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Goliath 120B

A large LLM created by combining two fine-tuned Llama 70B models into one 120B model. Combines Xwin and Euryale. Credits to - [@chargoddard](https://huggingface.co/chargoddard) for developing the framework used to merge the model - [mergekit](https://github.com/cg123/mergekit). - [@Undi95](https://huggingface.co/Undi95) for helping with the merge ratios. #merge

Context Window

Input Price

$6.00/M tokens

Output Price

$8.00/M tokens

Modality

text->text

Pricing Breakdown

Cost per million tokens for input and output

Input$6.00/M tokens

Output$8.00/M tokens

Cost Example: Processing 10,000 input tokens and generating 1,000 output tokens would cost approximately $0.068000

Context Window Size

Maximum tokens the model can process in a single request

Context Window6K tokens

1% of 1M max

~5K

Words Equivalent

Pages of Text

~61

Code Functions

Best Use Cases

What this model excels at

General-purpose

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