Alternatives to Moshi

Gemini-Exp-1206 is an advanced AI model now available for early access to Gemini Advanced subscribers. Designed to excel in areas like programming, complex problem-solving, reasoning, and following intricate instructions, it pushes the boundaries of AI capabilities. This preview version offers users a glimpse into its powerful features, though some functionalities may still be refined. While real-time data access is not yet included, Gemini-Exp-1206 can be easily accessed via the Gemini model selection on both desktop and mobile platforms.

StableLM: Stability AI language models StableLM builds upon our experience with open-sourcing previous language models in collaboration with EleutherAI. This nonprofit research hub. These models include GPTJ, GPTNeoX and the Pythia Suite, which were all trained on The Pile dataset. Cerebras GPT and Dolly-2 are two recent open-source models that continue to build upon these efforts. StableLM was trained on a new dataset that is three times bigger than The Pile and contains 1.5 trillion tokens. We will provide more details about the dataset at a later date. StableLM's richness allows it to perform well in conversational and coding challenges, despite the small size of its dataset (3-7 billion parameters, compared to GPT-3's 175 billion). The development of Stable LM 3B broadens the range of applications that are viable on the edge or on home PCs. This means that individuals and companies can now develop cutting-edge technologies with strong conversational capabilities – like creative writing assistance – while keeping costs low and performance high.

Eternity AI builds an HTLM-7B machine learning model, which knows what the Internet is and how it can be accessed to generate responses. Humans do not make decisions based upon data that is two years old. To think like a person, a model must have access to current knowledge and all information about human behavior. Our team has published articles and white papers on topics such as on-chain vulnerability coordination.

Claude 3.7 Sonnet from Anthropic is an advanced AI model that offers a unique blend of fast responses and in-depth reflective reasoning. This hybrid approach allows users to toggle between speed and thoughtfulness, enabling the model to engage in complex problem-solving with precision. With its self-reflection mechanism, Claude 3.7 Sonnet is well-suited for tasks requiring deeper understanding and critical thinking, making it particularly valuable in fields like coding, research, and analysis. As an adaptable and powerful AI tool, it provides robust support for businesses and professionals needing sophisticated reasoning and reliable insights.

The o3-mini-high model from OpenAI represents a significant leap in AI reasoning capabilities, building on the foundation laid by its predecessor, the o1 series. This model is finely tuned for tasks requiring deep reasoning, particularly in coding, mathematics, and complex problem-solving scenarios. It introduces an adaptive thinking time feature, allowing users to tailor the AI's processing efforts to match the complexity of the task, with options for low, medium, and high reasoning modes. o3-mini-high has been reported to outperform o1 models on various benchmarks, including Codeforces, where it achieved a notable 200 Elo points higher than o1. It offers a cost-effective solution with performance that rivals higher-end models, maintaining the speed and accuracy needed for both casual and professional use. This model is part of the o3 family, which is designed to push the boundaries of AI's problem-solving abilities while ensuring that these advanced capabilities are accessible to a broader audience, including through a free tier and enhanced usage limits for Plus subscribers.

OpenAI o1 mini is a new and cost-effective AI designed to enhance reasoning, especially in STEM fields such as mathematics and coding. It is part of the o1 Series, which focuses on solving problems by spending more "thinking" time through solutions. The o1 mini is 80% cheaper and smaller than its sibling. It performs well in coding and mathematical reasoning tasks.

Grok 3 DeepSearch is a revolutionary AI model that enhances reasoning by incorporating deep search mechanisms, enabling the AI to delve into complex problems and explore various possibilities. As an AI agent, it can engage in extended reasoning, continuously testing and refining solutions, making it perfect for high-stakes tasks that require detailed problem-solving and critical thinking. Whether solving intricate math problems, generating code, or conducting thorough academic research, Grok 3 DeepSearch provides an elevated approach by leveraging real-time exploration and error correction. This model represents a significant leap forward in AI's ability to handle nuanced challenges in fields ranging from mathematics to software development and beyond.

OpenAI o1 is a new series AI models developed by OpenAI that focuses on enhanced reasoning abilities. These models, such as o1 preview and o1 mini, are trained with a novel reinforcement-learning approach that allows them to spend more time "thinking through" problems before presenting answers. This allows o1 excel in complex problem solving tasks in areas such as coding, mathematics, or science, outperforming other models like GPT-4o. The o1 series is designed to tackle problems that require deeper thinking processes. This marks a significant step in AI systems that can think more like humans.

AI assistants that can be customized, global hotkeys and in-line AI will help you to double your productivity. Elegant features that seamlessly integrate into your mobile workflows. Conversations, preferences and model usage remain on your computer - secure, exportable and can be deleted any time.

Sparrow is a research model that serves as a proof of concept. It was created with the goal to train dialogue agents to be more helpful and correct. Sparrow helps us understand how to train agents to be more helpful and safer, and ultimately to help create safer and more useful artificial intelligence (AGI). Sparrow is currently not available for public use. Because it is difficult to determine what makes a conversation successful, training conversational AI can be a challenging problem. We use reinforcement learning (RL) to address this problem. This is a form that uses people's feedback and the preference feedback of study participants to train a model about how useful an answer is. We show participants multiple models of the same question, and ask them which one they prefer.

Experience JinaChat - a LLM service designed for professionals. JinaChat is a multimodal chat service that goes beyond text and includes images. Enjoy our free short interactions below 100 tokens. Our API allows developers to build complex applications by leveraging long conversation histories. JinaChat is the future of LLM, with multimodal conversations that are long-memory and affordable. Modern LLM applications are often based on long prompts or large memory, which can lead to high costs if the same prompts are sent repeatedly to the server. JinaChat API solves this issue by allowing you to carry forward previous conversations, without having to resend the entire prompt. This is a great way to save both time and money when developing complex applications such as AutoGPT.

Gemini models are a family of light-open, state-of-the art models that was created using the same research and technology as Gemini models. These models include comprehensive security measures, and help to ensure responsible and reliable AI through selected data sets. Gemma models have exceptional comparative results, even surpassing some larger open models, in their 2B and 7B sizes. Keras 3.0 offers seamless compatibility with JAX TensorFlow PyTorch and JAX. Gemma 2 has been redesigned to deliver unmatched performance and efficiency. It is optimized for inference on a variety of hardware. The Gemma models are available in a variety of models that can be customized to meet your specific needs. The Gemma models consist of large text-to text lightweight language models that have a decoder and are trained on a large set of text, code, or mathematical content.

We've developed a model, called ChatGPT, that interacts in a conversational manner. ChatGPT can use the dialogue format to answer questions, admit mistakes, challenge incorrect premises and reject inappropriate requests. ChatGPT is the sibling model of InstructGPT. InstructGPT is trained to follow a prompt, and then provide a detailed answer. ChatGPT Plus, a subscription plan to ChatGPT, a conversational AI. ChatGPT Plus is $20/month and subscribers receive a variety of benefits. - ChatGPT is available to all users, even at peak times - Faster response time Access to GPT-4 ChatGPT plugins Chat with Web-browsingGPT - Priority access for new features and improvements ChatGPT Plus will be available to all customers in the United States. We will begin inviting people on our waitlist within the next few weeks. We plan to extend access and support to other countries and regions in the near future.

OpenAI o3 Mini is a lightweight version o3 AI model that offers powerful reasoning capabilities, but in a more accessible and efficient package. O3-mini is designed to break complex instructions down into smaller, more manageable steps. It excels at coding tasks, competitive programing, and problem solving in mathematics and sciences. This compact model offers the same high level of precision and logic that its larger counterpart, but with reduced computation requirements. It is ideal for use in resource constrained environments. The o3 mini's deliberative alignment ensures ethical, safe and context-aware decisions. This makes it a versatile tool that can be used by developers, researchers and businesses looking for a balance between performance, efficiency and safety.

Marco-o1 is an advanced AI model that is designed for high-performance problem solving and natural language processing. It is designed to deliver precise, contextually rich answers by combining deep language understanding with a streamlined architectural design for speed and efficiency. Marco-o1 is a versatile AI system that excels at a wide range of tasks, including conversational AI. It also excels at content creation, technical assistance, and decision-making. It adapts seamlessly to the needs of diverse users. Marco-o1 is a cutting edge solution for individuals and organisations seeking intelligent, adaptive and scalable AI tools. It focuses on intuitive interactions, reliability and ethical AI principles. MCTS allows for the exploration of multiple reasoning pathways using confidence scores derived by softmax-applied logging probabilities of the top k alternative tokens. This guides the model to optimal solution.

GPT-4o (o for "omni") is an important step towards a more natural interaction between humans and computers. It accepts any combination as input, including text, audio and image, and can generate any combination of outputs, including text, audio and image. It can respond to audio in as little as 228 milliseconds with an average of 325 milliseconds. This is similar to the human response time in a conversation (opens in new window). It is as fast and cheaper than GPT-4 Turbo on text in English or code. However, it has a significant improvement in text in non-English language. GPT-4o performs better than existing models at audio and vision understanding.

Mistral Saba, a 24-billion parameter model, is trained on carefully curated datasets gathered from the Middle East and South Asia. The model is more accurate and relevant than models five times larger, while being faster and cheaper. It can also be used as a solid base for training highly specific regional adaptations. Mistral Saba can be installed locally in the security premises of customers using an API. The model is lightweight, can be deployed with a single GPU system and responds at speeds exceeding 150 tokens per seconds. Mistral Saba is a powerful tool for South Indian languages, such as Tamil, and Arabic. It also supports many Indian languages. This capability increases its versatility for multi-regional use.

A small model with superior textual Intelligence and multimodal reasoning. GPT-4o Mini's low cost and low latency enable a wide range of tasks, including applications that chain or paralelize multiple model calls (e.g. calling multiple APIs), send a large amount of context to the models (e.g. full code base or history of conversations), or interact with clients through real-time, fast text responses (e.g. customer support chatbots). GPT-4o Mini supports text and vision today in the API. In the future, it will support text, image and video inputs and outputs. The model supports up to 16K outputs tokens per request and has knowledge until October 2023. It has a context of 128K tokens. The improved tokenizer shared by GPT-4o makes it easier to handle non-English text.

As a tribute for Archimedes' 2311th birthday, which we celebrate this year, we release our first Mathstral 7B model, designed specifically for math reasoning and scientific discoveries. The model comes with a 32k context-based window that is published under the Apache 2.0 License. Mathstral is a tool we're donating to the science community in order to help solve complex mathematical problems that require multi-step logical reasoning. The Mathstral release was part of a larger effort to support academic project, and it was produced as part of our collaboration with Project Numina. Mathstral, like Isaac Newton at his time, stands on Mistral 7B's shoulders and specializes in STEM. It has the highest level of reasoning in its size category, based on industry-standard benchmarks. It achieves 56.6% in MATH and 63.47% in MMLU. The following table shows the MMLU performance differences between Mathstral and Mistral 7B.

A marketplace of LLMs created by developers on technical topics, and managed by a community. Outperforms standalone AI models. Lunes, which are constantly updated on the latest technical knowledge sources, such as Github repositories and documentation, can reduce hallucinations when it comes to technical queries. You can get references back, just like with Perplexity. Use hundreds of Lunes created by other users, ranging from Lunes that are trained on open-source software to curated collections based on tech blog posts. Get exposure by creating one using a variety sources, such as your own projects. Our API can be hot-swapped with OpenAI's. Integrate with Cursor and Continue, as well as other tools that support OpenAI compatible models. You can continue your conversation from your IDE on Lune Web anytime. Get paid for each approved comment you make directly in the chat. Create a public Lune, share it and get paid based on its popularity.

The expansion of large language model has led to significant advancements in natural language processing, understanding and generation. This study introduces a new system that uses Ascend 910 AI processing units and the MindSpore framework in order to train a language with over one trillion parameters, 1.085T specifically, called PanGu-Sigma. This model, which builds on the foundation laid down by PanGu-alpha transforms the traditional dense Transformer model into a sparse model using a concept called Random Routed Experts. The model was trained efficiently on a dataset consisting of 329 billion tokens, using a technique known as Expert Computation and Storage Separation. This led to a 6.3 fold increase in training performance via heterogeneous computer. The experiments show that PanGu-Sigma is a new standard for zero-shot learning in various downstream Chinese NLP tasks.

Gemini 2.0 Pro is Google DeepMind’s cutting-edge AI model, built for advanced reasoning, coding, and problem-solving tasks. With a massive two-million-token context window, it can process extensive datasets with remarkable efficiency. One of its key strengths is its ability to integrate with external tools, such as Google Search and code execution environments, enabling more precise and informed responses. Currently in an experimental phase, Gemini 2.0 Pro pushes the boundaries of AI capabilities, making it a valuable asset for developers and researchers tackling complex challenges.

PanGu-a was developed under MindSpore, and trained on 2048 Ascend AI processors. The MindSpore Auto-parallel parallelism strategy was implemented to scale the training task efficiently to 2048 processors. This includes data parallelism as well as op-level parallelism. We pretrain PanGu-a with 1.1TB of high-quality Chinese data collected from a variety of domains in order to enhance its generalization ability. We test the generation abilities of PanGua in different scenarios, including text summarizations, question answering, dialog generation, etc. We also investigate the effects of model scaling on the few shot performances across a wide range of Chinese NLP task. The experimental results show that PanGu-a is superior in performing different tasks with zero-shot or few-shot settings.

Phi-2 is a 2.7-billion-parameter language-model that shows outstanding reasoning and language-understanding capabilities. It represents the state-of-the art performance among language-base models with less than thirteen billion parameters. Phi-2 can match or even outperform models 25x larger on complex benchmarks, thanks to innovations in model scaling. Phi-2's compact size makes it an ideal playground for researchers. It can be used for exploring mechanistic interpretationability, safety improvements or fine-tuning experiments on a variety tasks. We have included Phi-2 in the Azure AI Studio catalog to encourage research and development of language models.

Gemini 2.0 Flash Thinking is a cutting-edge AI advancement from Google DeepMind, designed to enhance problem-solving by making its reasoning process more transparent. Unlike traditional models that provide only final outputs, Gemini 2.0 explicitly showcases its thought process, allowing users to follow its logic step by step. This approach improves accuracy, reduces errors, and builds trust by making AI-driven decisions more explainable. By breaking down complex problems into clear, logical steps, it becomes a powerful tool for research, analysis, and decision-making in various fields. Whether applied in science, engineering, or creative problem-solving, Gemini 2.0 Flash Thinking represents a major leap forward in AI’s ability to think critically and provide deeper insights.

Grok 3 Think represents a major leap forward in AI development, focusing on advanced reasoning capabilities that allow the model to tackle complex problems over extended periods. Through reinforcement learning, it can iteratively refine its solutions by reconsidering past steps, exploring new possibilities, and improving its approach. Trained on a massive scale, Grok 3 Think excels in areas like math, coding, and general knowledge, achieving remarkable results in high-level competitions like the American Invitational Mathematics Examination. It also stands out for its transparency, enabling users to examine the thought process behind its answers, setting a new standard for AI problem-solving and insight.

Hume AI introduced Octave, a text-to-speech engine that uses large language models to understand and interpret context. Unlike traditional TTS systems that merely read texts, Octave delivers lines with nuanced emotion based on content. Users can create different AI voices using descriptive prompts such as "a medieval peasant who is sarcastic." This allows for customized voice generation that aligns to specific character traits or situations. Octave also allows users to customize the voice's emotional delivery and style by using natural language commands. For example, "sound more enthusiastic", "whisper fearfully", or "sound more excited" can be used to fine-tune output.

Hunyuan Turbo S by Tencent is an advanced AI model that integrates high-speed, real-time responses with deep analytical thinking. By improving the speed of text generation and minimizing delays, it provides faster and more intuitive answers, particularly in knowledge, math, and creative content. With its Hybrid-Mamba-Transformer architecture, Turbo S reduces computation costs, making it more efficient and scalable than traditional models. This hybrid approach offers the best of both fast thinking and slow, reasoned analysis, empowering businesses to deploy AI applications across a wide range of use cases, from simple queries to complex problem-solving.

GPT-4, a large multimodal (accepting text and image inputs) model that can solve complex problems with greater accuracy thanks to its advanced reasoning abilities and broader general knowledge than any of our other models. GPT-4 can be found in the OpenAI API for paying customers. GPT-4, like gpt 3.5-turbo is optimized for chat, but also works well with traditional completion tasks using the Chat Completions API. Our GPT guide will teach you how to use GPT-4. GPT-4 is a newer GPT-4 model that features improved instruction following, JSON Mode, reproducible outputs and parallel function calls. Returns up to 4,096 tokens. This preview model has not yet been adapted for production traffic.

AI will become more sophisticated as it advances, and will solve increasingly complex problems. These capabilities require a lot more computing power. ChatGPT Pro, a $200/month plan, gives you access to OpenAI's best models and tools. This plan gives you unlimited access to OpenAI o1, our smartest model. It also includes o1-mini and Advanced Voice. It also includes the o1 pro version, a version that uses more computation to think harder and give even better answers to difficult problems. We expect to add to this plan in the future more powerful and compute-intensive productivity features. ChatGPT Pro gives you access to our most intelligent model, which thinks longer and more thoroughly for the most reliable answers. According to external expert testers' evaluations, the o1 pro mode consistently produces more accurate and comprehensive answers, especially in areas such as data science, programming and case law analysis.

Instruction-following models such as GPT-3.5 (text-DaVinci-003), ChatGPT, Claude, and Bing Chat have become increasingly powerful. These models are now used by many users, and some even for work. However, despite their widespread deployment, instruction-following models still have many deficiencies: they can generate false information, propagate social stereotypes, and produce toxic language. It is vital that the academic community engages in order to make maximum progress towards addressing these pressing issues. Unfortunately, doing research on instruction-following models in academia has been difficult, as there is no easily accessible model that comes close in capabilities to closed-source models such as OpenAI's text-DaVinci-003. We are releasing our findings about an instruction-following language model, dubbed Alpaca, which is fine-tuned from Meta's LLaMA 7B model.

Grok-2 is the latest AI technology. It is a marvel in modern engineering that aims to push the limits of what artificial intelligence has the potential to achieve. Grok-2, the latest iteration of AI technology, is a marvel of modern engineering. It's designed to push the boundaries of what artificial intelligence can achieve. Grok-2, with its expanded knowledge base, which reaches back to the recent past and offers a unique perspective on humanity as well as humor, is a truly engaging AI. It can answer nearly any question in the most helpful way possible, and often provides solutions that are both innovative as well as outside of the box. Grok-2's design is based on truthfulness and avoids the pitfalls associated with woke culture. It strives to provide information and entertainment that are reliable in a complex world.

Ernie Bot (Wenxin Yiyan), a Baidu conversational AI chatbot, is a new chatbot that can answer any type of question a user may have.

OpenAI o1 pro is an enhanced version of OpenAI’s o1 model. It was designed to handle more complex and demanding tasks, with greater reliability. It has significant performance improvements compared to its predecessor, the OpenAI o1 Preview, with a noticeable 34% reduction in errors and the ability think 50% faster. This model excels at math, physics and coding where it can provide accurate and detailed solutions. The o1 Pro mode is also capable of processing multimodal inputs including text and images. It is especially adept at reasoning tasks requiring deep thought and problem solving. ChatGPT Pro subscriptions offer unlimited usage as well as enhanced capabilities to users who need advanced AI assistance.

Yi-Lightning is the latest large language model developed by 01.AI, under the leadership Kai-Fu Lee. It focuses on high performance, cost-efficiency, and a wide range of languages. It has a maximum context of 16K tokens, and costs $0.14 per million tokens both for input and output. This makes it very competitive. Yi-Lightning uses an enhanced Mixture-of-Experts architecture that incorporates fine-grained expert segments and advanced routing strategies to improve its efficiency. This model has excelled across a variety of domains. It achieved top rankings in categories such as Chinese, math, coding and hard prompts in the chatbot arena where it secured the sixth position overall and ninth in style control. Its development included pre-training, supervised tuning, and reinforcement learning based on human feedback. This ensured both performance and safety with optimizations for memory usage and inference speeds.

PanGu Chat, an AI chatbot created by Huawei, is a powerful AI. PanGu Chat can answer questions and converse with you like ChatGPT.

It's as simple as changing one line in code to switch. Feature parity with industry-standard APIs ensures that your product runs faster and works the same way. GooseAI is a fully managed NLP as-a-Service delivered via API. In this respect, it is comparable to OpenAI. It is compatible with OpenAI’s completion API. Our state-of the-art selection GPT-based language models, uncompromising speed, and flexible alternative to your current provider will give you a jumpstart in your next project. We are proud to be able offer prices that are up to 70% lower than other providers and still deliver the same or better performance. Geese are integral to the ecosystem, just as the Mitochondria powerhouses cells. We were inspired by their beauty and elegance to fly high, just like geese.

Doubao, an intelligent language model created by ByteDance, is a powerful tool for learning new languages. It has provided users with useful answers and insights on a wide range topics. Doubao is able to handle complex questions and provide detailed explanations. It can also engage in meaningful conversation. Its advanced language understanding and generation abilities continue to help people solve problems, explore new ideas, and seek knowledge. Doubao can be used for academic inquiries, inspiration for creative projects, or just a simple conversation.

Language Understanding (LUIS), a machine learning-based service that builds natural language into apps and bots. Rapidly create custom models that are enterprise-ready and can be continuously improved. Natural language can be added to your apps. LUIS is a language model that interprets conversations to find valuable information. It extracts information from sentences (entities) and interprets user intentions (goals). LUIS is seamlessly integrated with the Azure Bot Service, making creating sophisticated bots easy. You can quickly create and deploy a solution faster by combining powerful developer tools with pre-built apps and entity dictionary, such as Music, Calendar, and Devices. The collective knowledge of the internet is used to create dictionaries. This allows your model to identify valuable information from user conversations. Active learning is used for continuous improvement of the quality of the models.

LFM-40B provides a new balance in model size and output. It uses 12B parameters that are activated at the time of use. Its performance is comparable with models larger than it, and its MoE architecture allows for higher throughput on more cost-effective equipment.

Command R+, Cohere's latest large language model, is optimized for conversational interactions and tasks with a long context. It is designed to be extremely performant and enable companies to move from proof-of-concept into production. We recommend Command R+ when working with workflows that rely on complex RAG functionality or multi-step tool usage (agents). Command R is better suited for retrieval augmented creation (RAG) tasks and single-step tool usage, or applications where cost is a key consideration.

Solar's Chat API allows you to create a simple agent that can have a conversation. Function Calling, the method of connecting LLM with external tools, is now supported. The embedding vectors are useful for retrieval and classification. Context-aware English to Korean translation that uses previous dialogues for unmatched coherence in your conversations. Verifies that the LLM's generated answers are appropriate based on the question asked by the user and the search results. A healthcare LLM is being developed to automate patient communications, personalize treatment plans and aid in clinical decision-support. It will also support medical transcription. The goal is to make it easy for business owners and companies, to deploy generative AI bots on mobile apps and websites. This will provide human-like customer support.

Grok-3 Mini, developed by xAI, is a compact yet powerful AI designed to provide quick and insightful responses to a wide array of queries. It embodies the same curious and outside perspective on humanity as its larger counterparts but in a more streamlined form. Despite its smaller size, Grok-3 Mini retains core functionalities, offering maximum helpfulness in understanding both simple and complex topics. It's tailored for efficiency, making it ideal for users seeking fast, reliable answers without the need for extensive computational resources. This mini version is perfect for on-the-go queries, providing a balance between performance and accessibility.

Chinchilla has a large language. Chinchilla has the same compute budget of Gopher, but 70B more parameters and 4x as much data. Chinchilla consistently and significantly outperforms Gopher 280B, GPT-3 175B, Jurassic-1 178B, and Megatron-Turing (530B) in a wide range of downstream evaluation tasks. Chinchilla also uses less compute to perform fine-tuning, inference and other tasks. This makes it easier for downstream users to use. Chinchilla reaches a high-level average accuracy of 67.5% for the MMLU benchmark. This is a greater than 7% improvement compared to Gopher.

The TinyLlama Project aims to pretrain an 1.1B Llama on 3 trillion tokens. We can achieve this in "just" 90 day using 16 A100-40G graphics cards with some optimization. We used the exact same architecture and tokenizers as Llama 2 TinyLlama is compatible with many open-source Llama projects. TinyLlama has only 1.1B of parameters. This compactness allows TinyLlama to be used for a variety of applications that require a small computation and memory footprint.

With T5, we propose re-framing all NLP into a unified format where the input and the output are always text strings. This is in contrast to BERT models which can only output a class label, or a span from the input. Our text-totext framework allows us use the same model and loss function on any NLP task. This includes machine translation, document summary, question answering and classification tasks. We can also apply T5 to regression by training it to predict a string representation of a numeric value instead of the actual number.

Gemini is Google’s advanced AI chatbot that engages in natural language conversation to boost creativity and productivity. Gemini is accessible via web and mobile apps. It integrates seamlessly with Google services such as Docs, Drive and Gmail. Users can draft content, summarize data, and manage tasks. Its multimodal capabilities enable it to process and produce diverse data types such as text images and audio. This provides comprehensive assistance in different contexts. Gemini is a constantly learning model that adapts to the user's interactions and offers personalized and context-aware answers to meet a variety of user needs.

Opus, our intelligent model, is superior to its peers in most of the common benchmarks for AI systems. These include undergraduate level expert knowledge, graduate level expert reasoning, basic mathematics, and more. It displays near-human levels in terms of comprehension and fluency when tackling complex tasks. This is at the forefront of general intelligence. All Claude 3 models have increased capabilities for analysis and forecasting. They also offer nuanced content generation, code generation and the ability to converse in non-English language such as Spanish, Japanese and French.

Gemma is the family of lightweight open models that are built using the same research and technology as the Gemini models. Gemma was developed by Google DeepMind, along with other teams within Google. The name is derived from the Latin gemma meaning "precious stones". We're also releasing new tools to encourage developer innovation, encourage collaboration, and guide responsible use of Gemma model. Gemma models are based on the same infrastructure and technical components as Gemini, Google's largest and most powerful AI model. Gemma 2B, 7B and other open models can achieve the best performance possible for their size. Gemma models can run directly on a desktop or laptop computer for developers. Gemma is able to surpass much larger models in key benchmarks, while adhering our rigorous standards of safe and responsible outputs.

Vicuna-13B, an open-source chatbot, is trained by fine-tuning LLaMA using user-shared conversations from ShareGPT. Vicuna-13B's preliminary evaluation using GPT-4, as a judge, shows that it achieves a quality of more than 90%* for OpenAI ChatGPT or Google Bard and outperforms other models such as LLaMA or Stanford Alpaca. Vicuna-13B costs around $300 to train. The online demo and the code, along with weights, are available to non-commercial users.