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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. Gemini 3.7 FlashGoogleRemove
  2. Claude Fable 5.1AnthropicRemove
  3. Gemma 4 31BGoogleRemove
gemini-3.7-flash vs claude-fable-5.1 vs gemma-4-31b-it
AttributeGemini 3.7 Flashgemini-3.7-flashClaude Fable 5.1claude-fable-5.1Gemma 4 31Bgemma-4-31b-it
Pricing
Input$0.375 / 1M$10.00 / 1M$0.14 / 1M
Output$1.88 / 1M$50.00 / 1M$0.40 / 1M
Cache Write (5m)$0.375 / 1M$12.50 / 1M$0.14 / 1M
Cache Write (1h)$0.375 / 1M$20.00 / 1M$0.14 / 1M
Cache Read$0.375 / 1M$1.00 / 1M$0.14 / 1M
Web Search$0 / 1M$0 / 1M$0 / 1M
Context
Max context1M1M262.1K
Max outputN/AN/AN/A
Capabilities
VisionYesYesYes
Function CallingYesYesYes
JSON ModeYesYesYes
StreamingYesYesYes
Catalogue
ProviderGoogleAnthropicGoogle
Categorychatchatchat
Charge typePay As You GoPay As You GoPay As You Go
Released
Description
SummaryGemini 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.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.Gemma 4 31B Instruct is Google DeepMind's 30.7B dense multimodal model, supporting text and image inputs with text outputs. It features a 256K token context window, configurable thinking/reasoning modes, native function calling, and broad multilingual support across 140+ languages. The model delivers strong performance in coding, reasoning, and document understanding, making it well suited for developer workflows, multilingual applications, and structured knowledge tasks.