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

  1. Transcribe 1 ProFish AudioRemove
  2. Gemini Embedding 2GoogleRemove
  3. Perceptron Mk1.5PerceptronRemove
transcribe-1-pro vs gemini-embedding-2-preview vs perceptron-mk1.5
AttributeTranscribe 1 Protranscribe-1-proGemini Embedding 2gemini-embedding-2-previewPerceptron Mk1.5perceptron-mk1.5
Pricing
Input— Not priced per input token$0.60 / 1M$0.15 / 1M
Output— Not priced per output token$2.40 / 1M$1.50 / 1M
Cache Write (5m)Not applicable$0.60 / 1M$0.15 / 1M
Cache Write (1h)Not applicable$0.60 / 1M$0.15 / 1M
Cache ReadNot applicable$0.60 / 1M$0.15 / 1M
Web Search$0 / 1M—$0 / 1M
Context
Max contextN/A8.2K36.9K
Max outputN/AN/AN/A
Capabilities
VisionNoYesNo
Function CallingNoYesNo
JSON ModeNoNoNo
StreamingNoNoYes
Catalogue
ProviderFish AudioGooglePerceptron
Categoryvoiceembeddingchat
Charge typePay As You GoPay As You GoPay As You Go
Released2026-09-24—2026-09-25
Description
SummaryFish Audio Transcribe 1 Pro speech-to-text with speaker labels; transcripts include speaker tags such as <|speaker:0|>. Billed per second of audio.Gemini Embedding 2 is Google's advanced text embedding model designed for high-accuracy semantic representation across large-scale retrieval and understanding tasks. It converts text into dense vector embeddings optimized for semantic search, retrieval-augmented generation (RAG), clustering, classification, and recommendation systems. Built for production use, it offers strong multilingual support, improved semantic similarity accuracy, and efficient embedding generation, making it well suited for large knowledge indexing pipelines and enterprise-scale retrieval applications.Perceptron Mk1.5 chat model that accepts audio input. Audio and text input are billed per token.