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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 3.8 FlashGoogleRemove
  2. Seedream 4.5ByteDanceRemove
  3. Muse Spark 1.3MetaRemove
gemini-3.8-flash vs doubao-seedream-4-5-251128 vs muse-spark-1.3
AttributeGemini 3.8 Flashgemini-3.8-flashSeedream 4.5doubao-seedream-4-5-251128Muse Spark 1.3muse-spark-1.3
Pricing
Input$0.75 / 1M$1.25 / 1M
Output$3.75 / 1M$4.25 / 1M
Cache Write (5m)$0.75 / 1MNot applicable$1.25 / 1M
Cache Write (1h)$0.75 / 1MNot applicable$1.25 / 1M
Cache Read$0.75 / 1MNot applicable$1.25 / 1M
Web Search$0 / 1M$0 / 1M
Request$0.375 / request
BillingPay Per Request
Context
Max context1M128K1M
Max outputN/AN/AN/A
Capabilities
VisionYesYesYes
Function CallingYesNoYes
JSON ModeYesNoYes
StreamingYesNoYes
Catalogue
ProviderGoogleByteDanceMeta
Categorychatimagechat
Charge typePay As You GoPay Per RequestPay As You Go
Released
Description
SummaryGemini 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.Seedream 4.5 is ByteDance's advanced AI image generation and editing model, representing a major evolution of the Seedream family. It delivers professional-grade visual quality with rich detail, improved spatial understanding, and cinematic rendering effects. Seedream 4.5 excels at understanding nuanced natural language prompts and generating consistent, high-fidelity outputs with enhanced lighting, depth, and texture. It supports complex workflows such as multi-image composition, fine typography and text rendering, and image-to-image editing with enhanced prompt interpretation.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.