Grok-1 vs PaLM 2
Overview
🔥 Trending in Text & Language Models on StackShare
Detailed Comparison
It is a next-generation large language model that excels at advanced reasoning tasks, including code and math, classification, question answering, translation, multilingual proficiency, and natural language generation. | It is the base model weights and network architecture of Grok-1, the large language model. Grok-1 is a 314 billion parameter Mixture-of-Experts model trained from scratch by xAI. |
Use of compute-optimal scaling;
Excels at advanced reasoning tasks;
Translation, multilingual proficiency, and natural language generation | 314B parameters;
Mixture of 8 Experts (MoE);
Trained from scratch by xAI |
Statistics | |
GitHub Stars - | GitHub Stars 50.6K |
GitHub Forks - | GitHub Forks 8.4K |
Stacks 1 | Stacks 7 |
Followers 1 | Followers 9 |
Votes 0 | Votes 2 |
Integrations | |
| No integrations available | |
What are some alternatives to PaLM 2, Grok-1?
Google Gemini
It is Google’s largest and most capable AI model. It is built to be multimodal, it can generalize, understand, operate across, and combine different types of info — like text, images, audio, video, and code.
LLaMA
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Whisper
It is a general-purpose speech recognition model. It is trained on a large dataset of diverse audio and is also a multi-task model that can perform multilingual speech recognition as well as speech translation and language identification.
Grok 4
Try Grok 4 on GPT Proto. Access xAI’s most advanced 1.7T LLM with 130K context, multimodal support, and real-time data integration for dynamic analysis.
OpenAI
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Claude
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GPT-4 by OpenAI
It is a large multimodal model (accepting text inputs and emitting text outputs today, with image inputs coming in the future) that can solve difficult problems with greater accuracy than any of our previous models, thanks to its broader general knowledge and advanced reasoning capabilities.
Cohere.com
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Mistral 7B
It is a small, yet powerful model adaptable to many use cases. It is better than Llama 2 13B on all benchmarks, has natural coding abilities, and 8k sequence length. We made it easy to deploy on any cloud.
DeepSeek Coder
It is composed of a series of code language models, each trained from scratch on 2T tokens, with a composition of 87% code and 13% natural language. There are various sizes of the code model, ranging from 1B to 33B versions.
