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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. Claude Fable 5.1AnthropicRemove
  2. GLM 5.3 FlashZ.AIRemove
  3. Perceptron Mk1.5PerceptronRemove
claude-fable-5.1 vs glm-5.3-flash vs perceptron-mk1.5
AttributeClaude Fable 5.1claude-fable-5.1GLM 5.3 Flashglm-5.3-flashPerceptron Mk1.5perceptron-mk1.5
Pricing
Input$10.00 / 1M$0.075 / 1M$0.15 / 1M
Output$50.00 / 1M$0.25 / 1M$1.50 / 1M
Cache Write (5m)$12.50 / 1M$0.075 / 1M$0.15 / 1M
Cache Write (1h)$20.00 / 1M$0.075 / 1M$0.15 / 1M
Cache Read$0.25 / 1M$0.075 / 1M$0.15 / 1M
Web Search$0 / 1M$0 / 1M$0 / 1M
Context
Max context1M1M36.9K
Max outputN/AN/AN/A
Capabilities
VisionYesYesNo
Function CallingYesYesNo
JSON ModeYesYesNo
StreamingYesYesYes
Catalogue
ProviderAnthropicZ.AIPerceptron
Categorychatchatchat
Charge typePay As You GoPay As You GoPay As You Go
Released——2026-09-25
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.Perceptron Mk1.5 chat model that accepts audio input. Audio and text input are billed per token.