Anthropic vs Google Gemini
Side-by-side — pricing, strengths, tradeoffs, and fit.
Free TierEnterprise
● Established·From $0.25/1M input tokens (Haiku)
Free TierEnterprise
◐ Growing·From $0.075/1M input tokens (Flash)
One-liner
One-liner
AI safety company building Claude, the helpful, harmless, and honest AI assistant.
One-liner
Google’s multimodal LLM family with long context, via the Gemini API and Vertex AI.
Maturity
Open source
Free tier
Free tier
✓ AvailableFree tier on claude.ai with rate limits. API has pay-as-you-go pricing
Free tier
✓ AvailableFree tier on Google AI Studio with rate limits
Starts at
Starts at
$0.25/1M input tokens (Haiku)
Starts at
$0.075/1M input tokens (Flash)
Model
Enterprise
✓ Best for
Applications requiring long document analysis200K context window handles entire codebases and long documents without chunking
Enterprise AI deployments needing safety guaranteesConstitutional AI training produces more predictable and steerable outputs
Coding assistants and developer toolsTop-tier code generation with strong instruction following and tool use
✓ Best for
Multimodal and long-context tasksMillion-token context and native media
Teams on Google CloudNative Vertex AI deployment
✕ Not for
Image or video generationText-only output — pair with image generation models for multimodal applications
Latency-critical applications needing sub-100ms responsesLLM inference has inherent latency; Haiku is fastest but still ~200ms for short prompts
↑ Strengths
Best-in-class long context handling (200K tokens)
Industry-leading coding capabilities
Strong safety alignment with Constitutional AI
Excellent tool use and structured output
↑ Strengths
Very long context windows
Natively multimodal
Competitive pricing (Flash)
↓ Weaknesses
No image generation or multimodal output
Limited availability in some regions
Higher cost for Opus tier compared to competitors
↓ Weaknesses
Free tier users' content is used to train and improve Google's products.
Grounding with Google Search is unavailable on the free tier.
Free tier access is limited to specific models.