Claude vs Gemini: Limits, Lineup & Integrations Compared
Anthropic’s Claude and Google’s Gemini compared on what each provider documents: current models, limits, stability, and where each is available.
| Evaluation Parameter | Anthropic Claude | Google Gemini |
|---|---|---|
| Current lineup | Fable 5.1, Opus 5.5, Sonnet 5.5, Haiku 5.5 | Gemini 4 Argon (flagship), Gemini 3.x Flash and Flash-Lite |
| Context window | 1M tokens on current models | 1M tokens on Gemini 4 Argon |
| Max output | 128K tokens | Up to 1M tokens on Gemini 4 Argon |
| Input types (API) | Text and image | Varies by model; the family includes live-audio and transcription models |
| Model stability | Current models have retirement dates no sooner than Sept 2027 | Several Gemini 3 models are still preview; older ones are shut down |
| Platform availability | Claude API, Amazon Bedrock, Google Cloud, Microsoft Foundry | Gemini API and Google Cloud |
| Coding and writing quality | Positioned for agentic coding and knowledge work | Positioned by Google as its flagship reasoning model |
Context and output
Both providers list a one-million-token context window on their flagship models, so raw context size no longer separates them. The difference is output: Google describes Gemini 4 Argon as supporting outputs up to 1M tokens, while every current Claude model lists a 128K maximum. That matters for tasks that generate very large documents or codebases in a single response.
Stability and lifecycle
Anthropic lists retirement dates no sooner than September 2027 for its current models. Google’s model list shows several Gemini 3 models still in preview and a number of older models already shut down, so plan for model IDs to change if you build on Gemini.
How to choose
- Need very long single outputs? Check Gemini 4 Argon’s output limit against your use case.
- Building on Google Cloud or Workspace? Gemini integrates natively. Claude is also available through Google Cloud, as well as Amazon Bedrock and Microsoft Foundry.
- Judging quality? Run both on your own tasks. We have not published a reproducible test, so we do not name a winner on coding or writing.