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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. Claude Fable 5.1AnthropicRemove
  2. GLM 5.3Z.AIRemove
  3. Qwen3.8 27BAlibabaRemove
  4. Gemma 3 4BGoogleRemove

4 is the maximum. Remove one to add another.

claude-fable-5.1 vs glm-5.3 vs qwen3.8-27b vs gemma-3-4b-it
AttributeClaude Fable 5.1claude-fable-5.1GLM 5.3glm-5.3Qwen3.8 27Bqwen3.8-27bGemma 3 4Bgemma-3-4b-it
Pricing
Input$10.00 / 1M$1.40 / 1M$0.45 / 1M$0.02 / 1M
Output$50.00 / 1M$4.40 / 1M$3.20 / 1M$0.04 / 1M
Cache Write (5m)$12.50 / 1M$1.40 / 1M$0.45 / 1M$0.02 / 1M
Cache Write (1h)$20.00 / 1M$1.40 / 1M$0.45 / 1M$0.02 / 1M
Cache Read$1.00 / 1M$1.40 / 1M$0.45 / 1M$0.02 / 1M
Web Search$0 / 1M$0 / 1M$0 / 1M$0 / 1M
Context
Max context1M1M262K131.1K
Max outputN/AN/AN/AN/A
Capabilities
VisionYesNoYesNo
Function CallingYesYesYesNo
JSON ModeYesYesYesNo
StreamingYesYesYesNo
Catalogue
ProviderAnthropicZ.AIAlibabaGoogle
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 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.Qwen3.8 27B is an open-weight dense vision-language model from Qwen, designed for coding, professional knowledge work, research, and multimodal interaction. It combines strong text and visual understanding with capabilities optimized for sustained, real-world agentic tasks. The model supports flexible thinking modes that can be enabled for deeper reasoning or disabled for faster execution, making it well suited for long-running agents, multimodal workflows, coding assistants, and cost-conscious self-hosted deployments.