DeepSeek-R1
DeepSeek-R1 is an AI model published by DeepSeek-AI, released on 2025-01-20, for Reasoning model, with 671B parameters, and 128K context length, requiring about 134GB storage, with a 1500.00 score on Creative Writing.
Data sourced primarily from official releases (GitHub, Hugging Face, papers), then benchmark leaderboards, then third-party evaluators. Learn about our data methodology
Model basics
Open source & experience
Official resources
API details
| Type | Condition | Input | Output |
|---|---|---|---|
| Text | - | $0.550/ 1M | $2.19/ 1M |
| Type | TTL | Write | Read |
|---|---|---|---|
| Text | - | $0.550/ 1M | $0.140/ 1M |
| Text | - | $0.550/ 1M Cache = write | — |
| Text | - | — | $0.140/ 1M Cache = hit |
“—” means the modality is not billed in that direction, or the vendor has not published a price for it.
Benchmark Results
DeepSeek-R1 currently shows benchmark results led by MMLU (8 / 124, score 90.80), MATH-500 (13 / 45, score 97.30), MMLU Pro (39 / 134, score 84). This page also consolidates core specs, context limits, and API pricing so you can evaluate the model from benchmark results and deployment constraints together.
General Knowledge
3 evaluationsCoding and Software Engineer
3 evaluationsMath and Reasoning
4 evaluationsWriting and Creative Capabilities
1 evaluationsAgent Level Benchmark
3 evaluationsPublisher
Model Overview
DeepSeek-R1 is an AI model published by DeepSeek-AI, released on 2025-01-20, for Reasoning model, with 671B parameters, and 128K context length, requiring about 134GB storage, with a 1500.00 score on Creative Writing.
DataLearner on WeChat
Follow DataLearner on WeChat for AI model updates and research notes.
