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GPT-Image-1 is OpenAI's state-of-the-art vision model designed to understand and interpret images with human-like perception. It enables developers and businesses to analyze, summarize, and extract detailed insights from images using natural language. Whether you're building AI agents, accessibility tools, or image-driven workflows, GPT-Image-1 brings powerful multimodal capabilities into your applications with impressive accuracy. Optimized for use via API, it can handle diverse image types—charts, screenshots, photographs, documents, and more—making it one of the most versatile models in OpenAI’s portfolio.
GPT-Image-1 is OpenAI's state-of-the-art vision model designed to understand and interpret images with human-like perception. It enables developers and businesses to analyze, summarize, and extract detailed insights from images using natural language. Whether you're building AI agents, accessibility tools, or image-driven workflows, GPT-Image-1 brings powerful multimodal capabilities into your applications with impressive accuracy. Optimized for use via API, it can handle diverse image types—charts, screenshots, photographs, documents, and more—making it one of the most versatile models in OpenAI’s portfolio.
GPT-Image-1 is OpenAI's state-of-the-art vision model designed to understand and interpret images with human-like perception. It enables developers and businesses to analyze, summarize, and extract detailed insights from images using natural language. Whether you're building AI agents, accessibility tools, or image-driven workflows, GPT-Image-1 brings powerful multimodal capabilities into your applications with impressive accuracy. Optimized for use via API, it can handle diverse image types—charts, screenshots, photographs, documents, and more—making it one of the most versatile models in OpenAI’s portfolio.
Meta Llama 4 is the latest generation of Meta’s large language model series. It features a mixture-of-experts (MoE) architecture, making it both highly efficient and powerful. Llama 4 is natively multimodal—supporting text and image inputs—and offers three key variants: Scout (17B active parameters, 10 M token context), Maverick (17B active, 1 M token context), and Behemoth (288B active, 2 T total parameters; still in development). Designed for long-context reasoning, multilingual understanding, and open-weight availability (with license restrictions), Llama 4 excels in benchmarks and versatility.
Meta Llama 4 is the latest generation of Meta’s large language model series. It features a mixture-of-experts (MoE) architecture, making it both highly efficient and powerful. Llama 4 is natively multimodal—supporting text and image inputs—and offers three key variants: Scout (17B active parameters, 10 M token context), Maverick (17B active, 1 M token context), and Behemoth (288B active, 2 T total parameters; still in development). Designed for long-context reasoning, multilingual understanding, and open-weight availability (with license restrictions), Llama 4 excels in benchmarks and versatility.
Meta Llama 4 is the latest generation of Meta’s large language model series. It features a mixture-of-experts (MoE) architecture, making it both highly efficient and powerful. Llama 4 is natively multimodal—supporting text and image inputs—and offers three key variants: Scout (17B active parameters, 10 M token context), Maverick (17B active, 1 M token context), and Behemoth (288B active, 2 T total parameters; still in development). Designed for long-context reasoning, multilingual understanding, and open-weight availability (with license restrictions), Llama 4 excels in benchmarks and versatility.
Meta Llama 3 is Meta’s third-generation open-weight large language model family, released in April 2024 and enhanced in July 2024 with the 3.1 update. It spans three sizes—8B, 70B, and 405B parameters—each offering a 128K‑token context window. Llama 3 excels at reasoning, code generation, multilingual text, and instruction-following, and introduces multimodal vision (image understanding) capabilities in its 3.2 series. Robust safety mechanisms like Llama Guard 3, Code Shield, and CyberSec Eval 2 ensure responsible output.
Meta Llama 3 is Meta’s third-generation open-weight large language model family, released in April 2024 and enhanced in July 2024 with the 3.1 update. It spans three sizes—8B, 70B, and 405B parameters—each offering a 128K‑token context window. Llama 3 excels at reasoning, code generation, multilingual text, and instruction-following, and introduces multimodal vision (image understanding) capabilities in its 3.2 series. Robust safety mechanisms like Llama Guard 3, Code Shield, and CyberSec Eval 2 ensure responsible output.
Meta Llama 3 is Meta’s third-generation open-weight large language model family, released in April 2024 and enhanced in July 2024 with the 3.1 update. It spans three sizes—8B, 70B, and 405B parameters—each offering a 128K‑token context window. Llama 3 excels at reasoning, code generation, multilingual text, and instruction-following, and introduces multimodal vision (image understanding) capabilities in its 3.2 series. Robust safety mechanisms like Llama Guard 3, Code Shield, and CyberSec Eval 2 ensure responsible output.
DeepSeek VL is DeepSeek’s open-source vision-language model designed for real-world multimodal understanding. It employs a hybrid vision encoder (SigLIP‑L + SAM), processes high-resolution images (up to 1024×1024), and supports both base and chat variants across two sizes: 1.3B and 7B parameters. It excels on tasks like OCR, diagram reasoning, webpage parsing, and visual Q&A—while preserving strong language ability.
DeepSeek VL is DeepSeek’s open-source vision-language model designed for real-world multimodal understanding. It employs a hybrid vision encoder (SigLIP‑L + SAM), processes high-resolution images (up to 1024×1024), and supports both base and chat variants across two sizes: 1.3B and 7B parameters. It excels on tasks like OCR, diagram reasoning, webpage parsing, and visual Q&A—while preserving strong language ability.
DeepSeek VL is DeepSeek’s open-source vision-language model designed for real-world multimodal understanding. It employs a hybrid vision encoder (SigLIP‑L + SAM), processes high-resolution images (up to 1024×1024), and supports both base and chat variants across two sizes: 1.3B and 7B parameters. It excels on tasks like OCR, diagram reasoning, webpage parsing, and visual Q&A—while preserving strong language ability.
Grok 3 Mini Fast is the low-latency, high-performance version of xAI’s Grok 3 Mini model. Released in beta around May 2025, it offers the same visible chain-of-thought reasoning as Grok 3 Mini but delivers responses significantly faster, powered by optimized infrastructure. It supports up to 131,072 tokens of context.
Grok 3 Mini Fast is the low-latency, high-performance version of xAI’s Grok 3 Mini model. Released in beta around May 2025, it offers the same visible chain-of-thought reasoning as Grok 3 Mini but delivers responses significantly faster, powered by optimized infrastructure. It supports up to 131,072 tokens of context.
Grok 3 Mini Fast is the low-latency, high-performance version of xAI’s Grok 3 Mini model. Released in beta around May 2025, it offers the same visible chain-of-thought reasoning as Grok 3 Mini but delivers responses significantly faster, powered by optimized infrastructure. It supports up to 131,072 tokens of context.
Grok 3 Mini Fast is xAI’s most recent, low-latency variant of the compact Grok 3 Mini model. It maintains full chain-of-thought “Think” reasoning and multimodal support while delivering faster response times. The model handles up to 131,072 tokens of context and is now widely accessible in beta via xAI API and select cloud platforms.
Grok 3 Mini Fast is xAI’s most recent, low-latency variant of the compact Grok 3 Mini model. It maintains full chain-of-thought “Think” reasoning and multimodal support while delivering faster response times. The model handles up to 131,072 tokens of context and is now widely accessible in beta via xAI API and select cloud platforms.
Grok 3 Mini Fast is xAI’s most recent, low-latency variant of the compact Grok 3 Mini model. It maintains full chain-of-thought “Think” reasoning and multimodal support while delivering faster response times. The model handles up to 131,072 tokens of context and is now widely accessible in beta via xAI API and select cloud platforms.
Llama 4 Behemoth is Meta’s ultimate “teacher” model within the Llama 4 series, currently in preview and training. Featuring an enormous 2 trillion total parameters with 288 billion active in a Mixture-of-Experts architecture (16 experts), it's designed to push the limits of multimodal reasoning, STEM, and long-context tasks. Initially slated for April 2025, its release has been postponed to fall 2025 or later due to internal performance and alignment concerns.
Llama 4 Behemoth is Meta’s ultimate “teacher” model within the Llama 4 series, currently in preview and training. Featuring an enormous 2 trillion total parameters with 288 billion active in a Mixture-of-Experts architecture (16 experts), it's designed to push the limits of multimodal reasoning, STEM, and long-context tasks. Initially slated for April 2025, its release has been postponed to fall 2025 or later due to internal performance and alignment concerns.
Llama 4 Behemoth is Meta’s ultimate “teacher” model within the Llama 4 series, currently in preview and training. Featuring an enormous 2 trillion total parameters with 288 billion active in a Mixture-of-Experts architecture (16 experts), it's designed to push the limits of multimodal reasoning, STEM, and long-context tasks. Initially slated for April 2025, its release has been postponed to fall 2025 or later due to internal performance and alignment concerns.
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.
Llama 3.2 Vision is Meta’s first open-source multimodal Llama model series, released on September 25, 2024. Available in 11 B and 90 B parameter sizes, it merges advanced image understanding with a massive 128 K‑token text context. Optimized for vision reasoning, captioning, document QA, and visual math tasks, it outperforms many closed-source multimodal models.
Llama 3.2 Vision is Meta’s first open-source multimodal Llama model series, released on September 25, 2024. Available in 11 B and 90 B parameter sizes, it merges advanced image understanding with a massive 128 K‑token text context. Optimized for vision reasoning, captioning, document QA, and visual math tasks, it outperforms many closed-source multimodal models.
Llama 3.2 Vision is Meta’s first open-source multimodal Llama model series, released on September 25, 2024. Available in 11 B and 90 B parameter sizes, it merges advanced image understanding with a massive 128 K‑token text context. Optimized for vision reasoning, captioning, document QA, and visual math tasks, it outperforms many closed-source multimodal models.
Pixtral Large is Mistral AI’s latest multimodal powerhouse, launched November 18, 2024. Built atop the 123B‑parameter Mistral Large 2, it features a 124B‑parameter multimodal decoder paired with a 1B‑parameter vision encoder, and supports a massive 128K‑token context window—enabling it to process up to 30 high-resolution images or ~300-page documents.
Pixtral Large is Mistral AI’s latest multimodal powerhouse, launched November 18, 2024. Built atop the 123B‑parameter Mistral Large 2, it features a 124B‑parameter multimodal decoder paired with a 1B‑parameter vision encoder, and supports a massive 128K‑token context window—enabling it to process up to 30 high-resolution images or ~300-page documents.
Pixtral Large is Mistral AI’s latest multimodal powerhouse, launched November 18, 2024. Built atop the 123B‑parameter Mistral Large 2, it features a 124B‑parameter multimodal decoder paired with a 1B‑parameter vision encoder, and supports a massive 128K‑token context window—enabling it to process up to 30 high-resolution images or ~300-page documents.
Qwen Chat is Alibaba Cloud’s conversational AI assistant built on the Qwen series (e.g., Qwen‑7B‑Chat, Qwen1.5‑7B‑Chat, Qwen‑VL, Qwen‑Audio, and Qwen2.5‑Omni). It supports text, vision, audio, and video understanding, plus image and document processing, web search integration, and image generation—all through a unified chat interface.
Qwen Chat is Alibaba Cloud’s conversational AI assistant built on the Qwen series (e.g., Qwen‑7B‑Chat, Qwen1.5‑7B‑Chat, Qwen‑VL, Qwen‑Audio, and Qwen2.5‑Omni). It supports text, vision, audio, and video understanding, plus image and document processing, web search integration, and image generation—all through a unified chat interface.
Qwen Chat is Alibaba Cloud’s conversational AI assistant built on the Qwen series (e.g., Qwen‑7B‑Chat, Qwen1.5‑7B‑Chat, Qwen‑VL, Qwen‑Audio, and Qwen2.5‑Omni). It supports text, vision, audio, and video understanding, plus image and document processing, web search integration, and image generation—all through a unified chat interface.
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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