How big is the price gap really?
Big enough to restructure a budget around. GPT-5.5 charges $5/Mtok input and $30/Mtok output. Gemini 3.1 Pro charges $2 and $12. That's a 60% discount on both sides.
Concretely: a workload of 1M input and 200K output tokens per day costs about $330/month on GPT-5.5 and about $132/month on Gemini 3.1 Pro. Scale that to ten times the traffic and you're comparing $3,300 against $1,320 every month. At volume, this gap is the argument; everything else on this page is a caveat to it.
What does Gemini's preview status mean for you?
The "preview" suffix is not decoration. Google has repeatedly adjusted pricing, rate limits, and model behavior between preview and general availability. Building a cost model on preview pricing is a gamble, and quietly shifting behavior can silently change your product's output quality.
That doesn't mean avoid it. It means: run it where regressions are cheap to catch, keep your prompts portable, and don't sign long commitments against preview numbers. GPT-5.5, by contrast, is a stable GA product with predictable behavior, and for some teams that predictability is worth the premium on its own.
Which handles multimodal work better?
Not close. Gemini 3.1 Pro accepts text, images, video, audio, and PDFs natively. GPT-5.5 accepts text, images, and PDFs. If your pipeline touches video or audio at all, meeting transcripts, screen recordings, voice input, Gemini is the only one of the two that handles it without a separate transcription or frame-extraction step. Removing a preprocessing stage from a media pipeline is often worth more than the token savings.
Which is stronger for code and agents?
On paper both support reasoning, tool calling, and 1M-class context (1.05M both, effectively identical). In practice, OpenAI's ecosystem advantage shows here: more agent frameworks, more eval tooling, more third-party integrations assume an OpenAI-shaped API first. GPT-5.5 also allows 128K output tokens per response against Gemini's 65K, relevant for large single-shot generations.
For raw coding ability at this tier, both are credible flagships; neither has a decisive, universal edge that survives contact with different codebases. Your own eval numbers beat anyone's blanket claim, ours included.
When should you pick which?
Pick GPT-5.5 if:
- You need GA-grade stability and predictable behavior today
- Your stack leans on OpenAI-compatible tooling
- Single responses sometimes need more than 65K tokens
Pick Gemini 3.1 Pro if:
- Volume makes the 60% saving material
- Your inputs include video or audio
- You can tolerate preview-stage changes while it heads to GA