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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. GPT-6.1 TerraOpenAIRemove
  3. Muse Spark OpenMetaRemove
gemini-embedding-2-preview vs gpt-6.1-terra vs muse-spark-open
AttributeGemini Embedding 2gemini-embedding-2-previewGPT-6.1 Terragpt-6.1-terraMuse Spark Openmuse-spark-open
Pricing
Input$0.60 / 1M$1.00 / 1M$1.25 / 1M
Output$2.40 / 1M$5.00 / 1M$4.25 / 1M
Cache Write (5m)$0.60 / 1M$1.00 / 1M$1.25 / 1M
Cache Write (1h)$0.60 / 1M$1.00 / 1M$1.25 / 1M
Cache Read$0.60 / 1M$1.00 / 1M$1.25 / 1M
Web Search—$0 / 1M$0 / 1M
Context
Max context8.2K1M1M
Max outputN/AN/AN/A
Capabilities
VisionYesYesYes
Function CallingYesYesYes
JSON ModeNoYesYes
StreamingNoNoYes
Catalogue
ProviderGoogleOpenAIMeta
Categoryembeddingchatchat
Charge typePay As You GoPay As You GoPay As You Go
Released———
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.GPT-6.1 Terra is OpenAI’s mid-tier model in the GPT-6.1 series, designed to balance capability, speed, and cost efficiency. Positioned below GPT-6.1 Sol, it delivers strong performance across everyday agentic workflows, coding, and professional writing, with particular strengths in screenshot understanding and on-screen content analysis. Optimized for high-volume production workloads, GPT-6.1 Terra is well suited for coding assistants, visual interface analysis, workflow automation, and scalable agentic applications that require reliable performance at an accessible cost.Muse Spark Open is an open-weight, coding-optimized model designed for agentic software engineering workflows. It delivers strong first-attempt accuracy, reliable tool calling, and deep codebase understanding, enabling effective development across real-world repositories. Optimized for autonomous coding agents, complex code navigation, and tool-driven development, Muse Spark Open is well suited for software engineering automation, debugging, code generation, and multi-step coding workflows where accuracy and reliable execution are essential.