Gemini 3.1 Pro vs Claude Opus 5.5
Choose by what you are feeding it. Gemini 3.1 Pro reads video and audio and is strong at abstract reasoning; Opus 5.5 is the better long-running worker and knows far more recent events — its knowledge runs to mid-2026, Gemini’s to January 2025.
Choose Gemini 3.1 Pro if
- Your material is video, audio or a mix of media.
- Abstract reasoning puzzles — 77.1% on ARC-AGI-2 at launch.
- Answers of up to about 65K tokens are enough.
Choose Claude Opus 5.5 if
- Long coding sessions and code review.
- Work that depends on recent knowledge.
- You want a generally available model rather than a preview.
Side by side
| Gemini 3.1 Pro | Claude Opus 5.5 | |
|---|---|---|
| Made by | Anthropic | |
| Released | February 2026 | September 2026 |
| Input price, per 1M tokens | A$3.03 | A$6.06 |
| Output price, per 1M tokens | A$18.17 | A$30.28 |
| Cached input, per 1M tokens | A$0.3028 | A$0.3028 |
| Batch (about half price) | Yes | Yes |
| Context window | 1.05M tokens | 1M tokens |
| Longest answer | 66K tokens | 128K tokens |
| Reads | Text, Images, Audio, Video, PDFs | Text, Images, PDFs |
| Thinks before answering | Always on | Always on |
| Open weights | No | No |
Prices are Roar AI’s published rates, live from our price list. Specs are each lab’s own published figures. Prices are our published US dollar rates converted at A$1.47 to the dollar, our rate for October — the same rate your card is charged.
What a real job costs
Take 1,000 requests, each about 3,000 tokens in and 1,000 out — a long prompt and a page of answer.
Gemini 3.1 Pro does the same job for 1.8× less. Models that think before answering spend extra output tokens doing it, so on hard prompts the real gap can be wider than the rates suggest.
Use both, switch any time
On Roar AI both are on the same key and the same monthly invoice, paid in your local currency. Trying the other one is a one-word change:
client.chat.completions.create(model="gemini-3.1-pro", …) client.chat.completions.create(model="claude-opus-5-5", …)
Send the same prompts to both for a day and compare the answers on your own work — that settles it faster than any benchmark. Read the docs.
Try both
on one key
Send the same prompts to each and compare the answers on your own work.