LLM Best Practices

Gemini vs Claude

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Overview

Choose Gemini when you want Google’s multimodal, voice, and image models and a low per-token price on Flash tiers; choose Claude for long-horizon agent loops and for access through several clouds. Prices below are per million input and output tokens, checked on 2026-10-01 against each vendor’s documentation. For the OpenAI comparison see claude-vs-gpt.

Compare

DimensionGeminiClaude
Top modelGemini 3.1 Pro, gemini-3.1-pro-preview (preview): 12, rising to 18 for prompts above 200K tokensClaude Fable 5.1, claude-fable-5-1: 50, 1M context
Mid and fast tiersGemini 3.8 Flash, gemini-3.8-flash (stable): 3.75 through 2026-12-31, then 7.50 from 2027-01-01Opus 5.5 20; Sonnet 5.5 10; both 1M context
CheapestGemini 3.1 Flash-Lite: 1.50; 2.5 Flash-Lite: 0.40Haiku 4.5, claude-haiku-4-5: 5, 200K context
Media modelsImage generation and editing (Nano Banana 2), Live voice, TTS, transcription, music, and video modelsNo image, audio, or video generation
Batch and caching50 percent batch discount; cached input billed at a reduced rate50 percent batch discount; cache reads at 10 percent of input (5 percent on Opus 5.5, 2.5 percent on Fable 5.1)
CloudsGemini API and Google CloudClaude API, Amazon Bedrock, Google Cloud Vertex AI, Microsoft Foundry, Claude Platform on AWS

Pick Gemini when

Pick Gemini for media-rich and cost-sensitive workloads.

  • Products that need generated images, voice agents, speech-to-text, or video in one vendor.
  • High-volume, latency-tolerant work on Flash or Flash-Lite tiers, where list price dominates; compare cost per completed task.
  • Prototyping on the free tier, or stacks centered on Google Cloud.
  • Plan for preview status: gemini-3.1-pro-preview is a preview model, and Flash pricing doubles on 2027-01-01.

Pick Claude when

Pick Claude for agent reliability and deployment flexibility.

  • Long-running, tool-using agents and coding work; start on Opus 5.5 and escalate to Fable 5.1 when evals at higher effort fall short.
  • Procurement through Bedrock, Vertex AI, or Foundry, or US-only inference on the Claude API with inference_geo (1.1x price).
  • Strict tool schemas and structured outputs; see structured-output.

Run both

Put a router in front, keep prompts per provider, and run a shared eval suite before moving traffic (evaluation). Parameters differ across models, so do not carry sampling settings between providers; see claude-vs-gpt for the Claude constraints. Track spend per task type (cost-control).

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