Google Gemini 2.0 Pro on Vertex AI — 1M Token Context Window at $1.25/M Tokens

Google has released Gemini 2.0 Pro on Vertex AI with a 1 million token context window — the largest context window of any generally available enterprise LLM. Standard pricing: $1.25/million input tokens and $5.00/million output tokens for prompts under 128K tokens. For 128K-1M token contexts: $2.50/$10.00. The 1M context allows processing entire codebases, entire books, or 1-2 hours of video in a single API call.

Cost comparison for 10 billion tokens/month (3:1 input:output ratio): Gemini 2.0 Pro = $4,375. Claude claude-sonnet-4-20250514 on Bedrock = $8,250. GPT-4o on Azure OpenAI = $6,875. Gemini 1.5 Flash (fast/cheap option) = $875. For GCP-native organisations, Vertex AI integration means IAM controls, VPC Service Controls and audit logs apply natively with no additional configuration.

Quality comparison: Gemini 2.0 Pro performs comparably to GPT-4o on most reasoning and coding benchmarks. It significantly outperforms GPT-4o on long-context tasks (>100K tokens) due to its superior handling of large context windows. For tasks involving large document analysis, codebase review or multi-document summarisation, Gemini 2.0 Pro is currently the strongest option.

TCOIQ Action: Run a 30-day cost comparison using your actual prompt/response logs. Estimate token counts (1 token ≈ 0.75 words). Calculate current monthly cost and compare against Gemini 2.0 Pro pricing. For most teams switching from GPT-4o to Gemini 2.0 Pro, the saving is 30-50% with no quality degradation on standard tasks. Start with non-production workloads and compare output quality before switching production.