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. Claude Sonnet 4.6AnthropicRemove
  2. Gemini 3.8 FlashGoogleRemove
  3. GPT-6 AstraOpenAIRemove
claude-sonnet-4-6 vs gemini-3.8-flash vs gpt-6-astra
AttributeClaude Sonnet 4.6claude-sonnet-4-6Gemini 3.8 Flashgemini-3.8-flashGPT-6 Astragpt-6-astra
Pricing
Input$2.40 / 1M$0.75 / 1M$10.00 / 1M
Output$12.00 / 1M$3.75 / 1M$50.00 / 1M
Cache Write (5m)$3.00 / 1M$0.75 / 1M$10.00 / 1M
Cache Write (1h)$4.80 / 1M$0.75 / 1M$10.00 / 1M
Cache Read$0.24 / 1M$0.75 / 1M$10.00 / 1M
Web Search$0 / 1M$0 / 1M$0 / 1M
Context
Max context1M1M1M
Max outputN/AN/AN/A
Capabilities
VisionYesYesYes
Function CallingYesYesYes
JSON ModeYesYesYes
StreamingYesYesYes
Catalogue
ProviderAnthropicGoogleOpenAI
Categorychatchatchat
Charge typePay As You GoPay As You GoPay As You Go
Released
Description
SummarySonnet 4.6 is Anthropic's most capable Sonnet-class model, delivering frontier-level performance across coding, agent workflows, and professional knowledge tasks. It excels at iterative development, complex codebase navigation, and end-to-end project execution, supported by strong contextual understanding and persistent task handling. Beyond engineering tasks, Sonnet 4.6 produces polished documents and analyses while demonstrating reliable computer-use capabilities for web QA, workflow automation, and structured productivity workflows, making it well suited for both development and professional applications.Gemini 3.8 Flash is Google's most intelligent Flash-class model, delivering significant improvements over Gemini 3.7 Flash across software engineering, agentic workflows, and complex multi-step reasoning. Designed to combine strong capability with Flash-tier efficiency, it is well suited for coding assistants, autonomous agents, and high-throughput production workflows that require responsive performance without sacrificing reasoning quality.GPT-6 Astra is OpenAI's flagship model for demanding end-to-end professional work, designed for advanced analysis, software engineering, deep research, scientific tasks, and document creation. It is particularly strong in long-horizon agentic workflows, including tasks that require sustained reasoning, tool orchestration, and computer and browser use, making it well suited for complex autonomous workflows and production-grade knowledge work.