-center hardware. Despite its compact footprint, Devstral Small 2 retains key capabilities of larger models; it can reason across multiple files and track dependencies.Starting Price: Free -
33
Mistral Agents API
Mistral AI
Mistral AI has introduced its Agents API, a significant advancement aimed at enhancing the capabilities of AI by addressing the limitations of traditional language models in performing actions and maintaining context. This new API integrates Mistral's powerful language models with several key features, built-in connectors for code execution, web search, image generation, and Model Context Protocol (MCP) tools; persistent memory across conversations; and agentic orchestration capabilities. The Agents API complements Mistral's Chat Completion API by providing a dedicated framework that simplifies the implementation of agentic use cases, serving as the backbone of enterprise-grade agentic platforms. It enables developers to build AI agents capable of handling complex tasks, maintaining context, and coordinating multiple actions, thereby making AI more practical and impactful for enterprises. -
34
Smaug-72B
Abacus
Smaug-72B is a powerful open-source large language model (LLM) known for several key features: High Performance: It currently holds the top spot on the Hugging Face Open LLM leaderboard, surpassing models like GPT-3.5 in various benchmarks. This means it excels at tasks like understanding, responding to, and generating human-like text. Open Source: Unlike many other advanced LLMs, Smaug-72B is freely available for anyone to use and modify, fostering collaboration and innovation in the AI community. Focus on Reasoning and Math: It specifically shines in handling reasoning and mathematical tasks, attributing this strength to unique fine-tuning techniques developed by Abacus AI, the creators of Smaug-72B. Based on Qwen-72B: It's technically a fine-tuned version of another powerful LLM called Qwen-72B, released by Alibaba, further improving upon its capabilities. Overall, Smaug-72B represents a significant step forward in open-source AI.Starting Price: Free -
35
Ministral 3
Mistral AI
Mistral 3 is the latest generation of open-weight AI models from Mistral AI, offering a full family of models, from small, edge-optimized versions to a flagship, large-scale multimodal model. The lineup includes three compact “Ministral 3” models (3B, 8B, and 14B parameters) designed for efficiency and deployment on constrained hardware (even laptops, drones, or edge devices), plus the powerful “Mistral Large 3,” a sparse mixture-of-experts model with 675 billion total parameters (41 billion active). The models support multimodal and multilingual tasks, not only text, but also image understanding, and have demonstrated best-in-class performance on general prompts, multilingual conversations, and multimodal inputs. The base and instruction-fine-tuned versions are released under the Apache 2.0 license, enabling broad customization and integration in enterprise and open source projects.Starting Price: Free -
36
Mistral Code
Mistral AI
Mistral Code is an AI-powered coding assistant designed to enhance software engineering productivity in enterprise environments by integrating powerful coding models, in-IDE assistance, local deployment options, and comprehensive enterprise tooling. Built on the open-source Continue project, Mistral Code offers secure, customizable AI coding capabilities while maintaining full control and visibility inside the customer’s IT environment. It supports over 80 programming languages and advanced functionalities such as multi-step refactoring, code search, and chat assistance, enabling developers to complete entire tickets, not just code completions. The platform addresses common enterprise challenges like proprietary repo connectivity, model customization, broad task coverage, and unified service-level agreements (SLAs). Major enterprises such as Abanca, SNCF, and Capgemini have adopted Mistral Code, using hybrid cloud and on-premises deployments. -
37
Mistral 7B
Mistral AI
Mistral 7B is a 7.3-billion-parameter language model that outperforms larger models like Llama 2 13B across various benchmarks. It employs Grouped-Query Attention (GQA) for faster inference and Sliding Window Attention (SWA) to efficiently handle longer sequences. Released under the Apache 2.0 license, Mistral 7B is accessible for deployment across diverse platforms, including local environments and major cloud services. Additionally, a fine-tuned version, Mistral 7B Instruct, demonstrates enhanced performance in instruction-following tasks, surpassing models like Llama 2 13B Chat.Starting Price: Free -
38
Falcon Chat
TII
Falcon LLM is a state-of-the-art open source large language model family developed by the Technology Innovation Institute (TII) that delivers advanced generative AI capabilities for natural language understanding, reasoning, and content generation across diverse applications. Built with hybrid Transformer and Mamba architectures, Falcon models span a range of sizes from compact 7B models with strong reasoning performance to large models like Falcon 180B that rival leading AI systems, making them efficient, scalable, and suitable for real-world tasks including text generation, translation, summarization, sentiment analysis, and chat-style conversational agents. It supports multilingual and multimodal use, handling multiple languages and data types, and integrates capabilities for long context processing, coding, logic, and math reasoning while remaining efficient even on resource-limited environments. -
39
Mistral Saba
Mistral AI
Mistral Saba is a 24-billion-parameter model trained on meticulously curated datasets from across the Middle East and South Asia. The model provides more accurate and relevant responses than models that are over five times its size while being significantly faster and lower cost. It can also serve as a strong base to train highly specific regional adaptations. Mistral Saba is available as an API and can be deployed locally within customers' security premises. Like the recently released Mistral Small 3, the model is lightweight and can be deployed on single-GPU systems, responding at speeds of over 150 tokens per second. In keeping with the rich cultural cross-pollination between the Middle East and South Asia, Mistral Saba supports Arabic and many Indian-origin languages and is particularly strong in South Indian-origin languages such as Tamil. This capability enhances its versatility in multinational use across these interconnected regions.Starting Price: Free -
40
Devstral
Mistral AI
Devstral is an open source, agentic large language model (LLM) developed by Mistral AI in collaboration with All Hands AI, specifically designed for software engineering tasks. It excels at navigating complex codebases, editing multiple files, and resolving real-world issues, outperforming all open source models on the SWE-Bench Verified benchmark with a score of 46.8%. Devstral is fine-tuned from Mistral-Small-3.1 and features a long context window of up to 128,000 tokens. It is optimized for local deployment on high-end hardware, such as a Mac with 32GB RAM or an Nvidia RTX 4090 GPU, and is compatible with inference frameworks like vLLM, Transformers, and Ollama. Released under the Apache 2.0 license, Devstral is available for free and can be accessed via Hugging Face, Ollama, Kaggle, Unsloth, and LM Studio.Starting Price: $0.1 per million input tokens -
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Archetype AI
Archetype AI
We are a physical AI company helping humanity make sense of the world. We solve real world problems using the power of AI to reveal the world’s hidden patterns and behaviors that escape our perception. Newton, a first-of-its-kind AI model that understands the physical world. Our proprietary foundation model can perceive and reason about the physical world in real-time by fusing multimodal sensor data and natural language. With Newton’s ready-to-use model and horizontal AI platform, any physical business can become a business with AI at its core. We invite enterprises and developers to join our design partner program and start using Newton to solve their real-world problems. -
42
GLM-4.7-Flash
Z.ai
GLM-4.7 Flash is a lightweight variant of GLM-4.7, Z.ai’s flagship large language model designed for advanced coding, reasoning, and multi-step task execution with strong agentic performance and a very large context window. It is an MoE-based model optimized for efficient inference that balances performance and resource use, enabling deployment on local machines with moderate memory requirements while maintaining deep reasoning, coding, and agentic task abilities. GLM-4.7 itself advances over earlier generations with enhanced programming capabilities, stable multi-step reasoning, context preservation across turns, and improved tool-calling workflows, and supports very long context lengths (up to ~200 K tokens) for complex tasks that span large inputs or outputs. The Flash variant retains many of these strengths in a smaller footprint, offering competitive benchmark performance in coding and reasoning tasks for models in its size class.Starting Price: Free -
43
Mistral Vibe
Mistral AI
Mistral Vibe is an agentic coding platform developed by Mistral AI that helps developers write, test, and deploy software more efficiently. The system uses specialized AI coding models that understand the full context of a project’s codebase to provide intelligent suggestions and automation. Developers can interact with Vibe through the terminal, IDE extensions, or automated agents that work asynchronously. The platform supports tasks such as code generation, debugging, documentation creation, and test generation. Vibe can analyze entire repositories to refactor code, translate legacy systems to modern stacks, and optimize performance. It integrates with development tools like GitHub, GitLab, and project management platforms to provide contextual insights during development. By combining autonomous coding agents with deep project awareness, Mistral Vibe enables teams to accelerate development while maintaining code quality.Starting Price: Free -
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Grok 4.1 Thinking is xAI’s advanced reasoning-focused AI model designed for deeper analysis, reflection, and structured problem-solving. It uses explicit thinking tokens to reason through complex prompts before delivering a response, resulting in more accurate and context-aware outputs. The model excels in tasks that require multi-step logic, nuanced understanding, and thoughtful explanations. Grok 4.1 Thinking demonstrates a strong, coherent personality while maintaining analytical rigor and reliability. It has achieved the top overall ranking on the LMArena Text Leaderboard, reflecting strong human preference in blind evaluations. The model also shows leading performance in emotional intelligence and creative reasoning benchmarks. Grok 4.1 Thinking is built for users who value clarity, depth, and defensible reasoning in AI interactions.
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45
Phi-4-mini-flash-reasoning
Microsoft
Phi-4-mini-flash-reasoning is a 3.8 billion‑parameter open model in Microsoft’s Phi family, purpose‑built for edge, mobile, and other resource‑constrained environments where compute, memory, and latency are tightly limited. It introduces the SambaY decoder‑hybrid‑decoder architecture with Gated Memory Units (GMUs) interleaved alongside Mamba state‑space and sliding‑window attention layers, delivering up to 10× higher throughput and a 2–3× reduction in latency compared to its predecessor without sacrificing advanced math and logic reasoning performance. Supporting a 64 K‑token context length and fine‑tuned on high‑quality synthetic data, it excels at long‑context retrieval, reasoning tasks, and real‑time inference, all deployable on a single GPU. Phi-4-mini-flash-reasoning is available today via Azure AI Foundry, NVIDIA API Catalog, and Hugging Face, enabling developers to build fast, scalable, logic‑intensive applications. -
46
Claude Sonnet 4.5
Anthropic
Claude Sonnet 4.5 is Anthropic’s latest frontier model, designed to excel in long-horizon coding, agentic workflows, and intensive computer use while maintaining safety and alignment. It achieves state-of-the-art performance on the SWE-bench Verified benchmark (for software engineering) and leads on OSWorld (a computer use benchmark), with the ability to sustain focus over 30 hours on complex, multi-step tasks. The model introduces improvements in tool handling, memory management, and context processing, enabling more sophisticated reasoning, better domain understanding (from finance and law to STEM), and deeper code comprehension. It supports context editing and memory tools to sustain long conversations or multi-agent tasks, and allows code execution and file creation within Claude apps. Sonnet 4.5 is deployed at AI Safety Level 3 (ASL-3), with classifiers protecting against inputs or outputs tied to risky domains, and includes mitigations against prompt injection. -
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OpenAI o1-mini
OpenAI
OpenAI o1-mini is a new, cost-effective AI model designed for enhanced reasoning, particularly excelling in STEM fields like mathematics and coding. It's part of the o1 series, which focuses on solving complex problems by spending more time "thinking" through solutions. Despite being smaller and 80% cheaper than its sibling, the o1-preview, o1-mini performs competitively in coding tasks and mathematical reasoning, making it an accessible option for developers and enterprises looking for efficient AI solutions. -
48
Unsloth
Unsloth
Unsloth is an open source platform designed to accelerate and optimize the fine-tuning and training of Large Language Models (LLMs). It enables users to train custom models, such as ChatGPT, in just 24 hours instead of the typical 30 days, achieving speeds up to 30 times faster than Flash Attention 2 (FA2) while using 90% less memory. Unsloth supports both LoRA and QLoRA fine-tuning techniques, allowing for efficient customization of models like Mistral, Gemma, and Llama versions 1, 2, and 3. Unsloth's efficiency stems from manually deriving computationally intensive mathematical steps and handwriting GPU kernels, resulting in significant performance gains without requiring hardware modifications. Unsloth delivers a 10x speed increase on a single GPU and up to 32x on multi-GPU systems compared to FA2, with compatibility across NVIDIA GPUs from Tesla T4 to H100, and portability to AMD and Intel GPUs.Starting Price: Free -
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Leanstral
Mistral AI
Leanstral is an open-source code agent developed by Mistral AI specifically designed to work with the Lean 4 proof assistant. The model focuses on generating code while also formally verifying its correctness against strict mathematical or software specifications. Unlike traditional coding assistants, Leanstral integrates directly with formal proof systems to ensure that generated code satisfies defined logical requirements. Its architecture is optimized for proof engineering tasks and operates efficiently with sparse model parameters. Leanstral is released under the Apache 2.0 license, making it freely accessible for developers, researchers, and organizations to use and customize. The model is designed to operate within real-world formal repositories rather than isolated problem environments. By combining code generation with formal verification, Leanstral aims to reduce the need for manual human review in complex software and mathematical development.Starting Price: Free -
50
Phi-4
Microsoft
Phi-4 is a 14B parameter state-of-the-art small language model (SLM) that excels at complex reasoning in areas such as math, in addition to conventional language processing. Phi-4 is the latest member of our Phi family of small language models and demonstrates what’s possible as we continue to probe the boundaries of SLMs. Phi-4 is currently available on Azure AI Foundry under a Microsoft Research License Agreement (MSRLA) and will be available on Hugging Face. Phi-4 outperforms comparable and larger models on math related reasoning due to advancements throughout the processes, including the use of high-quality synthetic datasets, curation of high-quality organic data, and post-training innovations. Phi-4 continues to push the frontier of size vs quality.
