DeepSeek: DeepSeek OCR
deepseek/deepseek-ocr
Access DeepSeek OCR from DeepSeek using the Puter.js AI API.
Get Started// npm install @heyputer/puter.js
import { puter } from '@heyputer/puter.js';
puter.ai.chat("Explain quantum computing in simple terms", {
model: "deepseek/deepseek-ocr"
}).then(response => {
document.body.innerHTML = response.message.content;
});
<html>
<body>
<script src="https://js.puter.com/v2/"></script>
<script>
puter.ai.chat("Explain quantum computing in simple terms", {
model: "deepseek/deepseek-ocr"
}).then(response => {
document.body.innerHTML = response.message.content;
});
</script>
</body>
</html>
Model Card
DeepSeek OCR is a vision model from DeepSeek, released in October 2025, built for optical character recognition and document parsing. It takes images as input through a chat-style API and returns text, including documents converted to markdown.
Its core idea is optical context compression, representing text as a small number of vision tokens and decoding them back to text. In DeepSeek's paper it reaches 97% decoding precision at compression ratios under 10x, and about 60% at 20x.
On OmniDocBench it outperforms GOT-OCR 2.0 while using only 100 vision tokens per page (versus 256), and beats MinerU 2.0 with fewer than 800 vision tokens (versus 6,000+).
It fits document-heavy workloads: parsing PDFs and scans, extracting text and tables, and generating training data for other models.
Context Window 8K
tokens
Max Output 8K
tokens
Input Cost $0.04
per million tokens
Output Cost $0.08
per million tokens
Input text, image
modalities
Release Date Oct 20, 2025
Model Playground
Try DeepSeek OCR instantly in your browser.
This playground uses the Puter.js AI API — no API keys or setup required.
More AI Models From DeepSeek
DeepSeek V4.1 Flash
DeepSeek V4.1 Flash is DeepSeek's fast, low-cost chat model, a 552B-parameter Mixture-of-Experts system using a new causal encoder-decoder design that activates 8B parameters while reading a prompt and 16B while generating a response. It succeeds DeepSeek V4 Flash, keeping a 1,000,000-token context window and adding a continuously adjustable reasoning effort setting (1-100). DeepSeek reports it beating the larger V4 Pro on performance, cost, speed, and total runtime. In DeepSeek's own tests it scored 90.6 on Terminal-Bench 2.1, ahead of Claude Opus 5 (89.1) and GPT-5.6 Sol (88.8), 88.1 on CyberGym versus 84.5 for GPT-5.6 Sol and GLM 5.3, and 74.2 on DeepSWE v1.1 versus 74.0 for Claude Opus 5. It supports tool calling, and DeepSeek says its KV cache footprint is about a quarter of V4 Flash's for cheaper long-context serving. At $0.08/M input and $0.34/M output tokens, it fits high-throughput coding agents, tool-calling pipelines, and long-context workloads.
ChatDeepSeek V4 Flash Vision Experimental
DeepSeek V4 Flash Vision Experimental is an experimental multimodal version of DeepSeek's V4 Flash model, released by DeepSeek in August 2026. It is a sparse Mixture-of-Experts model with 284B total parameters and 13B activated per token, and it accepts images (JPEG, PNG, GIF, WebP) alongside text through the same API used for V4 Flash, at the same per-token pricing. DeepSeek reports that it matches V4 Flash on text tasks including agentic reasoning and world knowledge, while adding image understanding for document and chart parsing, visual question answering, and agent workflows that interleave text and images. On multimodal agent benchmarks, DeepSeek's own numbers show gains over the text-only V4 Flash, with Terminal Bench 2.1 rising from 82.7 to 83.9, ApexBench from 26.2 to 36.5, and Agents' Last Exam from 25.2 to 27.3, approaching Anthropic's Opus 4.8 (85.0 on Terminal Bench 2.1). On NL2Repo it trails Opus 4.8, 57.7 versus 69.7.
ChatDeepSeek V4 Pro 0813
DeepSeek V4 Pro 0813 is the production release of DeepSeek's V4 Pro flagship model, a 1.6-trillion-parameter Mixture-of-Experts model with 49B parameters active per token, marking the end of a four-month preview. It keeps the preview's 1,048,576-token context window, 384,000-token max output, and three reasoning modes (non-thinking, high, and max effort). DeepSeek reports large gains over the preview build: Terminal Bench 2.1 rose from 72.1 to 87.9 and DeepSWE from 12.8 to 62.7. At max reasoning effort it scores 80.6% on SWE-bench Verified, matching Gemini 3.1 Pro, along with 90.1% on GPQA Diamond, 87.5% on MMLU-Pro, and a Codeforces rating of 3,206, ahead of GPT-5.4's 3,168. Priced at $0.38 per million input tokens and $1.14 per million output tokens. Pinning the 0813 route locks an application to this exact checkpoint rather than the rolling deepseek-v4-pro alias, useful for agentic coding and long-context reasoning tasks.
Frequently Asked Questions
You can access DeepSeek OCR by DeepSeek through Puter.js AI API. Include the library in your web app or Node.js project and start making calls with just a few lines of JavaScript — no backend and no configuration required. You can also use it with Python or cURL via Puter's OpenAI-compatible API.
DeepSeek OCR is free to integrate using the Puter.js AI API. With the User-Pays Model, you can add AI to your app for $0, since users cover their own AI usage through their Puter account.
| Price per 1M tokens | |
|---|---|
| Input | $0.04 |
| Output | $0.08 |
DeepSeek OCR was created by DeepSeek and released on Oct 20, 2025.
DeepSeek OCR supports a context window of 8K tokens. For reference, that is roughly equivalent to 16 pages of text.
DeepSeek OCR can generate up to 8K tokens in a single response.
DeepSeek OCR accepts the following input types: text, image. It produces: text.
Yes — the DeepSeek OCR API works with any JavaScript framework, Node.js, or plain HTML through Puter.js. Just include the library and start building. See the documentation for more details.
Add DeepSeek OCR to your app for free
Developers can integrate DeepSeek OCR for free using the Puter.js AI API.
With the User-Pays Model, each user covers their own AI usage instead of the developer.