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GPT-4o is a multimodal language model developed by OpenAI, released in May 2024. The "o" stands for "omni," reflecting its ability to accept any combination of text, audio, and image as input and generate any combination of those same modalities as output. It has a 128,000-token context window and a training data cutoff of October 2023.

Claude 3 Haiku is a text generation model developed by Anthropic, positioned as the fastest and most affordable model in the Claude 3 family. It features a 200,000-token context window and vision capabilities, making it suitable for tasks that require processing large documents or analyzing images alongside text. The model's training data has a cutoff of August 2023.

GPT-4 is a large language model developed by OpenAI and released in March 2023 as part of the Generative Pre-trained Transformer series. It accepts text input and produces text output, with a context window of 8,192 tokens, and its training data has a knowledge cutoff of April 2023. GPT-4 was designed to improve on earlier GPT models in areas such as instruction following, contextual understanding, and factual accuracy across a wide range of topics.

Speedy, cost-effective multimodal model for high-volume applications without compromising quality.

Compare Gemini 1.0 Pro Deprecated and Gemini 1.5 Flash Deprecated across pricing, context window, capabilities, benchmarks, and API access to choose the better fit for long-context workloads versus general-purpose AI workloads.

Compare Gemini 1.0 Pro Vision Deprecated and Gemini 1.5 Flash Deprecated across pricing, context window, capabilities, benchmarks, and API access to choose the better fit for general-purpose AI workloads versus general-purpose AI workloads.

Compare Gemini 1.5 Flash Vision Deprecated and Gemini 1.5 Flash Deprecated across pricing, context window, capabilities, benchmarks, and API access to choose the better fit for general-purpose AI workloads versus general-purpose AI workloads.

Compare Gemini 1.5 Pro Deprecated and Gemini 1.5 Flash Deprecated across pricing, context window, capabilities, benchmarks, and API access to choose the better fit for general-purpose AI workloads versus general-purpose AI workloads.