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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. GPT Image 2OpenAIRemove
  2. Muse Spark 1.3MetaRemove
  3. Gemini 3.8 FlashGoogleRemove
gpt-image-2 vs muse-spark-1.3 vs gemini-3.8-flash
AttributeGPT Image 2gpt-image-2Muse Spark 1.3muse-spark-1.3Gemini 3.8 Flashgemini-3.8-flash
Pricing
Request$0.04 / request
BillingPay Per Request
Cache Write (5m)Not applicable$1.25 / 1M$0.75 / 1M
Cache Write (1h)Not applicable$1.25 / 1M$0.75 / 1M
Cache ReadNot applicable$1.25 / 1M$0.75 / 1M
Input$1.25 / 1M$0.75 / 1M
Output$4.25 / 1M$3.75 / 1M
Web Search$0 / 1M$0 / 1M
Context
Max context272K1M1M
Max outputN/AN/AN/A
Capabilities
VisionYesYesYes
Function CallingNoYesYes
JSON ModeNoYesYes
StreamingNoYesYes
Catalogue
ProviderOpenAIMetaGoogle
Categoryimagechatchat
Charge typePay Per RequestPay As You GoPay As You Go
Released
Description
SummaryGPT Image 2 combines OpenAI's GPT-5.4 with advanced image generation capabilities from GPT Image 2, enabling fully integrated multimodal workflows. It allows users to seamlessly transition between reasoning, coding, and visual generation within a single interaction, making it well suited for creative, development, and agent-driven applications that require both intelligence and visual output.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.Gemini 3.8 Flash is Google's most intelligent Flash-class model, delivering significant improvements over Gemini 3.7 Flash across software engineering, agentic workflows, and complex multi-step reasoning. Designed to combine strong capability with Flash-tier efficiency, it is well suited for coding assistants, autonomous agents, and high-throughput production workflows that require responsive performance without sacrificing reasoning quality.