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Jina AI is a Berlin-based software company that provides a "search foundation" platform, offering various AI-powered tools designed to help developers build the next generation of search applications for unstructured data. Its mission is to enable businesses to create reliable and high-quality Generative AI (GenAI) and multimodal search applications by combining Embeddings, Rerankers, and Small Language Models (SLMs). Jina AI's tools are designed to provide real-time, accurate, and unbiased information, optimized for LLMs and AI agents.

Jina AI is a Berlin-based software company that provides a "search foundation" platform, offering various AI-powered tools designed to help developers build the next generation of search applications for unstructured data. Its mission is to enable businesses to create reliable and high-quality Generative AI (GenAI) and multimodal search applications by combining Embeddings, Rerankers, and Small Language Models (SLMs). Jina AI's tools are designed to provide real-time, accurate, and unbiased information, optimized for LLMs and AI agents.

Jina AI is a Berlin-based software company that provides a "search foundation" platform, offering various AI-powered tools designed to help developers build the next generation of search applications for unstructured data. Its mission is to enable businesses to create reliable and high-quality Generative AI (GenAI) and multimodal search applications by combining Embeddings, Rerankers, and Small Language Models (SLMs). Jina AI's tools are designed to provide real-time, accurate, and unbiased information, optimized for LLMs and AI agents.


LangChain AI Local Deep Researcher is an autonomous, fully local web research assistant designed to conduct in-depth research on user-provided topics. It leverages local Large Language Models (LLMs) hosted by Ollama or LM Studio to iteratively generate search queries, summarize findings from web sources, and refine its understanding by identifying and addressing knowledge gaps. The final output is a comprehensive markdown report with citations to all sources.


LangChain AI Local Deep Researcher is an autonomous, fully local web research assistant designed to conduct in-depth research on user-provided topics. It leverages local Large Language Models (LLMs) hosted by Ollama or LM Studio to iteratively generate search queries, summarize findings from web sources, and refine its understanding by identifying and addressing knowledge gaps. The final output is a comprehensive markdown report with citations to all sources.


LangChain AI Local Deep Researcher is an autonomous, fully local web research assistant designed to conduct in-depth research on user-provided topics. It leverages local Large Language Models (LLMs) hosted by Ollama or LM Studio to iteratively generate search queries, summarize findings from web sources, and refine its understanding by identifying and addressing knowledge gaps. The final output is a comprehensive markdown report with citations to all sources.

GPT-4o Search Preview is a powerful experimental feature of OpenAI’s GPT-4o model, designed to act as a high-performance retrieval system. Rather than just generating answers from training data, it allows the model to search through large datasets, documents, or knowledge bases to surface relevant results with context-aware accuracy. Think of it as your AI assistant with built-in research superpowers—faster, smarter, and surprisingly precise. This preview gives developers a taste of what’s coming next: an intelligent search engine built directly into the GPT-4o ecosystem.


GPT-4o Search Preview is a powerful experimental feature of OpenAI’s GPT-4o model, designed to act as a high-performance retrieval system. Rather than just generating answers from training data, it allows the model to search through large datasets, documents, or knowledge bases to surface relevant results with context-aware accuracy. Think of it as your AI assistant with built-in research superpowers—faster, smarter, and surprisingly precise. This preview gives developers a taste of what’s coming next: an intelligent search engine built directly into the GPT-4o ecosystem.


GPT-4o Search Preview is a powerful experimental feature of OpenAI’s GPT-4o model, designed to act as a high-performance retrieval system. Rather than just generating answers from training data, it allows the model to search through large datasets, documents, or knowledge bases to surface relevant results with context-aware accuracy. Think of it as your AI assistant with built-in research superpowers—faster, smarter, and surprisingly precise. This preview gives developers a taste of what’s coming next: an intelligent search engine built directly into the GPT-4o ecosystem.


Grok 3 is the latest flagship chatbot by Elon Musk’s xAI, described as "the world’s smartest AI." It was trained on a massive 200,000‑GPU supercomputer and offers tenfold more computing power than Grok 2. Equipped with two reasoning modes—Think and Big Brain—and featuring DeepSearch (a contextual web-and-X research tool), Grok 3 excels in math, science, coding, and truth-seeking tasks—all while offering fast, lively conversational style.


Grok 3 is the latest flagship chatbot by Elon Musk’s xAI, described as "the world’s smartest AI." It was trained on a massive 200,000‑GPU supercomputer and offers tenfold more computing power than Grok 2. Equipped with two reasoning modes—Think and Big Brain—and featuring DeepSearch (a contextual web-and-X research tool), Grok 3 excels in math, science, coding, and truth-seeking tasks—all while offering fast, lively conversational style.


Grok 3 is the latest flagship chatbot by Elon Musk’s xAI, described as "the world’s smartest AI." It was trained on a massive 200,000‑GPU supercomputer and offers tenfold more computing power than Grok 2. Equipped with two reasoning modes—Think and Big Brain—and featuring DeepSearch (a contextual web-and-X research tool), Grok 3 excels in math, science, coding, and truth-seeking tasks—all while offering fast, lively conversational style.


Grok 2 is xAI’s second-generation chatbot model, launched in August 2024 as a substantial upgrade over Grok 1.5. It delivers frontier-level performance in chat, coding, reasoning, vision tasks, and image generation via the FLUX.1 system. On leaderboards, it outscored Claude 3.5 Sonnet and GPT‑4 Turbo, with strong results in GPQA (56%), MMLU (87.5%), MATH (76.1%), HumanEval (88.4%), MathVista, and DocVQA benchmarks.


Grok 2 is xAI’s second-generation chatbot model, launched in August 2024 as a substantial upgrade over Grok 1.5. It delivers frontier-level performance in chat, coding, reasoning, vision tasks, and image generation via the FLUX.1 system. On leaderboards, it outscored Claude 3.5 Sonnet and GPT‑4 Turbo, with strong results in GPQA (56%), MMLU (87.5%), MATH (76.1%), HumanEval (88.4%), MathVista, and DocVQA benchmarks.


Grok 2 is xAI’s second-generation chatbot model, launched in August 2024 as a substantial upgrade over Grok 1.5. It delivers frontier-level performance in chat, coding, reasoning, vision tasks, and image generation via the FLUX.1 system. On leaderboards, it outscored Claude 3.5 Sonnet and GPT‑4 Turbo, with strong results in GPQA (56%), MMLU (87.5%), MATH (76.1%), HumanEval (88.4%), MathVista, and DocVQA benchmarks.


Llama 3.1 is Meta’s most advanced open-source Llama 3 model, released on July 23, 2024. It comes in three sizes—8B, 70B, and 405B parameters—with an expanded 128K-token context window and improved multilingual and multimodal capabilities. It significantly outperforms Llama 3 and rivals proprietary models across benchmarks like GSM8K, MMLU, HumanEval, ARC, and tool-augmented reasoning tasks.


Llama 3.1 is Meta’s most advanced open-source Llama 3 model, released on July 23, 2024. It comes in three sizes—8B, 70B, and 405B parameters—with an expanded 128K-token context window and improved multilingual and multimodal capabilities. It significantly outperforms Llama 3 and rivals proprietary models across benchmarks like GSM8K, MMLU, HumanEval, ARC, and tool-augmented reasoning tasks.


Llama 3.1 is Meta’s most advanced open-source Llama 3 model, released on July 23, 2024. It comes in three sizes—8B, 70B, and 405B parameters—with an expanded 128K-token context window and improved multilingual and multimodal capabilities. It significantly outperforms Llama 3 and rivals proprietary models across benchmarks like GSM8K, MMLU, HumanEval, ARC, and tool-augmented reasoning tasks.


Llama 3.3 is Meta’s instruction-tuned, text-only large language model released on December 6, 2024, available in a 70B-parameter size. It matches the performance of much larger models using significantly fewer parameters, is multilingual across eight key languages, and supports a massive 128,000-token context window—ideal for handling long-form documents, codebases, and detailed reasoning tasks.


Llama 3.3 is Meta’s instruction-tuned, text-only large language model released on December 6, 2024, available in a 70B-parameter size. It matches the performance of much larger models using significantly fewer parameters, is multilingual across eight key languages, and supports a massive 128,000-token context window—ideal for handling long-form documents, codebases, and detailed reasoning tasks.


Llama 3.3 is Meta’s instruction-tuned, text-only large language model released on December 6, 2024, available in a 70B-parameter size. It matches the performance of much larger models using significantly fewer parameters, is multilingual across eight key languages, and supports a massive 128,000-token context window—ideal for handling long-form documents, codebases, and detailed reasoning tasks.


DeepSeek R1 Distill refers to a family of dense, smaller models distilled from DeepSeek’s flagship DeepSeek R1 reasoning model. Released early 2025, these models come in sizes ranging from 1.5B to 70B parameters (e.g., DeepSeek‑R1‑Distill‑Qwen‑32B) and retain powerful reasoning and chain-of-thought abilities in a more efficient architecture. Benchmarks show distilled variants outperform models like OpenAI’s o1‑mini, while remaining open‑source under MIT license.


DeepSeek R1 Distill refers to a family of dense, smaller models distilled from DeepSeek’s flagship DeepSeek R1 reasoning model. Released early 2025, these models come in sizes ranging from 1.5B to 70B parameters (e.g., DeepSeek‑R1‑Distill‑Qwen‑32B) and retain powerful reasoning and chain-of-thought abilities in a more efficient architecture. Benchmarks show distilled variants outperform models like OpenAI’s o1‑mini, while remaining open‑source under MIT license.


DeepSeek R1 Distill refers to a family of dense, smaller models distilled from DeepSeek’s flagship DeepSeek R1 reasoning model. Released early 2025, these models come in sizes ranging from 1.5B to 70B parameters (e.g., DeepSeek‑R1‑Distill‑Qwen‑32B) and retain powerful reasoning and chain-of-thought abilities in a more efficient architecture. Benchmarks show distilled variants outperform models like OpenAI’s o1‑mini, while remaining open‑source under MIT license.

Mistral Large 2 is the second-generation flagship model from Mistral AI, released in July 2024. Also referenced as mistral-large-2407, it’s a 123 B-parameter dense LLM with a 128 K-token context window, supporting dozens of languages and 80+ coding languages. It excels in reasoning, code generation, mathematics, instruction-following, and function calling—designed for high throughput on single-node setups.

Mistral Large 2 is the second-generation flagship model from Mistral AI, released in July 2024. Also referenced as mistral-large-2407, it’s a 123 B-parameter dense LLM with a 128 K-token context window, supporting dozens of languages and 80+ coding languages. It excels in reasoning, code generation, mathematics, instruction-following, and function calling—designed for high throughput on single-node setups.

Mistral Large 2 is the second-generation flagship model from Mistral AI, released in July 2024. Also referenced as mistral-large-2407, it’s a 123 B-parameter dense LLM with a 128 K-token context window, supporting dozens of languages and 80+ coding languages. It excels in reasoning, code generation, mathematics, instruction-following, and function calling—designed for high throughput on single-node setups.

Perplexity Comet is an AI-augmented browser that blends web search, chat, and automation into a unified environment. Rather than switching between browser tabs and chat windows, Comet allows users to ask questions, explore content, and execute tasks all within the browsing flow. It acts like a conversational companion embedded in your web experience, helping you dig deeper into topics, compare different sources, and interact with pages more intelligently.

Perplexity Comet is an AI-augmented browser that blends web search, chat, and automation into a unified environment. Rather than switching between browser tabs and chat windows, Comet allows users to ask questions, explore content, and execute tasks all within the browsing flow. It acts like a conversational companion embedded in your web experience, helping you dig deeper into topics, compare different sources, and interact with pages more intelligently.

Perplexity Comet is an AI-augmented browser that blends web search, chat, and automation into a unified environment. Rather than switching between browser tabs and chat windows, Comet allows users to ask questions, explore content, and execute tasks all within the browsing flow. It acts like a conversational companion embedded in your web experience, helping you dig deeper into topics, compare different sources, and interact with pages more intelligently.

ChatBetter is an AI platform designed to unify access to all major large language models (LLMs) within a single chat interface. Built for productivity and accuracy, ChatBetter leverages automatic model selection to route every query to the most capable AI—eliminating guesswork about which model to use. Users can directly compare responses from OpenAI, Anthropic, Google, Meta, DeepSeek, Perplexity, Mistral, xAI, and Cohere models side by side, or merge answers for comprehensive insights. The system is crafted for teams and individuals alike, enabling complex research, planning, and writing tasks to be accomplished efficiently in one place.

ChatBetter is an AI platform designed to unify access to all major large language models (LLMs) within a single chat interface. Built for productivity and accuracy, ChatBetter leverages automatic model selection to route every query to the most capable AI—eliminating guesswork about which model to use. Users can directly compare responses from OpenAI, Anthropic, Google, Meta, DeepSeek, Perplexity, Mistral, xAI, and Cohere models side by side, or merge answers for comprehensive insights. The system is crafted for teams and individuals alike, enabling complex research, planning, and writing tasks to be accomplished efficiently in one place.

ChatBetter is an AI platform designed to unify access to all major large language models (LLMs) within a single chat interface. Built for productivity and accuracy, ChatBetter leverages automatic model selection to route every query to the most capable AI—eliminating guesswork about which model to use. Users can directly compare responses from OpenAI, Anthropic, Google, Meta, DeepSeek, Perplexity, Mistral, xAI, and Cohere models side by side, or merge answers for comprehensive insights. The system is crafted for teams and individuals alike, enabling complex research, planning, and writing tasks to be accomplished efficiently in one place.

LLM.co LLM-as-a-Service (LLMaaS) is a secure, enterprise-grade AI platform that provides private and fully managed large language model deployments tailored to an organization’s specific industry, workflows, and data. Unlike public LLM APIs, each client receives a dedicated, single-tenant model hosted in private clouds or virtual private clouds (VPCs), ensuring complete data privacy and compliance. The platform offers model fine-tuning on proprietary internal documents, semantic search, multi-document Q&A, custom AI agents, contract review, and offline AI capabilities for regulated industries. It removes infrastructure burdens by handling deployment, scaling, and monitoring, while enabling businesses to customize models for domain-specific language, regulatory compliance, and unique operational needs.

LLM.co LLM-as-a-Service (LLMaaS) is a secure, enterprise-grade AI platform that provides private and fully managed large language model deployments tailored to an organization’s specific industry, workflows, and data. Unlike public LLM APIs, each client receives a dedicated, single-tenant model hosted in private clouds or virtual private clouds (VPCs), ensuring complete data privacy and compliance. The platform offers model fine-tuning on proprietary internal documents, semantic search, multi-document Q&A, custom AI agents, contract review, and offline AI capabilities for regulated industries. It removes infrastructure burdens by handling deployment, scaling, and monitoring, while enabling businesses to customize models for domain-specific language, regulatory compliance, and unique operational needs.

LLM.co LLM-as-a-Service (LLMaaS) is a secure, enterprise-grade AI platform that provides private and fully managed large language model deployments tailored to an organization’s specific industry, workflows, and data. Unlike public LLM APIs, each client receives a dedicated, single-tenant model hosted in private clouds or virtual private clouds (VPCs), ensuring complete data privacy and compliance. The platform offers model fine-tuning on proprietary internal documents, semantic search, multi-document Q&A, custom AI agents, contract review, and offline AI capabilities for regulated industries. It removes infrastructure burdens by handling deployment, scaling, and monitoring, while enabling businesses to customize models for domain-specific language, regulatory compliance, and unique operational needs.
This page was researched and written by the ATB Editorial Team. Our team researches each AI tool by reviewing its official website, testing features, exploring real use cases, and considering user feedback. Every page is fact-checked and regularly updated to ensure the information stays accurate, neutral, and useful for our readers.
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