Models overview - Perceptron Docs

Use Perceptron Mk1.5 for new integrations that need audio understanding, video soundtracks, configurable reasoning, tool calling, visual grounding across multiple assets, or native video tracking.

Model	Inputs	Function calling	Model guide
`perceptron-mk1.5`	Text, images, video, audio	Yes	Perceptron Mk1.5
`perceptron-mk1`	Text, images, video	No	Perceptron Mk1

The Isaac 0.1 and 0.2 models have been retired from the Perceptron API; see the release notes. Model availability can change; query the API for the current catalog and per-model limits:

from perceptron import Client

client = Client(provider="perceptron")
models = client.models.list(extended=True)
for model in models:
    print(model.id, model.modalities, model.capabilities)

model = client.models.retrieve("perceptron-mk1.5", extended=True)
print("Tool calling:", model.supports("tool_calling"))
print("Context limit:", model.max_context_tokens)
print("Output limit:", model.max_output_tokens)

curl 'https://api.perceptron.inc/v1/models?extended=true' \
  -H "Authorization: Bearer $PERCEPTRON_API_KEY"

The Python example uses perceptron>=0.4.0 and reads PERCEPTRON_API_KEY from the environment; see the quickstart. extended=True includes capabilities, modalities, and token limits. Without it, the SDK returns basic model metadata. Inspect each model’s capabilities before sending optional features such as tool_calling. Treat capability names as an extensible list so newly added capabilities do not break your client; the SDK preserves new capability names.