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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. Muse Spark 1.3MetaRemove
  2. Gemini Embedding 2GoogleRemove
  3. GPT-6 AstraOpenAIRemove
muse-spark-1.3 vs gemini-embedding-2-preview vs gpt-6-astra
AttributeMuse Spark 1.3muse-spark-1.3Gemini Embedding 2gemini-embedding-2-previewGPT-6 Astragpt-6-astra
Pricing
Input$1.25 / 1M$0.60 / 1M$10.00 / 1M
Output$4.25 / 1M$2.40 / 1M$50.00 / 1M
Cache Write (5m)$1.25 / 1M$0.60 / 1M$10.00 / 1M
Cache Write (1h)$1.25 / 1M$0.60 / 1M$10.00 / 1M
Cache Read$1.25 / 1M$0.60 / 1M$10.00 / 1M
Web Search$0 / 1M$0 / 1M
Context
Max context1M8.2K1M
Max outputN/AN/AN/A
Capabilities
VisionYesYesYes
Function CallingYesYesYes
JSON ModeYesNoYes
StreamingYesNoYes
Catalogue
ProviderMetaGoogleOpenAI
Categorychatembeddingchat
Charge typePay As You GoPay As You GoPay As You Go
Released
Description
SummaryMuse Spark 1.3 is Meta's multimodal reasoning model designed for long-running agentic, multi-agent, and coding workflows. It maintains context and information across extended tasks, enabling reliable execution in complex, multi-step environments. The model is optimized to resolve conflicting information, seek clarification or confirmation when necessary, and execute concisely, making it well suited for autonomous agents, collaborative multi-agent systems, and long-horizon software engineering workflows.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.GPT-6 Astra is OpenAI's flagship model for demanding end-to-end professional work, designed for advanced analysis, software engineering, deep research, scientific tasks, and document creation. It is particularly strong in long-horizon agentic workflows, including tasks that require sustained reasoning, tool orchestration, and computer and browser use, making it well suited for complex autonomous workflows and production-grade knowledge work.