Alternatives to DataGemma
Compare DataGemma alternatives for your business or organization using the curated list below. SourceForge ranks the best alternatives to DataGemma in 2026. Compare features, ratings, user reviews, pricing, and more from DataGemma competitors and alternatives in order to make an informed decision for your business.
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LM-Kit.NET
LM-Kit
LM-Kit.NET is a cutting-edge, high-level inference SDK designed specifically to bring the advanced capabilities of Large Language Models (LLM) into the C# ecosystem. Tailored for developers working within .NET, LM-Kit.NET provides a comprehensive suite of powerful Generative AI tools, making it easier than ever to integrate AI-driven functionality into your applications. The SDK is versatile, offering specialized AI features that cater to a variety of industries. These include text completion, Natural Language Processing (NLP), content retrieval, text summarization, text enhancement, language translation, and much more. Whether you are looking to enhance user interaction, automate content creation, or build intelligent data retrieval systems, LM-Kit.NET offers the flexibility and performance needed to accelerate your project. -
2
Gemma
Google
Gemma is a family of lightweight, state-of-the-art open models built from the same research and technology used to create the Gemini models. Developed by Google DeepMind and other teams across Google, Gemma is inspired by Gemini, and the name reflects the Latin gemma, meaning “precious stone.” Accompanying our model weights, we’re also releasing tools to support developer innovation, foster collaboration, and guide the responsible use of Gemma models. Gemma models share technical and infrastructure components with Gemini, our largest and most capable AI model widely available today. This enables Gemma 2B and 7B to achieve best-in-class performance for their sizes compared to other open models. And Gemma models are capable of running directly on a developer laptop or desktop computer. Notably, Gemma surpasses significantly larger models on key benchmarks while adhering to our rigorous standards for safe and responsible outputs. -
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 -
4
Gemma 4
Google
Gemma 4 is an AI model introduced by Google and built on the Gemini architecture to deliver improved performance and flexibility. The model is designed to run efficiently on a single GPU or TPU, making it more accessible to developers and researchers. Gemma 4 enhances capabilities in natural language understanding and text generation, supporting a wide range of AI-driven applications. Its architecture allows it to handle complex tasks while maintaining efficient resource usage. Developers can use the model to build applications that rely on advanced language processing and automation. The design emphasizes scalability so that it can support both smaller projects and larger AI systems. By combining efficiency with powerful language capabilities, Gemma 4 helps advance the development of modern AI solutions.Starting Price: Free -
5
CodeGemma
Google
CodeGemma is a collection of powerful, lightweight models that can perform a variety of coding tasks like fill-in-the-middle code completion, code generation, natural language understanding, mathematical reasoning, and instruction following. CodeGemma has 3 model variants, a 7B pre-trained variant that specializes in code completion and generation from code prefixes and/or suffixes, a 7B instruction-tuned variant for natural language-to-code chat and instruction following; and a state-of-the-art 2B pre-trained variant that provides up to 2x faster code completion. Complete lines, and functions, and even generate entire blocks of code, whether you're working locally or using Google Cloud resources. Trained on 500 billion tokens of primarily English language data from web documents, mathematics, and code, CodeGemma models generate code that's not only more syntactically correct but also semantically meaningful, reducing errors and debugging time. -
6
Gemma 2
Google
A family of state-of-the-art, light-open models created from the same research and technology that were used to create Gemini models. These models incorporate comprehensive security measures and help ensure responsible and reliable AI solutions through selected data sets and rigorous adjustments. Gemma models achieve exceptional comparative results in their 2B, 7B, 9B, and 27B sizes, even outperforming some larger open models. With Keras 3.0, enjoy seamless compatibility with JAX, TensorFlow, and PyTorch, allowing you to effortlessly choose and change frameworks based on task. Redesigned to deliver outstanding performance and unmatched efficiency, Gemma 2 is optimized for incredibly fast inference on various hardware. The Gemma family of models offers different models that are optimized for specific use cases and adapt to your needs. Gemma models are large text-to-text lightweight language models with a decoder, trained in a huge set of text data, code, and mathematical content. -
7
Grounded Language Model (GLM)
Contextual AI
Contextual AI introduces its Grounded Language Model (GLM), engineered specifically to minimize hallucinations and deliver highly accurate, source-based responses for retrieval-augmented generation (RAG) and agentic applications. The GLM prioritizes faithfulness to the provided data, ensuring responses are grounded in specific knowledge sources and backed by inline citations. With state-of-the-art performance on the FACTS groundedness benchmark, the GLM outperforms other foundation models in scenarios requiring high accuracy and reliability. The model is designed for enterprise use cases like customer service, finance, and engineering, where trustworthy and precise responses are critical to minimizing risks and improving decision-making. -
8
PaliGemma 2
Google
PaliGemma 2, the next evolution in tunable vision-language models, builds upon the performant Gemma 2 models, adding the power of vision and making it easier than ever to fine-tune for exceptional performance. With PaliGemma 2, these models can see, understand, and interact with visual input, opening up a world of new possibilities. It offers scalable performance with multiple model sizes (3B, 10B, 28B parameters) and resolutions (224px, 448px, 896px). PaliGemma 2 generates detailed, contextually relevant captions for images, going beyond simple object identification to describe actions, emotions, and the overall narrative of the scene. Our research demonstrates leading performance in chemical formula recognition, music score recognition, spatial reasoning, and chest X-ray report generation, as detailed in the technical report. Upgrading to PaliGemma 2 is a breeze for existing PaliGemma users. -
9
TranslateGemma
Google
TranslateGemma is a new suite of open machine translation models from Google built on the Gemma 3 foundation that lets people and systems communicate across 55 languages with high-quality AI translation while maintaining efficiency and broad deployment flexibility. Available in 4 B, 12 B, and 27 B parameter sizes, TranslateGemma distills advanced multilingual capabilities into compact models that can run on mobile devices, consumer laptops, local machines, or cloud hardware without sacrificing accuracy or performance; technical evaluations show the 12 B version can outperform larger baseline models with lower compute demands. The models were developed through a specialized two-stage fine-tuning process combining high-quality human and synthetic translation data with reinforcement learning to optimize translation quality across diverse language families.Starting Price: Free -
10
Falcon 2
Technology Innovation Institute (TII)
Falcon 2 11B is an open-source, multilingual, and multimodal AI model, uniquely equipped with vision-to-language capabilities. It surpasses Meta’s Llama 3 8B and delivers performance on par with Google’s Gemma 7B, as independently confirmed by the Hugging Face Leaderboard. Looking ahead, the next phase of development will integrate a 'Mixture of Experts' approach to further enhance Falcon 2’s capabilities, pushing the boundaries of AI innovation.Starting Price: Free -
11
MedGemma
Google DeepMind
MedGemma is a collection of Gemma 3 variants that are trained for performance on medical text and image comprehension. Developers can use MedGemma to accelerate building healthcare-based AI applications. MedGemma currently comes in two variants: a 4B multimodal version and a 27B text-only version. MedGemma 4B utilizes a SigLIP image encoder that has been specifically pre-trained on a variety of de-identified medical data, including chest X-rays, dermatology images, ophthalmology images, and histopathology slides. Its LLM component is trained on a diverse set of medical data, including radiology images, histopathology patches, ophthalmology images, and dermatology images. MedGemma 4B is available in both pre-trained (suffix: -pt) and instruction-tuned (suffix -it) versions. The instruction-tuned version is a better starting point for most applications. -
12
Gemma 3n
Google DeepMind
Gemma 3n is our state-of-the-art open multimodal model, engineered for on-device performance and efficiency. Made for responsive, low-footprint local inference, Gemma 3n empowers a new wave of intelligent, on-the-go applications. It analyzes and responds to combined images and text, with video and audio coming soon. Build intelligent, interactive features that put user privacy first and work reliably offline. Mobile-first architecture, with a significantly reduced memory footprint. Co-designed by Google's mobile hardware teams and industry leaders. 4B active memory footprint with the ability to create submodels for quality-latency tradeoffs. Gemma 3n is our first open model built on this groundbreaking, shared architecture, allowing developers to begin experimenting with this technology today in an early preview. -
13
GPT-5.2 Pro
OpenAI
GPT-5.2 Pro is the highest-capability variant of OpenAI’s latest GPT-5.2 model family, built to deliver professional-grade reasoning, complex task performance, and enhanced accuracy for demanding knowledge work, creative problem-solving, and enterprise-level applications. It builds on the foundational improvements of GPT-5.2, including stronger general intelligence, superior long-context understanding, better factual grounding, and improved tool use, while using more compute and deeper processing to produce more thoughtful, reliable, and context-rich responses for users with intricate, multi-step requirements. GPT-5.2 Pro is designed to handle challenging workflows such as advanced coding and debugging, deep data analysis, research synthesis, extensive document comprehension, and complex project planning with greater precision and fewer errors than lighter variants. -
14
Gemma
Ceros
Meet Gemma, your new creative AI sidekick. Generate new ideas, optimize existing designs, and automate tedious tasks so you can focus on your creative vision. Ask Gemma for help writing just about anything, from headlines and body text to brand names. Gemma is capable of creating ultra realistic imagery, which can be upscaled and edited. Gemma is online 24/7. An intuitive interface unlocks countless AI models and connects to many creative tools you’re already familiar with. Gemma is programmed to learn from your ideas and preferences and to provide suggestions and insights that you might not have considered before. Easy to install onto your desktop allowing you to take Gemma with you to any file or application. That daunting blank canvas? Conquered. With advanced algorithms, Gemma can power your creative vision. -
15
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 -
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GPT-5 thinking
OpenAI
GPT-5 Thinking is the deeper reasoning mode within the GPT-5 unified AI system, designed to tackle complex, open-ended problems that require extended cognitive effort. It works alongside the faster GPT-5 model, dynamically engaging when queries demand more detailed analysis and thoughtful responses. This mode significantly reduces hallucinations and improves factual accuracy, producing more reliable answers on challenging topics like science, math, coding, and health. GPT-5 Thinking is also better at recognizing its own limitations, communicating clearly when tasks are impossible or underspecified. It incorporates advanced safety features to minimize harmful outputs and provide nuanced, helpful answers even in ambiguous or sensitive contexts. Available to all users, it helps bring expert-level intelligence to everyday and advanced use cases alike. -
17
Amazon Nova 2 Pro
Amazon
Amazon Nova 2 Pro is Amazon’s most advanced reasoning model, designed to handle highly complex, multimodal tasks across text, images, video, and speech with exceptional accuracy. It excels in deep problem-solving scenarios such as agentic coding, multi-document analysis, long-range planning, and advanced math. With benchmark performance equal or superior to leading models like Claude Sonnet 4.5, GPT-5.1, and Gemini Pro, Nova 2 Pro delivers top-tier intelligence across a wide range of enterprise workloads. The model includes built-in web grounding and code execution, ensuring responses remain factual, current, and contextually accurate. Nova 2 Pro can also serve as a “teacher model,” enabling knowledge distillation into smaller, purpose-built variants for specific domains. It is engineered for organizations that require precision, reliability, and frontier-level reasoning in mission-critical AI applications. -
18
Selene 1
atla
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. -
19
ERNIE X1.1
Baidu
ERNIE X1.1 is Baidu’s upgraded reasoning model that delivers major improvements over its predecessor. It achieves 34.8% higher factual accuracy, 12.5% better instruction following, and 9.6% stronger agentic capabilities compared to ERNIE X1. In benchmark testing, it surpasses DeepSeek R1-0528 and performs on par with GPT-5 and Gemini 2.5 Pro. Built on the foundation of ERNIE 4.5, it has been enhanced with extensive mid-training and post-training, including reinforcement learning. The model is available through ERNIE Bot, the Wenxiaoyan app, and Baidu’s Qianfan MaaS platform via API. These upgrades are designed to reduce hallucinations, improve reliability, and strengthen real-world AI task performance. -
20
UpTrain
UpTrain
Get scores for factual accuracy, context retrieval quality, guideline adherence, tonality, and many more. You can’t improve what you can’t measure. UpTrain continuously monitors your application's performance on multiple evaluation criterions and alerts you in case of any regressions with automatic root cause analysis. UpTrain enables fast and robust experimentation across multiple prompts, model providers, and custom configurations, by calculating quantitative scores for direct comparison and optimal prompt selection. Hallucinations have plagued LLMs since their inception. By quantifying degree of hallucination and quality of retrieved context, UpTrain helps to detect responses with low factual accuracy and prevent them before serving to the end-users. -
21
GPT-5.2 Instant
OpenAI
GPT-5.2 Instant is the fast, capable variant of OpenAI’s GPT-5.2 model family designed for everyday work and learning with clear improvements in information-seeking questions, how-tos and walkthroughs, technical writing, and translation compared to prior versions. It builds on the warmer conversational tone introduced in GPT-5.1 Instant and produces clearer explanations that surface key information upfront, making it easier for users to get concise, accurate answers quickly. GPT-5.2 Instant delivers speed and responsiveness for typical tasks like answering queries, generating summaries, assisting with research, and helping with writing and editing, while incorporating broader enhancements from the GPT-5.2 series in reasoning, long-context handling, and factual grounding. As part of the GPT-5.2 lineup, it shares the same foundational improvements that boost overall reliability and performance across a wide range of everyday activities. -
22
Amazon Titan
Amazon
Amazon Titan is a series of advanced foundation models (FMs) from AWS, designed to enhance generative AI applications with high performance and flexibility. Built on AWS's 25 years of AI and machine learning experience, Titan models support a range of use cases such as text generation, summarization, semantic search, and image generation. Titan models are optimized for responsible AI use, incorporating built-in safety features and fine-tuning capabilities. They can be customized with your own data through Retrieval Augmented Generation (RAG) to improve accuracy and relevance, making them ideal for both general-purpose and specialized AI tasks. -
23
EmbeddingGemma
Google
EmbeddingGemma is a 308-million-parameter multilingual text embedding model, lightweight yet powerful, optimized to run entirely on everyday devices such as phones, laptops, and tablets, enabling fast, offline embedding generation that protects user privacy. Built on the Gemma 3 architecture, it supports over 100 languages, processes up to 2,000 input tokens, and leverages Matryoshka Representation Learning (MRL) to offer flexible embedding dimensions (768, 512, 256, or 128) for tailored speed, storage, and precision. Its GPU-and EdgeTPU-accelerated inference delivers embeddings in milliseconds, under 15 ms for 256 tokens on EdgeTPU, while quantization-aware training keeps memory usage under 200 MB without compromising quality. This makes it ideal for real-time, on-device tasks such as semantic search, retrieval-augmented generation (RAG), classification, clustering, and similarity detection, whether for personal file search, mobile chatbots, or custom domain use. -
24
GPT-5.4
OpenAI
GPT-5.4 is an advanced artificial intelligence model developed by OpenAI to support complex professional and technical work. The model combines improvements in reasoning, coding, and agent-based workflows into a single system designed for real-world productivity tasks. GPT-5.4 can generate, analyze, and edit documents, spreadsheets, presentations, and other work outputs with greater accuracy and efficiency. It also features improved tool integration, enabling the model to interact with software environments and external tools to complete multi-step workflows. With enhanced context capabilities supporting up to one million tokens, GPT-5.4 can process and reason over very large amounts of information. The model also improves factual accuracy and reduces errors compared to earlier versions. By combining strong reasoning, coding ability, and tool use, GPT-5.4 helps users complete complex tasks faster and with fewer iterations. -
25
LTM-1
Magic AI
Magic’s LTM-1 enables 50x larger context windows than transformers. Magic's trained a Large Language Model (LLM) that’s able to take in the gigantic amounts of context when generating suggestions. For our coding assistant, this means Magic can now see your entire repository of code. Larger context windows can allow AI models to reference more explicit, factual information and their own action history. We hope to be able to utilize this research to improve reliability and coherence. -
26
OpenGPT-X
OpenGPT-X
OpenGPT-X is a German initiative focused on developing large AI language models tailored to European needs, emphasizing versatility, trustworthiness, multilingual capabilities, and open-source accessibility. The project brings together a consortium of partners to cover the entire generative AI value chain, from scalable, GPU-based infrastructure and data for training large language models to model design and practical applications through prototypes and proofs of concept. OpenGPT-X aims to advance cutting-edge research with a strong focus on business applications, thereby accelerating the adoption of generative AI in the German economy. The project also emphasizes responsible AI development, ensuring that the models are trustworthy and align with European values and regulations. The project provides resources such as the LLM Workbook, and a three-part reference guide with resources and examples to help users understand the key features of large AI language models.Starting Price: Free -
27
Sup AI
Sup AI
Sup AI is a multi-LLM platform that merges outputs from several top large language models, such as GPT, Claude, Llama, and more, to generate richer, more accurate, and better-validated answers than any single model could provide. It applies real-time “logprob confidence scoring,” analyzing each token’s probability to detect uncertainty or hallucination; when a model’s confidence falls below a threshold, the response is halted, helping ensure that delivered answers remain high-quality and trustworthy. Sup’s “multi-model fusion” then compares, contrasts, and consolidates outputs from different models, cross-verifying and synthesizing the best parts into a final result. Sup also supports “multimodal RAG” (retrieval-augmented generation) to incorporate external data (text, PDFs, images) into context-aware responses, giving the AI access to factual sources and helping it “never forget” relevant information.Starting Price: $20 per month -
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Eternity AI
Eternity AI
Eternity AI is building an HTLM-7B, a machine learning model that knows what the internet is and how to access it to generate responses. Humans don't make decisions based on 2-year-old data. For a model to think like a human, it needs to get access to real-time knowledge and everything about how humans behave. Members of our team have previously published white papers and articles on topics related to on-chain vulnerability coordination, GPT database retrieval, decentralized dispute resolution, etc. -
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Voyage AI
MongoDB
Voyage AI provides best-in-class embedding models and rerankers designed to supercharge search and retrieval for unstructured data. Its technology powers high-quality Retrieval-Augmented Generation (RAG) by improving how relevant context is retrieved before responses are generated. Voyage AI offers general-purpose, domain-specific, and company-specific models to support a wide range of use cases. The models are optimized for accuracy, low latency, and reduced costs through shorter vector dimensions. With long-context support of up to 32K tokens, Voyage AI enables deeper understanding of complex documents. The platform is modular and integrates easily with any vector database or large language model. Voyage AI is trusted by industry leaders to deliver reliable, factual AI outputs at scale. -
30
PaLM 2
Google
PaLM 2 is our next generation large language model that builds on Google’s legacy of breakthrough research in machine learning and responsible AI. It excels at advanced reasoning tasks, including code and math, classification and question answering, translation and multilingual proficiency, and natural language generation better than our previous state-of-the-art LLMs, including PaLM. It can accomplish these tasks because of the way it was built – bringing together compute-optimal scaling, an improved dataset mixture, and model architecture improvements. PaLM 2 is grounded in Google’s approach to building and deploying AI responsibly. It was evaluated rigorously for its potential harms and biases, capabilities and downstream uses in research and in-product applications. It’s being used in other state-of-the-art models, like Med-PaLM 2 and Sec-PaLM, and is powering generative AI features and tools at Google, like Bard and the PaLM API. -
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Mercury Coder
Inception Labs
Mercury, the latest innovation from Inception Labs, is the first commercial-scale diffusion large language model (dLLM), offering a 10x speed increase and significantly lower costs compared to traditional autoregressive models. Built for high-performance reasoning, coding, and structured text generation, Mercury processes over 1000 tokens per second on NVIDIA H100 GPUs, making it one of the fastest LLMs available. Unlike conventional models that generate text one token at a time, Mercury refines responses using a coarse-to-fine diffusion approach, improving accuracy and reducing hallucinations. With Mercury Coder, a specialized coding model, developers can experience cutting-edge AI-driven code generation with superior speed and efficiency.Starting Price: Free -
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Mistral Large 2
Mistral AI
Mistral AI has launched the Mistral Large 2, an advanced AI model designed to excel in code generation, multilingual capabilities, and complex reasoning tasks. The model features a 128k context window, supporting dozens of languages including English, French, Spanish, and Arabic, as well as over 80 programming languages. Mistral Large 2 is tailored for high-throughput single-node inference, making it ideal for large-context applications. Its improved performance on benchmarks like MMLU and its enhanced code generation and reasoning abilities ensure accuracy and efficiency. The model also incorporates better function calling and retrieval, supporting complex business applications.Starting Price: Free -
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Nano Banana Pro
Google
Nano Banana Pro is Google DeepMind’s advanced evolution of the original Nano Banana, designed to deliver studio-quality image generation with far greater accuracy, text rendering, and world knowledge. Built on Gemini 3 Pro, it brings improved reasoning capabilities that help users transform ideas into detailed visuals, diagrams, prototypes, and educational content. It produces highly legible multilingual text inside images, making it ideal for posters, logos, storyboards, and international designs. The model can also ground images in real-time information, pulling from Google Search to create infographics for recipes, weather data, or factual explanations. With powerful consistency controls, Nano Banana Pro can blend up to 14 images and maintain recognizable details across multiple people or elements. Its enhanced creative editing tools let users refine lighting, adjust focus, manipulate camera angles, and produce final outputs in up to 4K resolution. -
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Reka
Reka
Our enterprise-grade multimodal assistant carefully designed with privacy, security, and efficiency in mind. We train Yasa to read text, images, videos, and tabular data, with more modalities to come. Use it to generate ideas for creative tasks, get answers to basic questions, or derive insights from your internal data. Generate, train, compress, or deploy on-premise with a few simple commands. Use our proprietary algorithms to personalize our model to your data and use cases. We design proprietary algorithms involving retrieval, fine-tuning, self-supervised instruction tuning, and reinforcement learning to tune our model on your datasets. -
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Seed1.8
ByteDance
Seed1.8 is ByteDance’s latest generalized agentic AI model designed to bridge understanding and real-world action by combining multimodal perception, agent-like task execution, and wide-ranging reasoning capabilities into a single foundation model that goes beyond simple language generation. It supports multimodal inputs, including text, images, and video, processes very large context windows (hundreds of thousands of tokens at once), and is optimized to handle complex workflows in real environments, such as information retrieval, code generation, GUI interaction, and multi-step decision logic, with efficient, accurate responses suitable for real-world applications. Seed1.8 unifies skills such as search, code understanding, visual context interpretation, and autonomous reasoning so developers and AI systems can build interactive agents and next-generation workflows capable of synthesizing evidence, following instructions deeply, and acting on tasks like automation. -
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Palmyra LLM
Writer
Palmyra is a suite of Large Language Models (LLMs) engineered for precise, dependable performance in enterprise applications. These models excel in tasks such as question-answering, image analysis, and support for over 30 languages, with fine-tuning available for industries like healthcare and finance. Notably, Palmyra models have achieved top rankings in benchmarks like Stanford HELM and PubMedQA, and Palmyra-Fin is the first model to pass the CFA Level III exam. Writer ensures data privacy by not using client data to train or modify their models, adopting a zero data retention policy. The Palmyra family includes specialized models such as Palmyra X 004, featuring tool-calling capabilities; Palmyra Med, tailored for healthcare; Palmyra Fin, designed for finance; and Palmyra Vision, which offers advanced image and video processing. These models are available through Writer's full-stack generative AI platform, which integrates graph-based Retrieval Augmented Generation (RAG).Starting Price: $18 per month -
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GLM-4.6V
Zhipu AI
GLM-4.6V is a state-of-the-art open source multimodal vision-language model from the Z.ai (GLM-V) family designed for reasoning, perception, and action. It ships in two variants: a full-scale version (106B parameters) for cloud or high-performance clusters, and a lightweight “Flash” variant (9B) optimized for local deployment or low-latency use. GLM-4.6V supports a native context window of up to 128K tokens during training, enabling it to process very long documents or multimodal inputs. Crucially, it integrates native Function Calling, meaning the model can take images, screenshots, documents, or other visual media as input directly (without manual text conversion), reason about them, and trigger tool calls, bridging “visual perception” with “executable action.” This enables a wide spectrum of capabilities; interleaved image-and-text content generation (for example, combining document understanding with text summarization or generation of image-annotated responses).Starting Price: Free -
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Gemini 2.5 Flash-Lite
Google
Gemini 2.5 is Google DeepMind’s latest generation AI model family, designed to deliver advanced reasoning and native multimodality with a long context window. It improves performance and accuracy by reasoning through its thoughts before responding. The model offers different versions tailored for complex coding tasks, fast everyday performance, and cost-efficient high-volume workloads. Gemini 2.5 supports multiple data types including text, images, video, audio, and PDFs, enabling versatile AI applications. It features adaptive thinking budgets and fine-grained control for developers to balance cost and output quality. Available via Google AI Studio and Gemini API, Gemini 2.5 powers next-generation AI experiences. -
39
Azure OpenAI Service
Microsoft
Apply advanced coding and language models to a variety of use cases. Leverage large-scale, generative AI models with deep understandings of language and code to enable new reasoning and comprehension capabilities for building cutting-edge applications. Apply these coding and language models to a variety of use cases, such as writing assistance, code generation, and reasoning over data. Detect and mitigate harmful use with built-in responsible AI and access enterprise-grade Azure security. Gain access to generative models that have been pretrained with trillions of words. Apply them to new scenarios including language, code, reasoning, inferencing, and comprehension. Customize generative models with labeled data for your specific scenario using a simple REST API. Fine-tune your model's hyperparameters to increase accuracy of outputs. Use the few-shot learning capability to provide the API with examples and achieve more relevant results.Starting Price: $0.0004 per 1000 tokens -
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Gemini 2.0
Google
Gemini 2.0 is an advanced AI-powered model developed by Google, designed to offer groundbreaking capabilities in natural language understanding, reasoning, and multimodal interactions. Building on the success of its predecessor, Gemini 2.0 integrates large language processing with enhanced problem-solving and decision-making abilities, enabling it to interpret and generate human-like responses with greater accuracy and nuance. Unlike traditional AI models, Gemini 2.0 is trained to handle multiple data types simultaneously, including text, images, and code, making it a versatile tool for research, business, education, and creative industries. Its core improvements include better contextual understanding, reduced bias, and a more efficient architecture that ensures faster, more reliable outputs. Gemini 2.0 is positioned as a major step forward in the evolution of AI, pushing the boundaries of human-computer interaction.Starting Price: Free -
41
Command R
Cohere AI
Command’s model outputs come with clear citations that mitigate the risk of hallucinations and enable the surfacing of additional context from the source materials. Command can write product descriptions, help draft emails, suggest example press releases, and much more. Ask Command multiple questions about a document to assign a category to the document, extract a piece of information, or answer a general question about the document. Where answering a few questions about a document can save you a few minutes, doing it for thousands of documents can save a company years. This family of scalable models balances high efficiency with strong accuracy to enable enterprises to move from proof of concept into production-grade AI. -
42
eRAG
GigaSpaces
GigaSpaces eRAG (Enterprise Retrieval Augmented Generation) is an AI-powered platform designed to enhance enterprise decision-making by enabling natural language interactions with structured data sources such as relational databases. Unlike traditional generative AI models that may produce inaccurate or "hallucinated" responses when dealing with structured data, eRAG employs deep semantic reasoning to accurately translate user queries into SQL, retrieve relevant data, and generate precise, context-aware answers. This approach ensures that responses are grounded in real-time, authoritative data, mitigating the risks associated with unverified AI outputs. eRAG seamlessly integrates with various data sources, allowing organizations to unlock the full potential of their existing data infrastructure. eRAG offers built-in governance features that monitor interactions to ensure compliance with regulations. -
43
Amazon Nova 2 Lite
Amazon
Nova 2 Lite is a lightweight, high-speed reasoning model designed to handle everyday AI workloads across text, images, and video. It can generate clear, context-aware responses and lets users fine-tune how much internal reasoning the model performs before producing an answer. This adjustable “thinking depth” gives teams the flexibility to choose faster replies or more detailed problem-solving depending on the task. It stands out for customer service bots, automated document handling, and general business workflow support. Nova 2 Lite delivers strong performance across standard evaluation tests. It performs on par with or better than comparable compact models in most benchmark categories, demonstrating reliable comprehension and response quality. Its strengths include interpreting complex documents, pulling accurate insights from video content, generating usable code, and delivering grounded answers based on provided information. -
44
ByteDance Seed
ByteDance
Seed Diffusion Preview is a large-scale, code-focused language model that uses discrete-state diffusion to generate code non-sequentially, achieving dramatically faster inference without sacrificing quality by decoupling generation from the token-by-token bottleneck of autoregressive models. It combines a two-stage curriculum, mask-based corruption followed by edit-based augmentation, to robustly train a standard dense Transformer, striking a balance between speed and accuracy and avoiding shortcuts like carry-over unmasking to preserve principled density estimation. The model delivers an inference speed of 2,146 tokens/sec on H20 GPUs, outperforming contemporary diffusion baselines while matching or exceeding their accuracy on standard code benchmarks, including editing tasks, thereby establishing a new speed-quality Pareto frontier and demonstrating discrete diffusion’s practical viability for real-world code generation.Starting Price: Free -
45
GPT-4.5
OpenAI
GPT-4.5 is a powerful AI model that improves upon its predecessor by scaling unsupervised learning, enhancing reasoning abilities, and offering improved collaboration capabilities. Designed to better understand human intent and collaborate in more natural, intuitive ways, GPT-4.5 delivers higher accuracy and lower hallucination rates across a broad range of topics. Its advanced capabilities enable it to generate creative and insightful content, solve complex problems, and assist with tasks in writing, design, and even space exploration. With improved AI-human interactions, GPT-4.5 is optimized for practical applications, making it more accessible and reliable for businesses and developers.Starting Price: $75.00 / 1M tokens -
46
OpenAI o3-pro
OpenAI
OpenAI’s o3-pro is a high-performance reasoning model designed for tasks that require deep analysis and precision. It is available exclusively to ChatGPT Pro and Team subscribers, succeeding the earlier o1-pro model. The model excels in complex fields like mathematics, science, and coding by employing detailed step-by-step reasoning. It integrates advanced tools such as real-time web search, file analysis, Python execution, and visual input processing. While powerful, o3-pro has slower response times and lacks support for features like image generation and temporary chats. Despite these trade-offs, o3-pro demonstrates superior clarity, accuracy, and adherence to instructions compared to its predecessor.Starting Price: $20 per 1 million tokens -
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Sightify AI Agents
Sightify
Sightify | AI Agents is an LLM AI SaaS intended to automate SME workflows while ensuring data sovereignty. Some features include: Data-Sovereign Agents: Fine-tuned w/ RAG on open-source LLMs for specific business process optimization No AI Hallucinations: Source, page, and section citations for database-enforced tokens Multimodal: PDF, Excel, Word, TXT, PNG/JPEG, etc. CRM/ERP System Integration: API documentation, MCP compliant, R&D integration/support Updatable LLMs: Constant New Version Implementations (Qwen 70B, Gemma 27B) Our current AI Agents are: Knowledge Assistant: For client relationship management, HR/company regulations search, etc Contract Finalizer: Finalize legal contracts that are sent to or received from clients/partners Report Generator: Instant monthly/annual sales/marketing/budget reports Market Researcher: Research and analyze enterprise competitors, products, pricing, etc Meeting Notetaker: Employ LLM AI on audio-generated meeting notesStarting Price: $300/year/agent -
48
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 -
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ERNIE 4.5 Turbo
Baidu
ERNIE 4.5 Turbo, unveiled by Baidu at the 2025 Baidu Create conference, is a cutting-edge AI model designed to handle a variety of data inputs, including text, images, audio, and video. It offers powerful multimodal processing capabilities that enable it to perform complex tasks across industries such as customer support automation, content creation, and data analysis. With enhanced reasoning abilities and reduced hallucinations, ERNIE 4.5 Turbo ensures that businesses can achieve higher accuracy and reliability in AI-driven processes. Additionally, this model is priced at just 1% of GPT-4.5’s cost, making it a highly cost-effective alternative for enterprises looking for top-tier AI performance. -
50
Ferret
Apple
An End-to-End MLLM that Accept Any-Form Referring and Ground Anything in Response. Ferret Model - Hybrid Region Representation + Spatial-aware Visual Sampler enable fine-grained and open-vocabulary referring and grounding in MLLM. GRIT Dataset (~1.1M) - A Large-scale, Hierarchical, Robust ground-and-refer instruction tuning dataset. Ferret-Bench - A multimodal evaluation benchmark that jointly requires Referring/Grounding, Semantics, Knowledge, and Reasoning.Starting Price: Free
