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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. Codestral 2501Mistral AIRemove
  2. Claude Fable 5.1AnthropicRemove
  3. GLM 5.3 FlashZ.AIRemove
  4. Muse Spark 1.3MetaRemove

4 is the maximum. Remove one to add another.

codestral-2501 vs claude-fable-5.1 vs glm-5.3-flash vs muse-spark-1.3
AttributeCodestral 2501codestral-2501Claude Fable 5.1claude-fable-5.1GLM 5.3 Flashglm-5.3-flashMuse Spark 1.3muse-spark-1.3
Pricing
Input$0.30 / 1M$10.00 / 1M$0.075 / 1M$1.25 / 1M
Output$0.90 / 1M$50.00 / 1M$0.25 / 1M$4.25 / 1M
Cache Write (5m)$0.30 / 1M$12.50 / 1M$0.075 / 1M$1.25 / 1M
Cache Write (1h)$0.30 / 1M$20.00 / 1M$0.075 / 1M$1.25 / 1M
Cache Read$0.30 / 1M$1.00 / 1M$0.075 / 1M$1.25 / 1M
Web Search$0 / 1M$0 / 1M$0 / 1M$0 / 1M
Context
Max context262.1K1M1M1M
Max outputN/AN/AN/AN/A
Capabilities
VisionNoYesYesYes
Function CallingNoYesYesYes
JSON ModeNoYesYesYes
StreamingNoYesYesYes
Catalogue
ProviderMistral AIAnthropicZ.AIMeta
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.GLM-5.3-Flash is Z.AI's efficient native multimodal model, designed for coding and long-horizon agentic workflows. It combines strong multimodal capabilities with an architecture optimized for responsive, cost-efficient task execution. Built on a hybrid sparse and linear attention architecture, GLM-5.3-Flash maintains accurate long-context behavior while reducing computational overhead, making it well suited for coding agents, extended multi-step tasks, and scalable production workloads.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.