Perceptron: Perceptron Mk1

perceptron/perceptron-mk1

Access Perceptron Mk1 from Perceptron using 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: "perceptron/perceptron-mk1"
}).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: "perceptron/perceptron-mk1"
        }).then(response => {
            document.body.innerHTML = response.message.content;
        });
    </script>
</body>
</html>

# pip install openai
from openai import OpenAI

client = OpenAI(
    base_url="https://api.puter.com/puterai/openai/v1/",
    api_key="YOUR_PUTER_AUTH_TOKEN",
)

response = client.chat.completions.create(
    model="perceptron/perceptron-mk1",
    messages=[
        {"role": "user", "content": "Explain quantum computing in simple terms"}
    ],
)

print(response.choices[0].message.content)

curl https://api.puter.com/puterai/openai/v1/chat/completions \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer YOUR_PUTER_AUTH_TOKEN" \
  -d '{
    "model": "perceptron/perceptron-mk1",
    "messages": [
      {"role": "user", "content": "Explain quantum computing in simple terms"}
    ]
  }'

Model Card

Perceptron Mk1 is a vision-language model from Perceptron AI designed for video and embodied reasoning, capable of processing native video at up to 2 frames per second within its 32K context window.

It excels at video QA, video summarization, event detection, open-vocabulary object detection and counting, OCR on real-world documents, hand pose estimation, and point-by-example grounding from multimodal prompts. On spatial reasoning benchmarks, Mk1 scores 85.1 on EmbSpatialBench and 72.4 on RefSpatialBench, outperforming frontier models. On VSI-Bench it reaches 88.5, the highest recorded score among compared models.

At $0.15 per million input tokens, Mk1 is priced 80–90% below comparable frontier vision-language models, making it a strong choice for developers building video analysis, robotics data curation, or multimodal pipelines at scale.

Context Window 33K

tokens

Max Output 8K

tokens

Input Cost $0.15

per million tokens

Output Cost $1.5

per million tokens

Release Date May 12, 2026

 

Model Playground

Try Perceptron Mk1 instantly in your browser.
This playground uses the Puter.js AI API — no API keys or setup required.

Chat perceptron/perceptron-mk1
Chat with Perceptron Mk1
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Frequently Asked Questions

How do I use Perceptron Mk1?

You can access Perceptron Mk1 by Perceptron 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.

Is Perceptron Mk1 free?

Yes, it is free if you're using it through Puter.js. With the User-Pays Model, you can add Perceptron Mk1 to your app at no cost — your users pay for their own AI usage directly, making it completely free for you as a developer.

What is the pricing for Perceptron Mk1?
Perceptron Mk1 costs $0.15 per 1M input tokens and $1.5 per 1M output tokens.
Price per 1M tokens
Input$0.15
Output$1.5
Who created Perceptron Mk1?

Perceptron Mk1 was created by Perceptron and released on May 12, 2026.

What is the context window of Perceptron Mk1?

Perceptron Mk1 supports a context window of 33K tokens. For reference, that is roughly equivalent to 66 pages of text.

What is the max output length of Perceptron Mk1?

Perceptron Mk1 can generate up to 8K tokens in a single response.

Does it work with React / Vue / Vanilla JS / Node / etc.?

Yes — the Perceptron Mk1 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.

Get started with Puter.js

Add Perceptron Mk1 to your app without worrying about API keys or setup.

Read the Docs View Tutorials