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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. Claude Sonnet 5.5AnthropicRemove
transcribe-1-pro vs gemini-embedding-2-preview vs claude-sonnet-5.5
AttributeTranscribe 1 Protranscribe-1-proGemini Embedding 2gemini-embedding-2-previewClaude Sonnet 5.5claude-sonnet-5.5
Pricing
Input— Not priced per input token$0.60 / 1M$2.00 / 1M
Output— Not priced per output token$2.40 / 1M$10.00 / 1M
Cache Write (5m)Not applicable$0.60 / 1M$2.50 / 1M
Cache Write (1h)Not applicable$0.60 / 1M$4.00 / 1M
Cache ReadNot applicable$0.60 / 1M$0.20 / 1M
Web Search$0 / 1M—$0 / 1M
Context
Max contextN/A8.2K1M
Max outputN/AN/AN/A
Capabilities
VisionNoYesYes
Function CallingNoYesYes
JSON ModeNoNoYes
StreamingNoNoYes
Catalogue
ProviderFish AudioGoogleAnthropic
Categoryvoiceembeddingchat
Charge typePay As You GoPay As You GoPay As You Go
Released2026-09-24——
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.Claude Sonnet 5.5 is Anthropic's Sonnet-class model for well-scoped everyday work, serving as a direct upgrade to Sonnet 5. It excels at feature development, bug fixing, and creating polished documents, presentations, and spreadsheets, while offering clearer writing and communication than its predecessor.