perceptron-mk1-5
Perceptron Mk1.5 is Perceptron’s embodied reasoning model for physical agents. It takes text, image, video and audio input and can answer with structured annotations such as points, boxes, polygons and tracks.
Pricing: Input 30 credits / 1M tokens (≈ $0.15), Output 300 credits / 1M tokens (≈ $1.50).
Prices updated
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Perceptron Mk1.5 API on ModelFold
Perceptron Mk1.5 is Perceptron’s embodied reasoning model for physical agents. It takes text, image, video and audio input and can answer with structured annotations such as points, boxes, polygons and tracks. Try Perceptron Mk1.5 in the ModelFold Playground, then call it from your own code through an OpenAI-compatible chat completions API.
What Is the Perceptron Mk1.5 API
Perceptron Mk1.5 at a glance
Perceptron Mk1.5 is a chat model from Perceptron. It accepts text, images, video and audio as input and returns text, with a context window of up to 37K tokens.
Use it without hosting anything
On ModelFold you call Perceptron Mk1.5 with a single API key — no model weights to download and no inference servers to run. The same key also works for the other chat, image, video and audio models on ModelFold.
Core Capabilities of Perceptron Mk1.5
Up to 37K tokens of context
Keep long conversations, large documents and sizeable code in a single request, so the model can reason over the full material instead of fragments.
Understands images, video and audio
Besides text, Perceptron Mk1.5 accepts images, video and audio as input, so a single request can combine instructions with visual or other media.
Function calling
Perceptron Mk1.5 supports tool (function) calling: describe your functions in the request and the model returns structured calls your code can run — the basis for agents and integrations.
Adjustable reasoning effort
Choose a reasoning effort level (low, medium or high) per request to balance depth of thinking against speed and token usage.
Structured outputs
Ask for JSON that follows a schema (response_format), which makes extraction, classification and system integrations more reliable.
How to Use Perceptron Mk1.5 on ModelFold
- 1
Step 1: Try it in the Playground
Open the Playground at the top of this page, type a prompt and see how Perceptron Mk1.5 responds before writing any code.
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Step 2: Create an API key
Sign in to ModelFold and create an API key in the console. Keep it secret and send it as a Bearer token.
- 3
Step 3: Send a request
Call POST https://modelfold.ai/v1/chat/completions with "model": "perceptron-mk1-5" and your messages. Existing OpenAI-compatible SDKs work by changing the base URL and key.
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Step 4: Ship and monitor
Integrate the response into your product and check token usage and spend for every call in the console logs.
What You Can Build with Perceptron Mk1.5
Screenshot and image understanding
Read screenshots, charts, diagrams and photos alongside text — for UI review, visual QA or turning images into structured data.
Audio and video analysis
Summarize recordings, meetings and video clips, extract key points and answer questions about their content.
Autonomous agents
Build agents that plan multi-step tasks, call your tools and APIs, and keep working toward a goal across long sessions.
Analysis and complex reasoning
Work through research questions, data interpretation, planning and other problems that need careful step-by-step reasoning.
Frequently Asked Questions
What is Perceptron Mk1.5?⌄
Perceptron Mk1.5 is Perceptron’s embodied reasoning model for physical agents. It takes text, image, video and audio input and can answer with structured annotations such as points, boxes, polygons and tracks.
Which inputs does Perceptron Mk1.5 support?⌄
Perceptron Mk1.5 accepts text, images, video and audio and returns text. Through ModelFold you can send text and images (OpenAI-style image_url content); in the Playground you can also attach documents, which are converted to text.
How long is the context window of Perceptron Mk1.5?⌄
Up to 37K tokens, shared between your input and the model’s output.
Does Perceptron Mk1.5 support function calling?⌄
Yes. Perceptron Mk1.5 supports tools / function calling through the standard tools parameter of the chat completions API.
How is Perceptron Mk1.5 billed on ModelFold?⌄
Pay as you go by tokens: input and output tokens are charged at the per-million-token prices shown on this page. There is no monthly fee, and failed requests are not charged.
How do I call Perceptron Mk1.5 through the API?⌄
Send a POST request to https://modelfold.ai/v1/chat/completions with "model": "perceptron-mk1-5", using your ModelFold API key as the Bearer token.
| Input | 30 credits 1M tokens≈ $0.15 |
| Output | 300 credits 1M tokens≈ $1.50 |
Billed per token: input and output are priced separately, and thinking tokens count as output. The Playground charges exactly the same way.
Read API docs →AI Agents · Claude Code / Cursor / Trae →curl https://modelfold.ai/v1/chat/completions \
-H "Authorization: Bearer $MODELFOLD_API_KEY" \
-H "Content-Type: application/json" \
-d '{"model":"perceptron-mk1-5","messages":[{"role":"user","content":"Hello"}]}'