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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. Seedream 3.0ByteDanceRemove
  2. GLM 5.3Z.AIRemove
  3. Muse Spark 1.3MetaRemove
doubao-seedream-3-0-t2i-250415 vs glm-5.3 vs muse-spark-1.3
AttributeSeedream 3.0doubao-seedream-3-0-t2i-250415GLM 5.3glm-5.3Muse Spark 1.3muse-spark-1.3
Pricing
Request$0.075 / request
BillingPay Per Request
Cache Write (5m)Not applicable$1.40 / 1M$1.25 / 1M
Cache Write (1h)Not applicable$1.40 / 1M$1.25 / 1M
Cache ReadNot applicable$1.40 / 1M$1.25 / 1M
Input$1.40 / 1M$1.25 / 1M
Output$4.40 / 1M$4.25 / 1M
Web Search$0 / 1M$0 / 1M
Context
Max context128K1M1M
Max outputN/AN/AN/A
Capabilities
VisionYesNoYes
Function CallingNoYesYes
JSON ModeNoYesYes
StreamingNoYesYes
Catalogue
ProviderByteDanceZ.AIMeta
Categoryimagechatchat
Charge typePay Per RequestPay As You GoPay As You Go
Released
Description
SummaryDoubao-Seedream-3.0-T2I-250415 is ByteDance's advanced text-to-image (T2I) generation model, designed to deliver high-quality visual outputs with strong prompt alignment and fast inference performance. It supports detailed scene composition, rich stylistic control, and high-fidelity rendering across a wide range of creative use cases. Optimized for production deployment, Seedream 3.0 balances visual quality, generation speed, and cost efficiency, making it well suited for creative content generation, design workflows, marketing assets, and interactive image-based applications.GLM-5.3 is Z.ai's large-scale reasoning model designed for complex software engineering and long-horizon agentic workflows. It supports text input and output with a 1M-token context window, enabling sustained reasoning across large codebases and extended multi-step tasks. Building on GLM-5.2, it delivers stronger coding performance while improving the balance between capability and token efficiency, making it well suited for autonomous coding agents, large-scale engineering workflows, and complex task execution.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.