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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. Claude Fable 5.1AnthropicRemove
  2. Qwen TurboAlibabaRemove
  3. Muse Spark 1.3MetaRemove
  4. GLM 5.3Z.AIRemove

4 is the maximum. Remove one to add another.

claude-fable-5.1 vs qwen-turbo vs muse-spark-1.3 vs glm-5.3
AttributeClaude Fable 5.1claude-fable-5.1Qwen Turboqwen-turboMuse Spark 1.3muse-spark-1.3GLM 5.3glm-5.3
Pricing
Input$10.00 / 1M$0.05 / 1M$1.25 / 1M$1.40 / 1M
Output$50.00 / 1M$0.20 / 1M$4.25 / 1M$4.40 / 1M
Cache Write (5m)$12.50 / 1M$0.05 / 1M$1.25 / 1M$1.40 / 1M
Cache Write (1h)$20.00 / 1M$0.05 / 1M$1.25 / 1M$1.40 / 1M
Cache Read$1.00 / 1M$0.05 / 1M$1.25 / 1M$1.40 / 1M
Web Search$0 / 1M$0 / 1M$0 / 1M$0 / 1M
Context
Max context1M1M1M1M
Max outputN/AN/AN/AN/A
Capabilities
VisionYesNoYesNo
Function CallingYesNoYesYes
JSON ModeYesNoYesYes
StreamingYesNoYesYes
Catalogue
ProviderAnthropicAlibabaMetaZ.AI
Categorychatchatchatchat
Charge typePay As You GoPay As You GoPay As You GoPay As You Go
Released
Description
SummaryClaude Fable 5.1 is an upgraded version of Fable 5, delivering broad improvements with particularly strong gains in agentic coding, long-running workflows, and professional knowledge work. It excels at large code refactors, front-end and visual code generation, financial analysis, and complex analytical tasks. Compared with Fable 5, it also produces more concise plans and summaries while maintaining strong performance across extended tasks, making it a natural upgrade for existing Fable workflows and a strong option alongside Opus 5 for reasoning-intensive applications.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.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.