Gemini
8 results
Context Caching Explained: Cut AI Costs by Up to 90% on Repeated Context
Context caching lets you pay for large inputs once and reuse them across multiple calls. Here's how it works on Anthropic, Google, and OpenAI's APIs — and when to use it.
How to Prompt Gemini 2.0: Long Context, Multimodal, and Grounding
Gemini 2.0 excels at extremely long-context tasks and native multimodal reasoning. Here's how to prompt it effectively, including grounding, code execution, and the 1M-token window.
Claude vs GPT-4o vs Gemini vs LLaMA: Which Model for Which Task?
A practical comparison of the leading AI models for coding, writing, analysis, long context, and cost. No benchmarks — just honest trade-offs for real-world use cases.
How to Use OpenClaw with Gemini API (Step-by-Step Setup)
Connect OpenClaw to Google's Gemini API. Covers getting your API key from Google AI Studio, configuring the provider, choosing between Gemini Flash and Pro, and practical cost management.
Best LLM for OpenClaw: Anthropic vs OpenAI vs Local
Which AI model should you connect to OpenClaw? Tested breakdown of GPT-4o, Claude Sonnet, Gemini, and local models (Llama, Mistral, Phi) across cost, response quality, instruction-following, and tool use.
ChatGPT vs Claude vs Gemini: Best AI Pick for 2026
A practical comparison of ChatGPT, Claude, and Gemini — covering strengths, weaknesses, and exactly which model to use for different prompting tasks.
OpenClaw vs ChatGPT vs Claude vs Gemini: Best Pick
OpenClaw, ChatGPT, Claude, and Gemini are fundamentally different tools. Here's an honest breakdown of what each does well, what it costs, and how to decide which one belongs in your workflow.
Structured Output from AI APIs: JSON Every Time
How to reliably get JSON, typed objects, and formatted data from ChatGPT, Claude, and Gemini APIs. Covers response_format, tool use, Pydantic, and every technique that actually works in production.