Compare models

Put up to 4 models beside each other — token prices, context windows, capabilities and provider, from the same catalogue the model pages read.

Perceptron Mk1.5Perceptron Remove
Gemini 3.5 TranscribeGoogle Remove
Transcribe 1 ProFish Audio Remove
GPT-6.1 SolOpenAI Remove

4 is the maximum. Remove one to add another.

perceptron-mk1.5 vs gemini-3.5-transcribe vs transcribe-1-pro vs gpt-6.1-sol
Attribute	Perceptron Mk1.5perceptron-mk1.5	Gemini 3.5 Transcribegemini-3.5-transcribe	Transcribe 1 Protranscribe-1-pro	GPT-6.1 Solgpt-6.1-sol
Pricing
Input	$0.15 / 1M	$0 / 1M	$0 / 1M	$2.00 / 1M
Output	$1.50 / 1M	$0 / 1M	$0 / 1M	$10.00 / 1M
Cache Write (5m)	$0.15 / 1M	Not applicable	Not applicable	$2.00 / 1M
Cache Write (1h)	$0.15 / 1M	Not applicable	Not applicable	$2.00 / 1M
Cache Read	$0.15 / 1M	Not applicable	Not applicable	$2.00 / 1M
Web Search	$0 / 1M	$0 / 1M	$0 / 1M	$0 / 1M
Context
Max context	36.9K	98.3K	N/A	1M
Max output	N/A	N/A	N/A	N/A
Capabilities
Vision	No	Yes	No	Yes
Function Calling	No	Yes	No	Yes
JSON Mode	No	No	No	Yes
Streaming	Yes	No	No	Yes
Catalogue
Provider	Perceptron	Google	Fish Audio	OpenAI
Category	chat	voice	voice	chat
Charge type	Pay As You Go	Pay As You Go	Pay As You Go	Pay As You Go
Released	2026-09-25	2026-09-25	2026-09-24	—
Description
Summary	Perceptron Mk1.5 chat model that accepts audio input. Audio and text input are billed per token.	Google Gemini 3.5 Transcribe speech-to-text. Billed per input and output token.	Fish Audio Transcribe 1 Pro speech-to-text with speaker labels; transcripts include speaker tags such as <\|speaker:0\|>. Billed per second of audio.	GPT-6.1 Sol is an upgraded high-end model in OpenAI's GPT-6 series, positioned below the flagship GPT-6 Astra. It is optimized for agentic coding, computer use, document-heavy professional work, and multi-step business automation, delivering near-Astra-level capability at significantly lower cost. Compared with GPT-6 Sol, it offers improved factual reliability and stronger adherence to explicit constraints and user intent, making it well suited for complex, long-running agentic workflows where accurate and dependable execution is critical.