DeepSeek R1

deepseek-r1

DeepSeek R1 is the reasoning-focused DeepSeek model, widely referenced for open reasoning traces and strong math, logic, and coding performance. It shares the large MoE profile of the V3 generation but is trained and presented around deliberate reasoning rather than general chat alone. It is best described for tasks where the answer requires decomposition, verification, or step-by-step problem solving.

Total Context

128Ktokens

Max Output

32.8Ktokens

Released

Jan 20, 2025

Modalities

DeepSeek R1 Price

Input PriceOutput PriceCache Read
$0.5714/M$2.2857/M$0.2286/M

DeepSeek R1 API

POST /v1/chat/completions

DeepSeek R1 Benchmark

DeepSeek R1 (Jan '25)

12.6

/100

Artificial Analysis Intelligence Index

Artificial Analysis broad capability aggregate

Index score

15.9

/100

Artificial Analysis Coding Index

Artificial Analysis software task aggregate

Index score

68

/100

Artificial Analysis Math Index

Artificial Analysis math reasoning aggregate

Index score

Knowledge & Reasoning

MMLU-Pro

Advanced multi-task knowledge

84.4%

GPQA

Advanced science problem solving

70.8%

HLE

Broad expert-level exam set

9.3%

Coding & Engineering

LiveCodeBench

Live coding problems

61.7%

SciCode

Scientific coding challenges

35.7%

Terminal-Bench Hard

Hard terminal task execution

6.1%

Math

MATH-500

Advanced math problem solving

96.6%

AIME

Competition math problems

68.3%

AIME 2025

Competition math problems

68%

Instruction Following & Agent Tasks

IFBench

Prompt constraint adherence

39.0%

AA-LCR

Long-context reasoning

52.3%

τ²-Bench

Agent workflow tasks

11.4%

Metrics sourced from Artificial Analysis

Media and Discussions

Selected public videos and posts related to this model.

X (Twitter)

View post on X
View post on X
View post on X

Reddit

YouTube

Watch on YouTube
Watch on YouTube
Watch on YouTube

DeepSeek R1 FAQ

DeepSeek R1: capabilities, use cases, limits, and TokenHub guidance.

What is DeepSeek R1 built for?+

DeepSeek R1 is a DeepSeek model for open-weight, reasoning-intensive problem solving.

When is DeepSeek R1 most useful?+

Best for mathematical reasoning, code reasoning and scientific reasoning, especially when deep reasoning is the priority.

What distinguishes DeepSeek R1?+

Key strength: reasoning-focused post-training with openly released weights.

What should I watch for?+

Deep reasoning can increase response time and token use. For the latest capabilities matter, consider DeepSeek V4 Pro.

How do I check availability?+

Use TokenHub's exact ID; hosted behavior may differ from self-hosting.