On-premise AI constructionTry replacing it with your own business.
Estimate the capacity required to store weights based on model scale and accuracy.
You can check the processing results by changing the inputs and conditions below. Sample data and output can be saved.
On-premise AI construction
Estimate the capacity required to store weights based on model scale and accuracy.
01 / input sample
02 / Processing results
- Capacity (GB)
- 32
| model | Scale (B) | Accuracy (bit) | Weight capacity (GB) | Capacity comparison |
|---|---|---|---|---|
| MODEL-S | 7 | 4 | 3.5 | Weight only within capacity |
| MODEL-M | 14 | 8 | 14 | Weight only within capacity |
| MODEL-L | 32 | 16 | 64 | The weight alone exceeds the capacity |
Theoretical calculation of number of parameters x number of bits. KV cache, execution buffer, and speed need to be evaluated separately.
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From this sample to implementation
Check operation with sample
Check the processing content, required input, and output format. We will also organize unsupported formats and requirements.
Small-scale verification using in-house data
We evaluate accuracy, processing time, and correction man-hours using data that we have permission to use. We will agree in advance how to transfer confidential data.
Implement approval, collaboration, and operation
We decide on authority, person in charge of confirmation, existing system linkage, and maintenance conditions before implementing the system. Costs and delivery dates will be provided depending on the target data and requirements.
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