Models / Perceptron/ Perceptron Mk1

Perceptron Mk1

Perceptron · released May 12, 2026

Input: text, images and video. Output: text.InputOutput
Type
Proprietary
Input
$0.15
Output
$1.50
Cached
Not published

List price · per 1M tokens · Perceptron at 33K context · source ↗

Our take

Written Aug 3, 2026

Perceptron Mk1 is a hosted-only system that reads text, images and video and writes text back, with a 32,768-token limit per request. It launched in May 2026, but no independent quality scores are available yet to judge its capabilities.

Who should pick it

Use this when you need multimodal understanding across text, image and video in a single hosted system with a moderate context scale, and you are comfortable with the vendor's own hosting at 31 tokens per second. Skip it if you need verified quality data to justify your spend, if you want competitive pricing between providers, or if you need throughput guarantees on third-party hosts.

The case for it

  • Handles text, images and video with a 32,768-token request limit.
  • Available from two hosted providers, including direct from the vendor.

The case against it

  • No benchmark scores in our data for chat, reasoning, coding or multimodal tasks — quality is entirely unverified.
  • Output rate is high relative to the lack of measured quality evidence, with identical pricing across both tracked hosts and no competitive differentiation.
  • Throughput is only verified on Perceptron's own platform; the second provider's speed is unmeasured.
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How good is it?

We hold no score for this model.

We look for every model we track on every board we watch, and none of them has turned up Perceptron Mk1 — so there is no intelligence, coding, agentic or writing score to show you, not a low one, none.

The boards we watch →

01

Or rent it from someone else

Cheapest published offer

Why this differs from the header. The strip above quotes Perceptron's own list price. This is the cheapest live offer at the widest standard context we hold, whoever is serving it — a reseller undercutting a lab is ordinary commerce, not an error.

per 1M tokens
$0.15 in / $1.50 out
Context served
33K
Throughput
Not measured
Current provider offers with price, context and prompt-privacy answers
ProviderIn / out per 1M tokensContextThroughputTrains on promptsLogs promptsZero retention
OpenRouter$0.15 / $1.5033Knot measuredUnknownUnknownUnknown
Perceptron$0.15 / $1.5033K31 tok/sNoNoConfirmed

Across the 2 listings we hold: 1 say they do not train on prompts, 0 say they do and 1 do not say. 1 appear in the zero-retention registry we check; the rest are unknown to us rather than confirmed either way.

What each host's API supports

From the parameter list each endpoint publishes. Streaming is omitted: nothing we hold reports it, for any model.

Supported
Not supported
Not published
host gave no parameter list
API features per host
ProviderTool callingJSON outputStrict schema
OpenRouter
Perceptron

Tool calling: 0 of 2 listings say yes, 2 say no. JSON output: 0 of 2 listings say yes, 2 say no. Strict schema: 2 of 2 listings say yes.

02

When we formed this view

Dates behind this page

Jul 26, 2026ListedListed on LLMapfirst indexed by our pipeline
May 12, 2026AnnouncedPerceptron Mk1 announced by Perceptron

Prices last checked 9d ago

What we do not know about this model yet

  • No board we watch has turned up a score, so we hold no quality figures at all.
  • Nothing we hold says whether an endpoint streams, so we do not show it either way.
  • 1 of 2 listings do not say whether they train on prompts.
  • We hold no cached-input rate for any of its listings.
03

Licence and identifiers

What the licence allowsWe hold no licence record for this model. Inside are the identifiers you need to pull it — its Hugging Face repo where we have one, our slug and a machine-readable card.

Licence

Commercial API terms. We hold no licence record for this model, so there is nothing to summarise here.

Identifiers

Modality record
text+image+video->text
Catalogue slug
perceptron-perceptron-mk1

Machine-readable model card (omc.json) →

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