AI model comparison

deepseek-ai/DeepSeek-OCR vs deepseek-ai/DeepSeek-R1

Compare pricing, context limits, supported inputs and deployment options to choose a model for your workflow.

deepseek-ai/DeepSeek-OCR from deepseek-ai lists limited public specifications. deepseek-ai/DeepSeek-R1 from deepseek-ai lists 128K context, 32.77K maximum output. Compare the inputs, outputs and deployment options below to see which fits your workflow.

Side-by-sideCapabilities and practical differences
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deepseek-ai

deepseek-ai/DeepSeek-R1

deepseek-ai/DeepSeek-R1 is a source-linked Hugging Face repository assigned to Text generation. Its recorded task interface accepts text and produces text.

Context
128K
Max output
32.77K

Accepts

  • Text input

Produces

  • Text output

Specifications

Pricing, limits and capabilities

Specifications for deepseek-ai/DeepSeek-OCR and deepseek-ai/DeepSeek-R1. Higher limits and lower prices describe these figures only.
Specificationdeepseek-ai/DeepSeek-OCRdeepseek-ai/DeepSeek-R1
Providerdeepseek-aideepseek-ai
Listed pricing routedeepseek-aideepseek-ai
Model family——
Accepted inputsimage, texttext
Produced outputstexttext
Context window—128K
Max output—32.77K
Reasoning modeNot documentedDocumented
Tool callingNot documentedDocumented
Image inputDocumentedNot documented
Audio inputNot documentedNot documented
Structured outputNot documentedNot documented
LicenseNot documentedNot documented

Workload guidance

Which model should you choose?

The recorded figures alone do not establish a clear choice. deepseek-ai/DeepSeek-R1 offers downloadable weights; deepseek-ai/DeepSeek-OCR is listed as a proprietary model. Compare licence terms and operating costs before choosing a deployment. Test both on the same representative examples and judge the output against your acceptance criteria. Include tool failures, retries and the time to a completed task.

Documentation and model profiles

Explore each model’s features, API requirements and licence terms in the sources below.

Questions people ask

It brings together documented inputs and outputs, token limits, deployment terms and available pricing. When both models have source-linked, verified results on a shared benchmark, those results are shown with their individual sources. The comparison is a starting point for evaluating your own workload.

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