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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 3.1 Flash Image (Google Vertex AI)GoogleEnterprise & partner accessRemove
  2. Muse Spark 1.3MetaRemove
  3. Muse Spark OpenMetaRemove
gemini-3.1-flash-image-vertex vs muse-spark-1.3 vs muse-spark-open
AttributeGemini 3.1 Flash Image (Google Vertex AI)gemini-3.1-flash-image-vertexMuse Spark 1.3muse-spark-1.3Muse Spark Openmuse-spark-open
Pricing
Request$0.067 / request——
BillingPay Per Request——
Cache Write (5m)Not applicable$1.25 / 1M$1.25 / 1M
Cache Write (1h)Not applicable$1.25 / 1M$1.25 / 1M
Cache ReadNot applicable$1.25 / 1M$1.25 / 1M
Input—$1.25 / 1M$1.25 / 1M
Output—$4.25 / 1M$4.25 / 1M
Web Search—$0 / 1M$0 / 1M
Context
Max contextN/A1M1M
Max outputN/AN/AN/A
Capabilities
VisionYesYesYes
Function CallingNoYesYes
JSON ModeNoYesYes
StreamingNoYesYes
Catalogue
ProviderGoogleMetaMeta
Categoryimagechatchat
Charge typePay Per RequestPay As You GoPay As You Go
Released———
Description
SummaryGemini 3.1 Flash Image served from Google Vertex AI. Billed per image at US$0.067. Call it through /v1/chat/completions with stream set to false; the image is returned in the message content as a base64 data URI. Maximum output resolution is 2K. A request for a larger size, such as 4K or 4096x4096, returns a 2K image with the same aspect ratio at the same price. When a size is reduced, the response carries an X-Image-Resolution-Capped header with the requested and delivered size, for example 4096x4096->2048x2048.Muse 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.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.