Price for model Input: $0.0006064, Output: $0.0024145 per 1000 tokens until February 15. After February 15 we will increase the price.
DeepSeek R1 is a cutting-edge reasoning model developed by DeepSeek AI, designed to excel in complex problem-solving, mathematical reasoning, and programming assistance. Leveraging a Mixture-of-Experts (MoE) architecture, the model activates only a subset of its parameters for each token processed, allowing for efficient computation while maintaining high performance across various tasks.
DeepSeek R1 is intended for software developers, data scientists, and researchers who require advanced reasoning capabilities in their applications. It is particularly useful for tasks involving mathematical computations, coding challenges, and logical problem-solving.
The model primarily supports English but can accommodate multiple languages depending on user requirements.
DeepSeek R1 employs a Mixture-of-Experts (MoE) architecture that allows it to activate only a portion of its parameters during each forward pass. This design choice significantly reduces computational costs while maintaining high performance levels.
The model was trained on a large dataset consisting of diverse programming languages and mathematical problems.
The model is available on the AI/ML API platform as "DeepSeek R1 .
Detailed API Documentation is available here.
DeepSeek AI emphasizes ethical considerations in AI development by promoting transparency regarding the model's capabilities and limitations. The organization encourages responsible usage to prevent misuse or harmful applications of generated content.
DeepSeek R1 is available under an open-source MIT license that allows both research and commercial usage rights while ensuring compliance with ethical standards regarding creator rights
Get DeepSeek R1 API here.
Measured on the AI/ML API gateway across live traffic. Figures are medians unless stated. Last updated 2026-10-12.
import requests r = requests.post( "https://api.aimlapi.com/v1/chat/completions", headers={"Authorization": "Bearer " + AIMLAPI_KEY}, json={ "model": "deepseek/deepseek-reasoner", "messages": [ { "role": "user", "content": "Hello!" } ] }, ) print(r.json())
const r = await fetch("https://api.aimlapi.com/v1/chat/completions", { method: "POST", headers: { Authorization: `Bearer ${process.env.AIMLAPI_KEY}`, "Content-Type": "application/json", }, body: JSON.stringify({ "model": "deepseek/deepseek-reasoner", "messages": [ { "role": "user", "content": "Hello!" } ] }), }); console.log(await r.json());
curl -X POST https://api.aimlapi.com/v1/chat/completions \ -H "Authorization: Bearer $AIMLAPI_KEY" \ -H "Content-Type: application/json" \ -d '{"model":"deepseek/deepseek-reasoner","messages":[{"role":"user","content":"Hello!"}]}'
OpenAI-compatible — swap the base URL and it works with your existing SDK.
| Type | Price |
|---|---|
| Input | |
| Output | |
| Cached input |
| Benchmark | Score | What it measures | Source | Retrieved |
|---|---|---|---|---|
| Humanity's Last Exam | 17.7% | Expert-level questions across many domains | Source | July 12, 2026 |
| SWE-bench Verified | 57.6% | Resolving verified real GitHub issues | Source | July 12, 2026 |
| LiveCodeBench | 73.3% | Contamination-free competitive programming problems | Source | July 12, 2026 |
| GPQA Diamond | 81.0% | Google-proof graduate science questions (hardest subset) | Source | July 12, 2026 |
| AIME 2025 | 87.5% | Competition mathematics (AIME), 2025 | Source | July 12, 2026 |
| Intelligence | 13.1 | Composite score across standardised reasoning, knowledge and problem-solving evaluations, measured independently by Artificial Analysis | Source | September 12, 2026 |
| Math | 76 | Composite score across standardised mathematics evaluations, measured independently by Artificial Analysis | Source | September 12, 2026 |
| Model | Input | Output | Context | Best for |
|---|---|---|---|---|
DeepSeek-R1 This page | Chat + assistants | |||
| Reasoning + agents | ||||
| Balanced coding + agents | ||||
| Long-context, multimodal & agentic workflows | ||||
| Reasoning + agents |
DeepSeek-R1 has a 128,000 tokens context window and can return up to 127,000 tokens.
DeepSeek-R1 takes text as input and returns text.
Use deepseek/deepseek-reasoner as the model id. Requests go to https://api.aimlapi.com/v1/chat/completions.
DeepSeek-R1 became available on August 28, 2025.
DeepSeek-R1 is priced at input $0.39 / 1M tokens, output $1.56 / 1M tokens, cached input $0.0078 / 1M tokens.
Yes, DeepSeek-R1 can stream responses as they are generated.
DeepSeek-R1 was built by DeepSeek.
