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Perceptron: Perceptron Mk1

perceptron/perceptron-mk1

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Perceptron Mk1 (Mark One) is Perceptron's highest-quality vision-language model for video and embodied reasoning.** It accepts image and video inputs paired with natural language queries, and produces detailed visual understanding responses, either structured or natural language. It excels at video understanding tasks like video QA, summarization, and event detection. On image inputs, it advances point-by-example grounding from multimodal prompts, OCR and document parsing on messy real-world inputs, open vocabulary object detection and counting, and hand pose estimation.

Reasoning can be enabled per request to trade latency for deeper analysis on harder tasks. Structured annotations are emitted inline with text only when explicitly requested via the annotation_format parameter (pass "point", "box", or "polygon" for spatial localization on images, or "clip" (start/end timestamps) for temporal segments in video). Without annotation_format, the model returns natural-language text only.

Modalities

In / Out Price

$0.15 / $1.50per 1M

Context

33K

Overview
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Performance for Perceptron Mk1

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Effective Pricing for Perceptron Mk1

Actual cost per million tokens across providers over the past hour

Apps using Perceptron Mk1

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Recent activity on Perceptron Mk1

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Uptime stats for Perceptron Mk1

Uptime stats for Perceptron Mk1 across all providers

Providers for Perceptron Mk1

OpenRouter routes requests to the best providers that are able to handle your prompt size and parameters, with fallbacks to maximize uptime.

Sample code and API for Perceptron Mk1

OpenRouter normalizes requests and responses across providers for you.

OpenRouter supports reasoning-enabled models that can show their step-by-step thinking process. Use the reasoning parameter in your request to enable reasoning, and access the reasoning_details array in the response to see the model's internal reasoning before the final answer. When continuing a conversation, preserve the complete reasoning_details when passing messages back to the model so it can continue reasoning from where it left off. Learn more about reasoning tokens.

In the examples below, the OpenRouter-specific headers are optional. Setting them allows your app to appear on the OpenRouter leaderboards.

Using third-party SDKs

For information about using third-party SDKs and frameworks with OpenRouter, please see our frameworks documentation.

See the Request docs for all possible fields, and Parameters for explanations of specific sampling parameters.