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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. Gemini 3.7 FlashGoogleRemove
  3. GLM 4.6 (Thinking)Z.AIRemove
claude-fable-5.1 vs gemini-3.7-flash vs glm-4.6-thinking
AttributeClaude Fable 5.1claude-fable-5.1Gemini 3.7 Flashgemini-3.7-flashGLM 4.6 (Thinking)glm-4.6-thinking
Pricing
Input$10.00 / 1M$0.375 / 1M$0.40 / 1M
Output$50.00 / 1M$1.88 / 1M$1.50 / 1M
Cache Write (5m)$12.50 / 1M$0.375 / 1M$0.40 / 1M
Cache Write (1h)$20.00 / 1M$0.375 / 1M$0.40 / 1M
Cache Read$1.00 / 1M$0.375 / 1M$0.40 / 1M
Web Search$0 / 1M$0 / 1M$0 / 1M
Context
Max context1M1M202.8K
Max outputN/AN/AN/A
Capabilities
VisionYesYesYes
Function CallingYesYesYes
JSON ModeYesYesYes
StreamingYesYesYes
Catalogue
ProviderAnthropicGoogleZ.AI
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.Gemini 3.7 Flash is Google's fast multimodal model designed for agentic workflows, coding, and complex multi-step reasoning. It combines responsive inference with reliable problem-solving capabilities, making it well suited for interactive and production-scale applications. Optimized for speed and dependable multi-step execution, Gemini 3.7 Flash is a strong choice for coding assistants, autonomous agents, and high-throughput workflows that require both low latency and capable reasoning.GLM-4.6 improves on GLM-4.5 with a larger 200K context window, stronger coding performance (including better real-world agent tools like Claude Code and Cline), and clearer gains in reasoning with built-in tool use. It delivers more capable agent behavior, integrates better into agent frameworks, and produces more natural, readable writing — especially in role-playing scenarios.