Show HN: Comparisons – Gemini-1-5-vs-ChatGPT-4o
Gemini 1.5 Pro and ChatGPT-4o are competing AI models, with Gemini excelling in math and coding, while ChatGPT-4o is superior in language comprehension, despite higher output costs.
Read original article
Gemini 1.5 Pro and ChatGPT-4o are two advanced AI models competing in the natural language processing space. Gemini 1.5 Pro has recently excelled in LLM leaderboards, while ChatGPT-4o remains widely recognized. The two models differ in architecture, performance, and specific use cases. Gemini 1.5 Pro features a larger context window of 2 million tokens compared to ChatGPT-4o's 128, allowing it to manage more complex inputs. However, ChatGPT-4o has a higher output capacity of 16,000 tokens versus Gemini's 8,000. Benchmark tests reveal that while Gemini performs better in math-related tasks, ChatGPT-4o outperforms in language comprehension and coding tasks. Practical tests showed both models providing accurate responses to various prompts, but ChatGPT-4o consistently excelled in language comprehension, while Gemini 1.5 Pro was more effective in coding challenges. Despite their strengths, ChatGPT-4o is more expensive in terms of output pricing. Overall, Gemini 1.5 Pro is recommended for coding tasks, while ChatGPT-4o is preferred for language comprehension.
- Gemini 1.5 Pro has a larger input context window than ChatGPT-4o.
- ChatGPT-4o excels in language comprehension and coding tasks.
- Gemini 1.5 Pro is more effective in math-related tasks.
- ChatGPT-4o is more expensive in output pricing compared to Gemini.
- Both models are capable but cater to different strengths and use cases.
Related
Gemini's data-analyzing abilities aren't as good as Google claims
Google's Gemini 1.5 Pro and 1.5 Flash AI models face scrutiny for poor data analysis performance, struggling with large datasets and complex tasks. Research questions Google's marketing claims, highlighting the need for improved model evaluation.
Gemini Pro 1.5 experimental "version 0801" available for early testing
Google DeepMind's Gemini family of AI models, particularly Gemini 1.5 Pro, excels in multimodal understanding and complex tasks, featuring a two million token context window and improved performance in various benchmarks.
Google Gemini 1.5 Pro leaps ahead in AI race, challenging GPT-4o
Google has launched Gemini 1.5 Pro, an advanced AI model excelling in multilingual tasks and coding, now available for testing. It raises concerns about AI safety and ethical use.
Gemma explained: An overview of Gemma model family architectures
Gemma is a family of lightweight models for text and code generation, utilizing transformer decoders and advanced techniques. Key models include CodeGemma, optimized for coding tasks, and Gemma 2, promising improved performance.
Gemma explained: What's new in Gemma 2
Gemma 2 introduces open models in 2B, 9B, and 27B sizes, enhancing conversational AI with innovations like GQA and logit soft-capping, while future developments will explore the RecurrentGemma model.
3 commentsit's basically like Apple at this point, they don't have to be the best
Related
Gemini's data-analyzing abilities aren't as good as Google claims
Google's Gemini 1.5 Pro and 1.5 Flash AI models face scrutiny for poor data analysis performance, struggling with large datasets and complex tasks. Research questions Google's marketing claims, highlighting the need for improved model evaluation.
Gemini Pro 1.5 experimental "version 0801" available for early testing
Google DeepMind's Gemini family of AI models, particularly Gemini 1.5 Pro, excels in multimodal understanding and complex tasks, featuring a two million token context window and improved performance in various benchmarks.
Google Gemini 1.5 Pro leaps ahead in AI race, challenging GPT-4o
Google has launched Gemini 1.5 Pro, an advanced AI model excelling in multilingual tasks and coding, now available for testing. It raises concerns about AI safety and ethical use.
Gemma explained: An overview of Gemma model family architectures
Gemma is a family of lightweight models for text and code generation, utilizing transformer decoders and advanced techniques. Key models include CodeGemma, optimized for coding tasks, and Gemma 2, promising improved performance.
Gemma explained: What's new in Gemma 2
Gemma 2 introduces open models in 2B, 9B, and 27B sizes, enhancing conversational AI with innovations like GQA and logit soft-capping, while future developments will explore the RecurrentGemma model.