Question 1

What is the cost of DeepSeek-R1-0528 by Nebius Token Factory?

Accepted Answer

DeepSeek-R1-0528 by Nebius Token Factory costs $0.80 per 1M input tokens and $2.40 per 1M output tokens. Cached reads cost $0.08 per 1M tokens. Cache writes cost $1.00 per 1M tokens.

Question 2

What is the context window of DeepSeek-R1-0528 by Nebius Token Factory?

Accepted Answer

DeepSeek-R1-0528 by Nebius Token Factory has a context window of 128K tokens. It supports up to 120K input tokens and can generate up to 33K output tokens.

Question 3

What are the capabilities of DeepSeek-R1-0528 by Nebius Token Factory?

Accepted Answer

DeepSeek-R1-0528 by Nebius Token Factory supports advanced reasoning, tool calling/function calling, structured output, adjustable temperature. It has open weights.

Question 4

What input and output types does DeepSeek-R1-0528 support?

Accepted Answer

DeepSeek-R1-0528 by Nebius Token Factory accepts text as input and can generate text as output.

Question 5

Does DeepSeek-R1-0528 by Nebius Token Factory support reasoning?

Accepted Answer

Yes, DeepSeek-R1-0528 by Nebius Token Factory supports advanced reasoning capabilities. Reasoning output costs $2.40 per 1M tokens.

Question 6

Is DeepSeek-R1-0528 by Nebius Token Factory open source?

Accepted Answer

Yes, DeepSeek-R1-0528 by Nebius Token Factory has open weights, meaning the model weights are publicly available for download and self-hosting.

Question 7

Does DeepSeek-R1-0528 support function calling?

Accepted Answer

Yes, DeepSeek-R1-0528 by Nebius Token Factory supports tool calling (also known as function calling), allowing it to interact with external tools and APIs during conversations.

Question 8

What is the knowledge cutoff date for DeepSeek-R1-0528?

Accepted Answer

DeepSeek-R1-0528 by Nebius Token Factory has a knowledge cutoff date of 2025-11. This means the model was trained on data available up until that date.

DeepSeek-R1-0528 API

Input Modalities

Output Modalities

Standard (per 1M tokens)

Reasoning (per 1M tokens)

Caching (per 1M tokens)