perceptron · Efficient
Perceptron Mk1.5
Perceptron Mk1.5 is a multimodal reasoning model for visual analysis and physical agents. It accepts text, images, video, and audio, supports tool calling and structured output, and can return spatial annotations such as points, boxes, polygons, and tracks.
- Reasoning
- Tools
- Vision
- Structured output
- Audio input
- Video input
- Input
- Text, Images, Video, Audio
- Output
- Text
- Reasoning effort
- none · minimal · low · medium · high
- Discovery tier
- Efficient
Pricing
USD per 1M tokens- Input
- $0.15
- Output
- $1.50
Reference prices as published by the model provider. API example
Specifications
- Context window
- 36.9K
- Max output
- 8.2K
- Average output (7 days)
- 81 tokens
- Longer than 7% of 468 models
Side by side
Perceptron Mk1.5 compared
Specifications, prices, speed and benchmark scores next to each other. Benchmarks below show every compared model too.
| Perceptron Mk1.5perceptronThis model | Perceptron Mk1perceptronRemove | |
|---|---|---|
| Provider | perceptron | perceptron |
| Discovery tier | Efficient | Efficient |
| Added | Sep 25, 2026 | May 12, 2026 |
| Limits | ||
| Context window | 36.86KBest | 32.77K |
| Max output | 8.19K | 8.19K |
| Average output | 81 tokens | — |
| Pricing, USD per 1M tokens | ||
| Input | $0.15 | $0.15 |
| Output | $1.50 | $1.50 |
| Capabilities | ||
| Reasoning | Yes | Yes |
| Tools | Yes | No |
| Vision | Yes | Yes |
| Structured output | Yes | Yes |
| Audio input | Yes | No |
| Video input | Yes | Yes |
| Reasoning effort | none, minimal, low, medium, high | — |
Public evaluations
Benchmarks
There are no public benchmark results for these models yet.
Live routing data
Performance and reliability
Recent averages across requests routed for this model. Your own speed depends on prompt length, reasoning effort and load.
- Prompt cache hits
- 0.0%
Cache hits are the share of input tokens recently served from a prompt cache across all requests. They are not a forecast of your own hit rate.
Developers
Use it through the API
Noumen’s API is OpenAI-compatible: any Chat Completions client works with a base URL and a key.
curl https://www.noumen.xyz/api/v1/chat/completions \
-H "Authorization: Bearer $NOUMEN_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"model": "perceptron/perceptron-mk1.5",
"reasoning_effort": "medium",
"messages": [{ "role": "user", "content": "Explain this stack trace." }]
}'import os
from openai import OpenAI
client = OpenAI(base_url="https://www.noumen.xyz/api/v1", api_key=os.environ["NOUMEN_API_KEY"])
reply = client.chat.completions.create(
model="perceptron/perceptron-mk1.5",
messages=[{"role": "user", "content": "Explain this stack trace."}],
)
print(reply.choices[0].message.content)perceptron
Related models
Other perceptron models, starting with the same family.
- Efficient