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deepseek-ai/DeepSeek-R1

DeepInfra Inc./🇺🇸 US/chat

DeepSeek-R1 is an advanced, open-weights reasoning model by DeepSeek. Designed to compete with flagship reasoning models like OpenAI's o1, it focuses heavily on complex problem-solving in mathematics, coding, and science by "thinking" before it speaks, natively outputting a detailed, step-by-step chain of thought.More
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Which id to call

deepinfra/deepseek-ai/DeepSeek-R1

This exact deployment on DeepInfra Inc., with no routing and no failover. Send it as the model field.

Input /1M

$0.85

DeepInfra Inc.

Output /1M

$2.50

2.9x input

Context

64K

8K output

Added

Jan 2025

chat

Capabilities 1/8

VisionReasoningTool callingCachingWeb searchJSON schemaComputer useImage generation

Provider rates

What deepseek-ai/DeepSeek-R1 costs

Provider prices per 1M tokens, updated September 11, 2026.more

These are the upstream provider rates. Pay as you go adds 5%, or 0% if you bring your own keys, and there is no per-request fee. Prompt caching and routing change what you pay against these rates, not the rates themselves.

Input /1M

$0.85

Output /1M

$2.50

Cache write /1M

-

Cache read /1M

-

What a workload costs

100K input + 10K output
$0.11
1M input + 100K output
$1.10
10M input + 1M output
$11.00

At the rates above. This endpoint does not offer prompt caching, so repeated context is billed as new input every time.

OpenAI compatible

Call it in three lines

Change the base url, use your Requesty key, set the model to deepinfra/deepseek-ai/DeepSeek-R1. Existing OpenAI SDK code needs no other edit.

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from openai import OpenAI

client = OpenAI(
    api_key="YOUR_REQUESTY_API_KEY",
    base_url="https://router.requesty.ai/v1",
)

response = client.chat.completions.create(
    model="deepinfra/deepseek-ai/DeepSeek-R1",
    messages=[
        {"role": "user", "content": "Explain quantum computing in one paragraph."},
    ],
)

print(response.choices[0].message.content)

Reference

Specs and data terms

What the catalog reports for this deployment, and what the provider does with the traffic.

Context window64K tokens
Max output8K tokens
API typechat
AddedJan 2025
Model id
Data retentionNone
Used for trainingNo
Served from🇺🇸 US
Privacy policyDeepInfra Privacy Policy →

Released 2025-05-28

Benchmark scores

Benchmarks measure the model, not this endpoint, so they are the same wherever these weights are served.

GPQA Diamondreasoning
81.3%

Graduate-level physics, chemistry & biology questions designed to resist Googling.

Intelligence Indexreasoning
13.1%

Artificial Analysis Intelligence Index: a composite of multiple evaluations measuring overall model capability.

Scores from official model cards, Artificial Analysis and public leaderboards. They measure specific skills and do not capture every aspect of model quality, so test on your own workload.

Same provider

More from DeepInfra Inc.

Newest first, on the same provider and the same key.

glm-5.3-flash

1.0M ctx/$0.15/1M

glm-5.3

1.0M ctx/$1.20/1M

deepseek-v4-pro-0813

1.0M ctx/$1.30/1M

qwen3.8

262K ctx/$2.00/1M

deepseek-v4-flash-0731

1.0M ctx/$0.09/1M

deepseek-v4-flash-0731:flex

1.0M ctx/$0.07/1M

Reference

deepseek-ai/DeepSeek-R1 questions

How much does deepseek-ai/DeepSeek-R1 cost?

deepseek-ai/DeepSeek-R1 is priced at $0.85 per million input tokens and $2.50 per million output tokens when accessed via Requesty. Those are the upstream provider rates: pay as you go adds 5% on top, or 0% if you bring your own provider keys.

What is the context window of deepseek-ai/DeepSeek-R1?

deepseek-ai/DeepSeek-R1 has a context window of 64K tokens, with a maximum output of 8K tokens per response. That's roughly 85 words of input you can fit in a single prompt.

How does deepseek-ai/DeepSeek-R1 perform on benchmarks?

deepseek-ai/DeepSeek-R1 scores 84.9% on MMLU Pro, 81.3% on GPQA Diamond, 77.0% on LiveCodeBench. See the full benchmark chart above for results across MMLU Pro, GPQA Diamond, SWE-Bench Verified, HumanEval, MATH, AIME, MMMU, and LiveBench.

What can deepseek-ai/DeepSeek-R1 do?

deepseek-ai/DeepSeek-R1 supports tool calling. You can call it through any OpenAI-compatible client by pointing base_url to Requesty.

How do I use deepseek-ai/DeepSeek-R1 with the OpenAI SDK?

Install the OpenAI SDK, set base_url to "https://router.requesty.ai/v1", set your API key to your Requesty key, and set the model to "deepinfra/deepseek-ai/DeepSeek-R1". The Quickstart above shows Python, JavaScript and cURL snippets.

Can I run deepseek-ai/DeepSeek-R1 through Requesty?

Yes. deepseek-ai/DeepSeek-R1 runs through Requesty's OpenAI-compatible API, served from DeepInfra Inc.. You do not host the model yourself: point base_url at Requesty, set the model to "deepinfra/deepseek-ai/DeepSeek-R1", and requests are routed to the upstream provider with automatic failover. The same key gives you 600+ other models too.

Call deepseek-ai/DeepSeek-R1 through one endpoint

One key for this endpoint and 600+ other models. No markup on provider prices, automatic failover, caching built in.

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