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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. Gemini Embedding 2GoogleRemove
  2. Perceptron Mk1.5PerceptronRemove
  3. Universal-3.5 ProAssemblyAIRemove
gemini-embedding-2-preview vs perceptron-mk1.5 vs universal-3-5-pro
AttributeGemini Embedding 2gemini-embedding-2-previewPerceptron Mk1.5perceptron-mk1.5Universal-3.5 Prouniversal-3-5-pro
Pricing
Input$0.60 / 1M$0.15 / 1M— Not priced per input token
Output$2.40 / 1M$1.50 / 1M— Not priced per output token
Cache Write (5m)$0.60 / 1M$0.15 / 1MNot applicable
Cache Write (1h)$0.60 / 1M$0.15 / 1MNot applicable
Cache Read$0.60 / 1M$0.15 / 1MNot applicable
Web Search—$0 / 1M$0 / 1M
Context
Max context8.2K36.9KN/A
Max outputN/AN/AN/A
Capabilities
VisionYesNoNo
Function CallingYesNoNo
JSON ModeNoNoNo
StreamingNoYesNo
Catalogue
ProviderGooglePerceptronAssemblyAI
Categoryembeddingchatvoice
Charge typePay As You GoPay As You GoPay As You Go
Released—2026-09-252026-09-22
Description
SummaryGemini 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.AssemblyAI Universal-3.5 Pro speech-to-text. Billed per second of audio.