R1 0528

About R1 0528

DeepSeek R1 is a revolutionary reasoning model that matches OpenAI o1's performance at a fraction of the cost, democratizing access to advanced AI reasoning capabilities. Released in January 2025, R1 demonstrates that sophisticated reasoning doesn't require proprietary architectures or massive budgets. The model excels at mathematics, coding, and scientific reasoning, achieving competitive scores on benchmarks like AIME and Codeforces that previously seemed exclusive to frontier labs. DeepSeek R1 uses a novel training approach that develops reasoning capabilities through reinforcement learning, producing transparent chain-of-thought outputs that show its problem-solving process. With open weights available for self-hosting, R1 offers unprecedented flexibility for organizations requiring on-premise deployment of reasoning AI. The model supports a 128K context window and integrates well with existing DeepSeek infrastructure. For developers building applications requiring genuine reasoning—not just pattern matching—DeepSeek R1 provides a cost-effective path to capabilities that were recently considered cutting-edge. Its release marked a significant moment in AI accessibility, proving that advanced reasoning can be achieved outside the largest AI labs.

Model Specifications

💰 Real-World Cost Examples

Estimated monthly costs for common use cases

DeepSeek Model Lineup

Compare all models from DeepSeek to find the best fit

Similar Models from Other Providers

Cross-brand alternatives with similar capabilities

MiniMax M1

MiniMax

Input: $0.40

Output: $2.20

Context: 1.0M

Kimi K2.5

Moonshot AI

Input: $0.45

Output: $2.20

Context: 262k

Cogito v2.1 671B

Other

Input: $1.25

Output: $1.25

Context: 128k

Kimi K2 Thinking

Moonshot AI

Input: $0.47

Output: $2.00

Context: 131k

💡 Cheaper Alternatives

Same Brand (DeepSeek)

Cross Brand

🚀 Quick Start

Get started with R1 0528 API

from openai import OpenAI

client = OpenAI(
    base_url="https://api.provider.com/v1",
    api_key="YOUR_API_KEY"
)

response = client.chat.completions.create(
    model="deepseek/deepseek-r1-0528",
    messages=[
        {"role": "user", "content": "Hello!"}
    ]
)
print(response.choices[0].message.content)

Continue Your Decision