Overview

DeepSeek R1 is a reasoning model trained with reinforcement learning to produce chain-of-thought before answering. It matches or exceeds OpenAI o1 on several math and coding benchmarks and is available as a fully open-weight model.

History

DeepSeek R1 became available via the DeepSeek API on 2025-01-20.

Training & availability

Training data has a knowledge cutoff of 2024-07-31 — information about events after that date is unlikely to appear in the model's responses. Weights are publicly available under the MIT license, making this an open-weight model suitable for on-prem deployment and fine-tuning.

Capabilities

Context window: 128K tokens.
Max output: 32K tokens.
Input modalities: text.
Intelligence Index: 76.9/100.

Strongest categories: General knowledge (91), Math (89), Reasoning (72).

Recommended for: math, open-source, reasoning.

Limitations

The knowledge cutoff is 20 months old — this model will not know about recent events, releases, or API changes.
Text-only — cannot process images, audio, or video inputs.

Pricing

Input: $0.5500 per 1M tokens
Output: $2.1900 per 1M tokens

Use the cost calculator above to estimate monthly spend for your workload.

Quick start

Minimal example using the OpenRouter API. Copy, paste, replace the key.

from openai import OpenAI

client = OpenAI(
    base_url="https://openrouter.ai/api/v1",
    api_key="sk-or-...",
)
resp = client.chat.completions.create(
    model="deepseek/deepseek-r1",
    messages=[{"role": "user", "content": "Explain quantum computing in one sentence."}],
)
print(resp.choices[0].message.content)

Cost calculator

Estimate your monthly bill. Presets are typical workload sizes.

Input tokens / month5.0M

@ $0.55/1M

Output tokens / month2.0M

@ $2.19/1M

Input cost

$2.75

5.0M × $0.55/1M

Output cost

$4.38

2.0M × $2.19/1M

Total / month

$7.13

$85.56 / year

Providers & performance

2 providers

Multi-provider inference routes for this model — sorted by throughput. Latency is time-to-first-token; throughput is output tokens per second. Data from OpenRouter, measured over the last 30 minutes.

Provider	Throughput	Latency (TTFT)	Input $ / 1M	Output $ / 1M	Context	Quant	Supports
Azure	67tok/s	1.41s	$1.49	$5.94	164K	—	—
Novita	30tok/s	1.63s	$0.7	$2.5	64K	fp8	tools

Popularity

Signals from open-source communities — not a quality measure, but useful for gauging adoption among developers.

🤗

HuggingFace downloads

4.0M/ month

HuggingFace likes

13.3K

Benchmarks

Benchmark	Score	Source
AIME 2024Math	79.8% accuracy	Self-reported DeepSeek R1 paper
Aider PolyglotCoding	56.9% pass@2	Third-party Papers With Code
GPQA DiamondReasoning	71.5% accuracy	Self-reported DeepSeek R1 paper

Integrations & tooling support

Tool calling: Not supported
Structured outputs: Not supported

Price vs quality

Fair value

Mid-tier performance and pricing — standard choice.

Quality percentile: 68.1%
Effective price: $1.78/1M
Pricing breakdown: $0.55/1M in
$2.19/1M out

DeepSeek R1

Intelligence Index