Alternatives to Claude 3.5 Sonnet

Claude 3 Haiku has the fastest and most affordable model of its intelligence class. Haiku's powerful performance and state-of-the art vision capabilities make it a versatile solution that can be used for a variety of enterprise applications. The model is available in the Claude API alongside Sonnet and Opus for our Claude Pro customers.

Open source AI model that you can fine-tune and distill anywhere. Our latest instruction-tuned models are available in 8B 70B and 405B version. Our open ecosystem allows you to build faster using a variety of product offerings that are differentiated and support your use cases. Choose between real-time or batch inference. Download model weights for further cost-per-token optimization. Adapt to your application, improve using synthetic data, and deploy on-prem. Use Llama components and extend the Llama model using RAG and zero shot tools to build agentic behavior. Use 405B high-quality data to improve specialized model for specific use cases.

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.

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.

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.

Our new flagship model, the Small Language Model (SLM), has all the power and performance that you would expect from a leading LLM. Excels at generalized tasks, instruction-following, and human preferences. The best 70B model available. SuperNova is a generalized task-based AI that can be used for any generalized task. It's similar to Open AI's GPT4o and Claude Sonnet 3.5. SuperNova is trained with the most advanced optimization & learning techniques to generate highly accurate responses. It is the most flexible, cost-effective, and secure language model available. Customers can save up to 95% in total deployment costs when compared with traditional closed-source models. SuperNova can be used to integrate AI in apps and products, as well as for general chat and a variety of other uses. Update your models regularly with the latest open source tech to ensure you're not locked into a single solution. Protect your data using industry-leading privacy features.

Qwen2-VL, the latest version in the Qwen model family of vision language models, is based on Qwen2. Qwen2-VL is a newer version of Qwen-VL that has: SoTA understanding of images with different resolutions & ratios: Qwen2-VL reaches state-of-the art performance on visual understanding benchmarks including MathVista DocVQA RealWorldQA MTVQA etc. Understanding videos over 20 min: Qwen2-VL is able to understand videos longer than 20 minutes, allowing for high-quality video-based questions, dialogs, content creation, and more. Agent that can control your mobiles, robotics, etc. Qwen2-VL, with its complex reasoning and decision-making abilities, can be integrated into devices such as mobile phones, robots and other devices for automatic operation using visual environment and text instruction. Multilingual Support - To serve users worldwide, Qwen2-VL supports texts in other languages within images, besides English or Chinese.

The Gemini 1.5 Pro LLM is a powerful large-language model from Google that pushes the boundaries of natural languages understanding and generation. This model is part of Google DeepMind’s Gemini series and integrates advanced machine-learning techniques to provide exceptional performance for tasks such as text summarization, sentiment analyses, translation, conversational AI, and text completion. The Gemini 1.5 Pro LLM was designed with scalability and accuracy in mind. It is capable of handling real time applications in diverse environments from customer support systems, to content creation platforms. Gemini 1.5 Pro introduces the largest context window ever for a large scale foundation model. It achieves near perfect recall on long-context retriever tasks across modalities.

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.

The next generation of the large language model. This release includes modelweights and starting code to pretrained and fine tuned Llama languages models, ranging from 7B-70B parameters. Llama 1 models have a context length of 2 trillion tokens. Llama 2 models have a context length double that of Llama 1. The fine-tuned Llama 2 models have been trained using over 1,000,000 human annotations. Llama 2, a new open-source language model, outperforms many other open-source language models in external benchmarks. These include tests of reasoning, coding and proficiency, as well as knowledge tests. Llama 2 has been pre-trained using publicly available online data sources. Llama-2 chat, a fine-tuned version of the model, is based on publicly available instruction datasets, and more than 1 million human annotations. We have a wide range of supporters in the world who are committed to our open approach for today's AI. These companies have provided early feedback and have expressed excitement to build with Llama 2

The training of state-of-the art language models is extremely difficult. They require large compute budgets, complex distributed computing techniques and deep ML knowledge. Few organizations are able to train large language models from scratch. The number of organizations that do not open source their results is increasing, even though they have the expertise and resources to do so. We at Cerebras believe in open access to the latest models. Cerebras is proud to announce that Cerebras GPT, a family GPT models with 111 million to thirteen billion parameters, has been released to the open-source community. These models are trained using the Chinchilla Formula and provide the highest accuracy within a given computing budget. Cerebras GPT has faster training times and lower training costs. It also consumes less power than any other publicly available model.

Pixtral 12B, a multimodal AI model pioneered by Mistral AI and designed to process and understand both text and images data seamlessly, is a groundbreaking AI model. This model represents a significant advance in the integration of data types. It allows for more intuitive interaction and enhanced content creation abilities. Pixtral 12B, which is based on Mistral's NeMo 12B Text Model, incorporates an additional Vision Adapter that adds 400 million parameters. This allows it to handle visual inputs of up to 1024x1024 pixels. This model is capable of a wide range of applications from image analysis to answering visual content questions. Its versatility is demonstrated in real-world scenarios. Pixtral 12B is a powerful tool for developers, as it not only has a large context of 128k tokens, but also uses innovative techniques such as GeLU activation and RoPE 2D for its vision components.

LTM-2 mini is a 100M token model: LTM-2 mini. 100M tokens is 10,000,000 lines of code, or 750 novels. LTM-2 mini's sequence-dimension algorithms is approximately 1000x cheaper for each token decoded than the attention mechanism of Llama 3.0 405B1 when a 100M tokens context window is used. LTM only requires a fraction of one H100 HBM per user to store the same context.

Claude is an artificial intelligence language model that can generate text with human-like processing. Anthropic is an AI safety company and research firm that focuses on building reliable, interpretable and steerable AI systems. While large, general systems can provide significant benefits, they can also be unpredictable, unreliable and opaque. Our goal is to make progress in these areas. We are currently focusing on research to achieve these goals. However, we see many opportunities for our work in the future to create value both commercially and for the public good.

Introducing MPT-7B - the latest addition to our MosaicML Foundation Series. MPT-7B, a transformer that is trained from scratch using 1T tokens of code and text, is the latest entry in our MosaicML Foundation Series. It is open-source, available for commercial purposes, and has the same quality as LLaMA-7B. MPT-7B trained on the MosaicML Platform in 9.5 days, with zero human interaction at a cost $200k. You can now train, fine-tune and deploy your private MPT models. You can either start from one of our checkpoints, or you can start from scratch. For inspiration, we are also releasing three finetuned models in addition to the base MPT-7B: MPT-7B-Instruct, MPT-7B-Chat, and MPT-7B-StoryWriter-65k+, the last of which uses a context length of 65k tokens!

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.

GPT-J, a cutting edge language model developed by EleutherAI, is a leading-edge language model. GPT-J's performance is comparable to OpenAI's GPT-3 model on a variety of zero-shot tasks. GPT-J, in particular, has shown that it can surpass GPT-3 at tasks relating to code generation. The latest version of this language model is GPT-J-6B and is built on a linguistic data set called The Pile. This dataset is publically available and contains 825 gibibytes worth of language data organized into 22 subsets. GPT-J has some similarities with ChatGPT. However, GPTJ is not intended to be a chatbot. Its primary function is to predict texts. Databricks made a major development in March 2023 when they introduced Dolly, an Apache-licensed model that follows instructions.

Baichuan-13B, a large-scale language model with 13 billion parameters that is open source and available commercially by Baichuan Intelligent, was developed following Baichuan -7B. It has the best results for a language model of the same size in authoritative Chinese and English benchmarks. This release includes two versions of pretraining (Baichuan-13B Base) and alignment (Baichuan-13B Chat). Baichuan-13B has more data and a larger size. It expands the number parameters to 13 billion based on Baichuan -7B, and trains 1.4 trillion coins on high-quality corpus. This is 40% more than LLaMA-13B. It is open source and currently the model with the most training data in 13B size. Support Chinese and English bi-lingual, use ALiBi code, context window is 4096.

GPT-4o Claude 3.5 Sonnet Gemini 1.5 flash can all be accessed from the same platform for just 19 USD per month. Start a free trial without requiring a credit card.

One-stop AI Coding assistant for your favorite code editor. Supports GPT-4o, Claude 3.5 Sonnet and GPT-4o. Code suggestions in real-time based on cursor position and comments as you code. Select any code to update it with a simple prompt. Modify a function easily or rewrite a class. Chat with the active file or entire indexed codebase, using best models such as Claude 3.5 Sonnet and GPT-4o. You can also send a screenshot for debugging. Monica Code can be asked to create, modify or navigate through multiple files. Monica Code can help you generate code snippets and structures in your preferred language by describing your requirements using natural language. This AI-assisted feature can be used for a variety of programming tasks, ranging from simple scripts to complex application structures.

Martian outperforms GPT-4 across OpenAI's evals (open/evals). Martian outperforms GPT-4 in all OpenAI's evaluations (open/evals). We transform opaque black boxes into interpretable visual representations. Our router is our first tool built using our model mapping method. Model mapping is being used in many other applications, including transforming transformers from unintelligible matrices to human-readable programs. Automatically reroute your customers to other providers if a company has an outage or a high latency period. Calculate how much money you could save using the Martian Model Router by using our interactive cost calculator. Enter the number of users and tokens per session. Also, specify how you want to trade off between cost and quality.

Gemini Ultra is an advanced new language model by Google DeepMind. It is the most powerful and largest model in the Gemini Family, which includes Gemini Pro & Gemini Nano. Gemini Ultra was designed to handle highly complex tasks such as machine translation, code generation, and natural language processing. It is the first language model that has outperformed human experts in the Massive Multitask Language Understanding test (MMLU), achieving a score 90%.

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.

A Chrome extension that runs your analytics apps. MinusX provides the fastest way to gain insights from data. Interact with MinusX for modifications or extensions to existing notebooks. Select a section and ask questions or request modifications. MinusX integrates with your existing analytics tools, such as Jupyter Notebooks Metabase Tableau etc. You can create analyses with minusx and instantly share the results with your team. MinusX has nuanced privacy controls. All data you share will be used to create better, more accurate models. We never share any of your data with third-parties. MinusX integrates seamlessly with existing tools. This means you will never have to leave your workflow to answer a question. MinusX is able to select the appropriate action for each context because actions are first class entities. Currently we support Claude Sonnet 3.5 and GPT-4o. We are also working to allow you to bring your own models.

This repository contains a research preview of LongLLaMA. It is a large language-model capable of handling contexts up to 256k tokens. LongLLaMA was built on the foundation of OpenLLaMA, and fine-tuned with the Focused Transformer method. LongLLaMA code was built on the foundation of Code Llama. We release a smaller base variant of the LongLLaMA (not instruction-tuned) on a permissive licence (Apache 2.0), and inference code that supports longer contexts for hugging face. Our model weights are a drop-in replacement for LLaMA (for short contexts up to 2048 tokens) in existing implementations. We also provide evaluation results, and comparisons with the original OpenLLaMA model.

CodeQwen, developed by the Qwen Team, Alibaba Cloud, is the code version. It is a transformer based decoder only language model that has been pre-trained with a large number of codes. A series of benchmarks shows that the code generation is strong and that it performs well. Supporting long context generation and understanding with a context length of 64K tokens. CodeQwen is a 92-language coding language that provides excellent performance for text-to SQL, bug fixes, and more. CodeQwen chat is as simple as writing a few lines of code using transformers. We build the tokenizer and model using pre-trained methods and use the generate method for chatting. The chat template is provided by the tokenizer. Following our previous practice, we apply the ChatML Template for chat models. The model will complete the code snippets in accordance with the prompts without any additional formatting.

ChatGPT Enterprise is the most powerful version yet, with enterprise-grade security and privacy. 1. Training models do not use customer prompts or data 2. Data encryption in transit and at rest (TLS 1.2+). 3. SOC 2 compliant 4. Easy bulk member management and dedicated admin console 5. SSO and Domain Verification 6. Use the analytics dashboard to understand usage 7. Access to GPT-4 Advanced Data Analysis and GPT-4 at high speed is unlimited 8. 32k token context window for 4X longer inputs, memory and inputs 9. Shareable chat templates to help your company collaborate

StarCoderBase and StarCoder are Large Language Models (Code LLMs), trained on permissively-licensed data from GitHub. This includes data from 80+ programming language, Git commits and issues, Jupyter Notebooks, and Git commits. We trained a 15B-parameter model for 1 trillion tokens, similar to LLaMA. We refined the StarCoderBase for 35B Python tokens. The result is a new model we call StarCoder. StarCoderBase is a model that outperforms other open Code LLMs in popular programming benchmarks. It also matches or exceeds closed models like code-cushman001 from OpenAI, the original Codex model which powered early versions GitHub Copilot. StarCoder models are able to process more input with a context length over 8,000 tokens than any other open LLM. This allows for a variety of interesting applications. By prompting the StarCoder model with a series dialogues, we allowed them to act like a technical assistant.

Falcon-7B is a 7B parameter causal decoder model, built by TII. It was trained on 1,500B tokens from RefinedWeb enhanced by curated corpora. It is available under the Apache 2.0 licence. Why use Falcon-7B Falcon-7B? It outperforms similar open-source models, such as MPT-7B StableLM RedPajama, etc. It is a result of being trained using 1,500B tokens from RefinedWeb enhanced by curated corpora. OpenLLM Leaderboard. It has an architecture optimized for inference with FlashAttention, multiquery and multiquery. It is available under an Apache 2.0 license that allows commercial use without any restrictions or royalties.

Mistral NeMo, our new best small model. A state-of the-art 12B with 128k context and released under Apache 2.0 license. Mistral NeMo, a 12B-model built in collaboration with NVIDIA, is available. Mistral NeMo has a large context of up to 128k Tokens. Its reasoning, world-knowledge, and coding precision are among the best in its size category. Mistral NeMo, which relies on a standard architecture, is easy to use. It can be used as a replacement for any system that uses Mistral 7B. We have released Apache 2.0 licensed pre-trained checkpoints and instruction-tuned base checkpoints to encourage adoption by researchers and enterprises. Mistral NeMo has been trained with quantization awareness to enable FP8 inferences without performance loss. The model was designed for global applications that are multilingual. It is trained in function calling, and has a large contextual window. It is better than Mistral 7B at following instructions, reasoning and handling multi-turn conversation.

Mixtral 8x22B is our latest open model. It sets new standards for performance and efficiency in the AI community. It is a sparse Mixture-of-Experts model (SMoE), which uses only 39B active variables out of 141B. This offers unparalleled cost efficiency in relation to its size. It is fluently bilingual in English, French Italian, German and Spanish. It has strong math and coding skills. It is natively able to call functions; this, along with the constrained-output mode implemented on La Plateforme, enables application development at scale and modernization of tech stacks. Its 64K context window allows for precise information retrieval from large documents. We build models with unmatched cost-efficiency for their respective sizes. This allows us to deliver the best performance-tocost ratio among models provided by the Community. Mixtral 8x22B continues our open model family. Its sparse patterns of activation make it faster than any 70B model.

NinjaChat offers a complete AI platform. Use 8+ AI apps in One platform. You can access six AI chatbots of premium quality (including GPT 4o, Claude 3 Sonnet and more), a AI image generator (Stable Diffusion 3), as well as an AI data scientist, all seamlessly integrated.

Falcon-40B is a 40B parameter causal decoder model, built by TII. It was trained on 1,000B tokens from RefinedWeb enhanced by curated corpora. It is available under the Apache 2.0 licence. Why use Falcon-40B Falcon-40B is the best open source model available. Falcon-40B outperforms LLaMA, StableLM, RedPajama, MPT, etc. OpenLLM Leaderboard. It has an architecture optimized for inference with FlashAttention, multiquery and multiquery. It is available under an Apache 2.0 license that allows commercial use without any restrictions or royalties. This is a raw model that should be finetuned to fit most uses. If you're looking for a model that can take generic instructions in chat format, we suggest Falcon-40B Instruct.

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.

Jamba is a powerful and efficient long context model that is open to builders, but built for enterprises. Jamba's latency is superior to all other leading models of similar size. Jamba's 256k window is the longest available. Jamba's Mamba Transformer MoE Architecture is designed to increase efficiency and reduce costs. Jamba includes key features from OOTB, including function calls, JSON output, document objects and citation mode. Jamba 1.5 models deliver high performance throughout the entire context window. Jamba 1.5 models score highly in common quality benchmarks. Secure deployment tailored to your enterprise. Start using Jamba immediately on our production-grade SaaS Platform. Our strategic partners can deploy the Jamba model family. For enterprises who require custom solutions, we offer VPC and on-premise deployments. We offer hands-on management and continuous pre-training for enterprises with unique, bespoke needs.

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.

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.

Hermes 3 contains advanced long-term context retention and multi-turn conversation capabilities, complex roleplaying and internal monologue abilities, and enhanced agentic function-calling. Hermes 3 has advanced long-term contextual retention, multi-turn conversation capabilities, complex roleplaying, internal monologue, and enhanced agentic functions-calling. Our training data encourages the model in a very aggressive way to follow the system prompts and instructions exactly and in a highly adaptive manner. Hermes 3 was developed by fine-tuning Llama 3.0 8B, 70B and 405B and training with a dataset primarily containing synthetic responses. The model has a performance that is comparable to Llama 3.1, but with deeper reasoning and creative abilities. Hermes 3 is an instruct and tool-use model series with strong reasoning and creativity abilities.

IBM® Granite™ is an AI family that was designed from scratch for business applications. It helps to ensure trust and scalability of AI-driven apps. Granite models are open source and available today. We want to make AI accessible to as many developers as we can. We have made the core Granite Code, Time Series models, Language and GeoSpatial available on Hugging Face, under a permissive Apache 2.0 licence that allows for broad commercial use. Granite models are all trained using carefully curated data. The data used to train them is transparent at a level that is unmatched in the industry. We have also made the tools that we use available to ensure that the data is of high quality and meets the standards required by enterprise-grade applications.

Our models are deployed all over the world for the best possible response time. Integrate our OpenAI compatible API seamlessly into your application. Start in minutes and scale seamlessly to serve millions of users. Our API is 4 times cheaper than OpenAI GPT-3.5 API due to our extensive performance and scale optimizations. Our AI model can generate text and chat at ChatGPT performance levels for a fraction of what it costs. Our OpenAI-compatible API makes it easy to get started. Use one of the most powerful AI image models in order to create stunning images, graphics and illustrations.

Qwen LLM is a family of large-language models (LLMs), developed by Damo Academy, an Alibaba Cloud subsidiary. These models are trained using a large dataset of text and codes, allowing them the ability to understand and generate text that is human-like, translate languages, create different types of creative content and answer your question in an informative manner. Here are some of the key features of Qwen LLMs. Variety of sizes: Qwen's series includes sizes ranging from 1.8 billion parameters to 72 billion, offering options that meet different needs and performance levels. Open source: Certain versions of Qwen have open-source code, which is available to anyone for use and modification. Qwen is multilingual and can translate multiple languages including English, Chinese and Japanese. Qwen models are capable of a wide range of tasks, including text summarization and code generation, as well as generation and translation.

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.

Kerlig for macOS adds AI to any application. Bring your own API keys for OpenAI, Claude Pro, Gemini Pro and Groq. Never again be embarrassed by typos. Before you send, check spelling and grammar. Send a perfectly crafted reply using your tone of speech. Kerlig is an AI assistant that writes in context. Claude models allow you to chat with up 350 pages of documents. Kerlig will take the text you have selected in any app, and perform various actions on it, such as correcting spelling, changing tone or writing a response. You can then paste the generated text into the original app or copy it to your clipboard and manually paste it. OpenAI models allow you to chat with PDFs and other long-form documents. The maximum input limit is 8, 16 or 32K tokens. Kerlig is lightning fast. It launches in 150 milliseconds, and only uses 60-140MB memory.

Through scientific rigor and human insight, healthcare breakthroughs can change the world, bringing hope to humanity. We believe that AI can help in this area, through collaboration between researchers, healthcare organisations, and the wider ecosystem. Today, we are sharing exciting progress in these initiatives with the announcement that Google's large language model (LLM) for medical applications, called Med PaLM 2, will be available to a limited number of customers. In the coming weeks, it will be available to a small group of Google Cloud users for limited testing. We will explore use cases, share feedback, and investigate safe, responsible and meaningful ways to utilize this technology. Med-PaLM 2, which harnesses Google's LLMs aligned with the medical domain, is able to answer medical questions more accurately and safely. Med-PaLM 2 is the first LLM that has performed at an "expert" level on the MedQA dataset consisting of US Medical Licensing Examination-style questions.

Poe allows you to ask questions, get instant responses, and have back-and forth conversations with AI. Access to gpt3.5-turbo and Claude from Anthropic as well as a variety other bots.

DuckDuckGo AI Chat, a private chat service powered by AI, currently supports OpenAI’s GPT-3.5 chat model and Anthropic’s Claude chat model.

ARES: Your all-in-one AI subscription service. No more juggling several accounts - access the world of AI using just one. What you get - Stable Diffusion XL for AI image generation ElevenLabs for AI Audio Generation Wolfram Alpha is a math problem solving AI. - GPT-4 & Claude 3.5 Sonnets for Conversations - We are constantly updating our toolkit Soon, you will be able to use your ARES account directly to access AI partner websites, and spend your credits without additional subscriptions. With our flexible credit system, you can use your monthly allowance on any tool. The more you subscribe to our service, the more credits we give you. ARES is the perfect tool for AI enthusiasts, creators, and anyone interested in AI's potential. Create images, create audio, solve complex issues, or chat with AI. Join the #ARESRevolution today. Start your free trial to experience the convenience of AI tools at your fingertips.

Aider allows you to pair program with LLMs and edit code in your local repository. Start a project or work on an existing git repository. Aider is compatible with GPT-4o & Claude 3.5 Sonnet, but can connect to any LLM. Aider is one of the highest scorers on SWE Bench. SWE Bench is a challenging benchmark for software engineering. Aider solved real GitHub problems from popular open-source projects such as django scikitlearn matplotlib etc.

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.

MacCopilot is an app that integrates Copilot AI into macOS. It allows users to interact with AI on a natural level. MacCopilot integrate AI model like GPT-4o and screen capturing to provide a convenient way of talking directly with AI about screen content. Key Features - AI-Powered Interactive: Interact with AI models about your screen content. - Flexible Screenshot Capture: Select, resize and quickly capture any portion of your screen. - Multi-Platform support: Connect to different AI models such as OpenAI, Google Gemini AI and Claude AI. - Builtin OpenAI GPT-4o, Claude AI 3.5 Sonnet Use Cases - Summarize articles - Explain social media conversation Draft email responses - Improved OCR performance on screen content - Filling out forms