Microsoft says its model matched DeepSeek-V4-Pro-Base on held-out code with 12x less compute
Overview
Mustafa Suleyman says Microsoft matched the pre-trained held-out code score of DeepSeek-V4-Pro-Base using 12x less training compute.
He attributes the result to compounding efficiency gains. The claim comes from a single post on X, and the source does not name the Microsoft model or publish the benchmark details.
Written by AI from the articles below · updated Oct 15, 12:38 PM ET
Check the sources:
Article timeline
The articles in this story. Times are ET.
Mustafa Suleyman@mustafasuleymanXMicrosoft matches DeepSeek-V4-Pro-Base code score with 12x less computeAIMustafa Suleyman says Microsoft matched DeepSeek-V4-Pro-Base's pre-trained score on held-out code using 12x less training compute. He attributes the result to compounding efficiency gains.

Heat trend
- Current comparable heat
- 9
- Peak comparable heat
- 10Oct 15, 1:00 PM ET
- Change in past 24 hours
- –
The trend compares only continuously observed participants, so its scope may be smaller than the current heat total. Hover or tap for hourly heat; use arrow keys with a keyboard.