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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 5.3Z.AIRemove
  3. GPT-5.3-CodexOpenAIRemove
claude-fable-5.1 vs glm-5.3 vs gpt-5.3-codex
AttributeClaude Fable 5.1claude-fable-5.1GLM 5.3glm-5.3GPT-5.3-Codexgpt-5.3-codex
Pricing
Input$10.00 / 1M$1.40 / 1M$1.75 / 1M
Output$50.00 / 1M$4.40 / 1M$14.00 / 1M
Cache Write (5m)$12.50 / 1M$1.40 / 1M$1.75 / 1M
Cache Write (1h)$20.00 / 1M$1.40 / 1M$1.75 / 1M
Cache Read$1.00 / 1M$1.40 / 1M$1.75 / 1M
Web Search$0 / 1M$0 / 1M$0 / 1M
Context
Max context1M1M400K
Max outputN/AN/AN/A
Capabilities
VisionYesNoYes
Function CallingYesYesYes
JSON ModeYesYesYes
StreamingYesYesYes
Catalogue
ProviderAnthropicZ.AIOpenAI
Categorychatchatchat
Charge typePay 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 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.GPT-Codex-5.3 is OpenAI's most advanced agentic coding model, designed for software engineering workflows that extend beyond single prompts into long-running, tool-driven execution. It combines the frontier coding performance of earlier Codex models with stronger reasoning and professional knowledge capabilities, enabling reliable handling of complex refactors, multi-step debugging, research-driven development, and autonomous task execution. Optimized for developer productivity, GPT-Codex-5.3 supports interactive collaboration during execution, allowing users to steer tasks in real time without losing context. With improved agentic reliability, faster inference, and stronger performance on long-horizon engineering tasks, it is well suited for coding agents, IDE and CLI workflows, and end-to-end software development pipelines where persistence, tool use, and execution continuity are critical.