Background
DeepSeek-V3 is a large language model that DeepSeek claims was trained using 2.788 million H800 GPU hours, costing approximately $5.576 million in direct training costs. This is notably efficient compared to similar models like Llama 3.1 405B, which required over 11 times more GPU hours.
Resolution Criteria
This market will resolve YES if:
A team openly publishes reproducible or otherwise credible replication of DeepSeek-V3 with comparable performance
The compute cost is less than $10 million
The market will resolve NO if:
No successful replication is achieved by the resolution date
A replication is achieved but costs $10 million or more
A replication is achieved but there are no credible reports of the costs
Considerations
The cost of GPU compute will be calculated using December 2024 prices.
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@mods please resolve this market to "no", as an open-source reproduction of DeepSeek v3 did not happen in 2025.
There was a model (Kimi k2) which used the same architecture, but they changed it a touch for it did not strictly match DeepSeek v3
The reported cost for training Kimi k2 of 4.6 million is also unverified
https://www.yicaiglobal.com/news/kimi-k2-thinkings-reported-usd46-million-training-cost-isnt-official-moonshot-ceo-says
