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DeepSeek

DeepSeek R1

deepseek/deepseek-r1
Open weightsReasoning

The open reasoning model that reset expectations, deliberate chain-of-thought quality at open-weight prices.

Model overview

Context window

164K

tokens

Input price

—

quoted on request

Output price

—

quoted on request

Weekly volume

—

tokens / week

Open weights

Yes

self-hostable

Capabilities

4

of 11 tags

Description

DeepSeek R1 is a reasoning model from DeepSeek. Webparam does not stock this model yet and can source it on request — tell us what you need it for and we will come back with availability and a price. DeepSeek’s stated focus is open-weight frontier reasoning at disruptive economics. Its mean it can also be self-hosted under its licence.

Capabilities

Reasoning
Spends extra billed tokens thinking before it answers, trading latency and cost for accuracy.
Tool calling
Calls functions you define and returns their arguments as structured data, the basis of agents.
Streaming
Emits tokens as they are generated, so answers appear progressively rather than all at once.
Open weights
The parameters are published, so the model can be inspected, fine-tuned and self-hosted under its licence.

Strengths & weaknesses

Strengths

  • Open-weight reasoning near frontier quality
  • Transparent thinking traces
  • Dramatic cost advantage over closed reasoning models

Weaknesses

  • High output token consumption
  • Slower first token than language models

Pricing

Free
Pricing for DeepSeek R1, per 1M tokens
RatePriceUnit
Input$0.00per 1M tokens
Output— not charged—

Free at the point of use; fair-use rate limits apply to the free tier. Illustrative placeholder pricing.

Context window

164Ktokens

covers prompt and response together, so a long input leaves less room for the answer.

164K tokens against a peer range of 128K to 300K, median 182K. Compared across 8 reasoning models.

Supported features

Feature support for DeepSeek R1
FeatureSupport
Tool callingSupported
JSON modeNot supported
StreamingSupported
Vision inputNot supported
Audio inputNot supported
Long contextNot supported
Open weightsSupported
ReasoningSupported
Fine-tunableNot supported
BatchNot supported
CachingNot supported

Example use cases

  • Math and logic problems

    Open-weight reasoning near frontier quality

  • Analysis pipelines

    Transparent thinking traces

  • Verification passes

    Dramatic cost advantage over closed reasoning models

Related models

Comparison

DeepSeek R1 compared with DeepSeek V3.2 and Kimi K2 Thinking
AttributeDeepSeek R1DeepSeek V3.2Kimi K2 Thinking
Context window164K128K256K
Input price$0.00$0.00$0.00
Output price— not charged— not charged— not charged
Tool callingSupportedSupportedSupported
JSON modeNot supportedSupportedNot supported
Vision inputNot supportedNot supportedNot supported
Open weightsSupportedSupportedSupported
Prompt cachingNot supportedSupportedNot supported

Best value in each row is highlighted. Illustrative placeholder data.

Provider information

View DeepSeek →
DeepSeek3 models

DeepSeek · 深度求索 · Hangzhou, China · est. 2023

Spun out of a quantitative trading firm, DeepSeek built its reputation by releasing open-weight models that matched closed frontier quality at a fraction of the price. Its V-series redefined cost expectations for production LLMs, and its R-series brought open reasoning models into serious enterprise conversations.

Recent releases

    Documentation

    Frequently asked questions

    Input is billed at $0.00 per 1M tokens, and there is no separate output charge. Every figure on this page is an illustrative placeholder.