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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 Sonnet 5.5AnthropicRemove
  2. Gemma 4 31B (Free)GoogleRemove
  3. GPT-6.1 SolOpenAIRemove
claude-sonnet-5.5 vs gemma-4-31b-it:free vs gpt-6.1-sol
AttributeClaude Sonnet 5.5claude-sonnet-5.5Gemma 4 31B (Free)gemma-4-31b-it:freeGPT-6.1 Solgpt-6.1-sol
Pricing
Input$2.00 / 1M$0 / 1M$2.00 / 1M
Output$10.00 / 1M$0 / 1M$10.00 / 1M
Cache Write (5m)$2.50 / 1M—$2.00 / 1M
Cache Write (1h)$4.00 / 1M—$2.00 / 1M
Cache Read$0.20 / 1M$0 / 1M$2.00 / 1M
Web Search$0 / 1M—$0 / 1M
Cache Write—$0 / 1M—
Context
Max context1M262.1K1M
Max outputN/AN/AN/A
Capabilities
VisionYesYesYes
Function CallingYesYesYes
JSON ModeYesYesYes
StreamingYesYesYes
Catalogue
ProviderAnthropicGoogleOpenAI
Categorychatchatchat
Charge typePay As You GoFreePay As You Go
Released———
Description
SummaryClaude Sonnet 5.5 is Anthropic's Sonnet-class model for well-scoped everyday work, serving as a direct upgrade to Sonnet 5. It excels at feature development, bug fixing, and creating polished documents, presentations, and spreadsheets, while offering clearer writing and communication than its predecessor.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.GPT-6.1 Sol is an upgraded high-end model in OpenAI's GPT-6 series, positioned below the flagship GPT-6 Astra. It is optimized for agentic coding, computer use, document-heavy professional work, and multi-step business automation, delivering near-Astra-level capability at significantly lower cost. Compared with GPT-6 Sol, it offers improved factual reliability and stronger adherence to explicit constraints and user intent, making it well suited for complex, long-running agentic workflows where accurate and dependable execution is critical.