Gemini 3.1 Pro vs Gemini 2.0 Pro

Both models come from Google, so they share a tokenizer, an API surface, and a billing account. Switching between them is a model-string change and nothing else — no new SDK, no re-tokenizing your prompts to re-estimate cost, no second vendor to onboard. That makes routing between them far cheaper to implement than a cross-vendor split.

These are the same lab's model at the same tier, 12 months apart — so this is an upgrade question, not a choice between alternatives. Gemini 3.1 Pro is the current entry; Gemini 2.0 Pro is here because plenty of production traffic still runs on it. If you are starting something new there is little reason to pick the older one, and if you are already on it the question is whether the migration cost is worth the gain.

Gemini 2.0 Pro carries the larger context window at 2.0M tokens versus 1.0M for Gemini 3.1 Pro. The gap is real but not decisive — it matters if your prompts routinely run long, and is irrelevant if they sit where most production prompts sit, well under 100K. Bear in mind that filling a large window is also what makes a request expensive.

Throughput is close enough to ignore — 83/100 versus 82/100. Neither model will feel noticeably quicker in an interactive product, so latency is not a reason to choose between them.

One practical asymmetry: Gemini 3.1 Pro offers a batch API at 50% off standard rates, and Gemini 2.0 Pro does not. For anything that does not need an answer immediately — nightly enrichment, backfills, evaluation runs — that discount can be worth more than the difference in list price, and it is easy to overlook when comparing headline rates.