Skip to content

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. GLM 5.3Z.AIRemove
  2. Claude Fable 5.1AnthropicRemove
  3. Grok 4.7SpaceXAIRemove
glm-5.3 vs claude-fable-5.1 vs grok-4.7
AttributeGLM 5.3glm-5.3Claude Fable 5.1claude-fable-5.1Grok 4.7grok-4.7
Pricing
Input$1.40 / 1M$10.00 / 1M$1.60 / 1M
Output$4.40 / 1M$50.00 / 1M$4.80 / 1M
Cache Write (5m)$1.40 / 1M$12.50 / 1M$1.60 / 1M
Cache Write (1h)$1.40 / 1M$20.00 / 1M$1.60 / 1M
Cache Read$1.40 / 1M$1.00 / 1M$1.60 / 1M
Web Search$0 / 1M$0 / 1M$0 / 1M
Context
Max context1M1M500K
Max outputN/AN/AN/A
Capabilities
VisionNoYesYes
Function CallingYesYesYes
JSON ModeYesYesYes
StreamingYesYesYes
Catalogue
ProviderZ.AIAnthropicSpaceXAI
Categorychatchatchat
Charge typePay As You GoPay As You GoPay As You Go
Released
Description
SummaryGLM-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.Claude 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.Grok 4.7 is SpaceXAI's flagship model for coding, agentic workflows, and professional knowledge work, succeeding Grok 4.6. It is particularly strong at long-running software engineering, self-verification, and long-context execution, while improving capabilities in document drafting, presentations, and other professional tasks. Trained with extended reinforcement learning focused on multi-hour problems, Grok 4.7 is optimized for sustained, complex task execution and natively supports the Grok Bot harness for conversational workflows. It also introduces an enhanced safeguard stack designed to combine strong jailbreak resistance with low refusal rates for legitimate technical work. Reported benchmark results use xhigh reasoning effort.