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Compare models

Put up to 4 models beside each other — token prices, context windows, capabilities and provider, from the same catalogue the model pages read.

  1. Nova Lite 1.0AmazonRemove
  2. GLM 5.3Z.AIRemove
  3. Muse Spark 1.3MetaRemove
nova-lite-v1 vs glm-5.3 vs muse-spark-1.3
AttributeNova Lite 1.0nova-lite-v1GLM 5.3glm-5.3Muse Spark 1.3muse-spark-1.3
Pricing
Input$0.18 / 1M$1.40 / 1M$1.25 / 1M
Output$0.72 / 1M$4.40 / 1M$4.25 / 1M
Cache Write (5m)$0.18 / 1M$1.40 / 1M$1.25 / 1M
Cache Write (1h)$0.18 / 1M$1.40 / 1M$1.25 / 1M
Cache Read$0.18 / 1M$1.40 / 1M$1.25 / 1M
Web Search$0 / 1M$0 / 1M$0 / 1M
Context
Max context300K1M1M
Max outputN/AN/AN/A
Capabilities
VisionNoNoYes
Function CallingNoYesYes
JSON ModeNoYesYes
StreamingNoYesYes
Catalogue
ProviderAmazonZ.AIMeta
Categorychatchatchat
Charge typePay As You GoPay As You GoPay As You Go
Released———
Description
Summary—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.