Token Economics Calculator
We created this Tokenomics calculator to help companies deploying LLMs understand the costs and energy involved, and compare different hardware and models.
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Model Selection
Included models
- Llama 3 70B - 1k_1k
- Llama 3 70B - MLPerf®
- Llama 3 405B - 1k_1k
- Llama 3 405B - MLPerf®
Parameters (millions)
Quantization (model parameter precision)
- 1 byte - INT8, FP8...
- 2 bytes - FP16, BF16...
Quantization (math/KV-cache precision)
- 1 byte - INT8, FP8...
- 2 bytes - FP16, BF16...
Hardware Selection
Reference Hardware
- AMD MI325X
- Cerebras CS-3d-Matrix
- Corsair
- Furiosa RNG
- GroqRack
- Nvidia L40S
- Nvidia DGX H200
- Nvidia NVL72
- Nvidia RTX Pro 6000
- Rebellions REBEL-Quad
- SambaNova SN40L
- Tenstorrent Galaxy Rack
Memory per Chip (GB)
Chips per Rack
Rack Power (kW)
Rack Cost (USD)
Concurrent Users (est)
Operating Parameters
Depreciation (years)
Weighted Average Cost of Capital (%)
Colocation Cost ($/kW per month)
Energy Cost ($/kWh)
Learn about US energy cost
Learn about EU energy cost
Colo/Datacenter PUE
Expected System Utilization (%)
Default Operating Parameters
Results
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0 Rack Comparison
Total Tokens per Second
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Cost per million total tokens
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Total Tokens per USD
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Total Tokens per kWh
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Total Expenses per Month
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Total Rack Cost (USD)
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0 Racks Needed
Reference Hardware Cost Breakdown
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Disclaimer
The GenAI Token Economics Calculator was developed to help users consider how variation in certain parameters may impact the performance, costs, and energy for deploying LLMs using different hardware and models.
Tensordyne has attempted to provide estimates for a limited number of substantially similar scenarios by compiling information from publicly available sources including MLCommons and normalizing the data. Where public information is limited or missing for certain parameters, Tensordyne has included its best estimates, e.g. concurrent users supported, quantization, etc.
This calculator is for instructional purposes only. The calculator makes many assumptions and relies on publicly available data that may be incorrect or outdated, which may introduce significant error into results. Tensordyne does not make factual representations about any of the calculator’s inputs or outputs. Users are encouraged to observe the relative sensitivity of outputs to changes in inputs.