Gemini 3.1 Pro vs Claude Opus 4.7: large-context vs frontier pricing
Gemini 3.1 Pro is more than 2x cheaper on both inputs and outputs, representing a highly economical premium frontier tier. Claude Opus 4.7 is reserved for absolute top-tier intelligence requirements.
Large-context reasoning versus frontier flagship reasoning.
Processing complex reasoning tasks at scale requires choosing a premium model. Let's compare Gemini 3.1 Pro (<=200k) and Claude Opus 4.7 API rates.
By TechCompare · Updated
Cost Comparison
Based on 100,000 input tokens (50% cached), 5,000 output tokens, and 100 requests.
Side-by-side specs
| Spec | Gemini 3.1 Pro | Claude Opus 4.7 |
|---|---|---|
| Input Cost (per M) | $2.00 (better on this spec) | $5.00 |
| Output Cost (per M) | $12.00 (better on this spec) | $25.00 |
| Cached Input (per M) | $0.20 (better on this spec) | $0.50 |
| Batch Discount | 50% | 50% |
How they differ
Gemini 3.1 Pro (<=200k) costs $2.00 per million input tokens and $12.00 per million output tokens, with a 75% caching discount. Claude Opus 4.7 costs $5.00 per million input tokens and $25.00 per million output tokens, also with a 90% caching discount.
Verdict
Gemini wins every row: $2.00/M input against $5.00 and $12.00/M output against $25.00, both about 2.5x cheaper. The cached-input row is no exception at $0.20/M against $0.50/M despite Opus's deeper 90% discount. Batch ties at 50% on both, so the Gemini lead holds in every mode. Opus 4.7 earns its premium only on tasks where its flagship reasoning and instruction-following undo retries and catch errors the cheaper model misses.
Which should you pick?
Choose Gemini 3.1 Pro
Ultra-long context windows (up to 2M tokens), high-caching search datasets.
Choose Claude Opus 4.7
Flagship executive reasoning tasks, multi-step code planning, and maximum logical accuracy.