DeepSeek-R1 (May 2025)

Training compute

4×10²⁴ FLOP

Parameters

671B

Published

May 28, 2025

DeepSeek-R1 (May 2025) is an AI model developed by DeepSeek (China), first published in May 2025. It works in the language domain, on tasks such as language modeling/generation, code generation, quantitative reasoning and question answering.

Training it took an estimated 4×10²⁴ FLOP of compute (estimation method: operation counting). The model has 671,000,000,000 parameters. It was trained on roughly 14.8T datapoints. The compute alone is estimated at $7M in 2023 dollars.

Access: Open weights (unrestricted). Its weights are openly available. It is built on top of DeepSeek-V3. Epoch AI rates the confidence of this record as confident.

Full record

Organization: DeepSeek
Country of organization: China
Domain: Language
Task: Language modeling/generation, Code generation, Quantitative reasoning, Question answering
Training compute: 4×10²⁴ FLOP
Compute estimation method: Operation counting
Parameters: 671,000,000,000
Dataset size: 14.8T
Training cost (2023 USD): $7M
Numerical format: FP8
Model accessibility: Open weights (unrestricted)
Open weights: Yes
Base model: DeepSeek-V3
Epoch confidence: Confident

Benchmark results

01

Epoch Capabilities Index

ECI Score

142