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| Attribute | Perceptron Mk1.5perceptron-mk1.5 | Gemini Embedding 2gemini-embedding-2-preview |
|---|---|---|
| Pricing | ||
| Input | $0.15 / 1M | $0.60 / 1M |
| Output | $1.50 / 1M | $2.40 / 1M |
| Cache Write (5m) | $0.15 / 1M | $0.60 / 1M |
| Cache Write (1h) | $0.15 / 1M | $0.60 / 1M |
| Cache Read | $0.15 / 1M | $0.60 / 1M |
| Web Search | $0 / 1M | — |
| Context | ||
| Max context | 36.9K | 8.2K |
| Max output | N/A | N/A |
| Capabilities | ||
| Vision | No | Yes |
| Function Calling | No | Yes |
| JSON Mode | No | No |
| Streaming | Yes | No |
| Catalogue | ||
| Provider | Perceptron | |
| Category | chat | embedding |
| Charge type | Pay As You Go | Pay As You Go |
| Released | 2026-09-25 | — |
| Description | ||
| Summary | Perceptron Mk1.5 chat model that accepts audio input. Audio and text input are billed per token. | 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. |