Gemini 3.1 Pro Preview vs GPT-5.2 Pro
Both are current frontier models, released three months apart (GPT-5.2 Pro on 2025-12-10, Gemini 3.1 Pro Preview on 2026-02-19). The gap that matters isn't intelligence — it's price and context. Gemini costs a fraction of GPT-5.2 Pro per token and handles over 2.6x the input length, while GPT-5.2 Pro counters with a wider reasoning-effort range and a larger max output. Both run on OpenKey with one key and a flat 3% fee on top of provider pricing.
Spec vs spec
| Spec | Gemini 3.1 Pro Preview | GPT-5.2 Pro |
|---|---|---|
| Context window | 1.0M | 400K |
| Max output | 66K | 128K |
| Input modalities | audio, file, image, text, video | image, text, file |
| Output modalities | text | text |
| Released | Feb 19, 2026 | Dec 10, 2025 |
| Reasoning | always on | always on |
Pricing
Per 1M tokens. Provider price plus the flat 3% fee — the sum is what you pay.
google/gemini-3.1-pro-preview
Input · 1M tokens
$2.00 + 3%$2.06
Output · 1M tokens
$12.00 + 3%$12.36
Cache read · 1M tokens
$0.200 + 3%$0.206
Cache write · 1M tokens
$0.375 + 3%$0.386
FEE — FLAT, EVERY MODEL3%
openai/gpt-5.2-pro
Input · 1M tokens
$21.00 + 3%$21.63
Output · 1M tokens
$168.00 + 3%$173.04
FEE — FLAT, EVERY MODEL3%
One workload, priced on both
10M input + 2M output tokens at each model's price, flat 3% fee included.
google/gemini-3.1-pro-previewCheaper
$45.32
$44.00 provider + 3%
openai/gpt-5.2-pro
$562.38
$546.00 provider + 3%
Pricing math on a real workload
Take a 10M-input / 2M-output job — a reasonable stand-in for a batch coding or document-processing run. On OpenKey, Gemini 3.1 Pro Preview costs $44.00 for that workload; GPT-5.2 Pro costs $546.00. That's a 12.4x difference for the same shape of job.
The per-token math: Gemini's provider price is $2.00/M input and $12.00/M output; OpenKey adds the flat 3% fee, landing at $2.06/M input and $12.36/M output. GPT-5.2 Pro's provider price is $21.00/M input and $168.00/M output, becoming $21.63/M input and $173.04/M output on OpenKey ($21.00 × 1.03 and $168.00 × 1.03). The input price ratio is 0.1 — Gemini's input tokens cost one-tenth of GPT-5.2 Pro's. Gemini also supports cache reads at $0.20/M and cache writes at $0.375/M provider-side; GPT-5.2 Pro has no listed cache pricing in this data.
Context and output limits
Gemini 3.1 Pro Preview accepts up to 1,048,576 tokens of context — 2.62x GPT-5.2 Pro's 400,000-token window. If your workload involves ingesting large codebases, long transcripts, or multi-document retrieval in a single call, Gemini's window gives you more room before you need to chunk or summarize.
GPT-5.2 Pro wins on the output side: it can generate up to 128,000 tokens per response versus Gemini's 65,536. For tasks that produce very long single outputs — extensive reports, full applications generated in one pass — GPT-5.2 Pro's ceiling is roughly double.
Coding and agentic benchmarks
The research data includes Design Arena and Artificial Analysis scores for Gemini 3.1 Pro Preview but no benchmark data for GPT-5.2 Pro, so a head-to-head score comparison isn't possible here — treat GPT-5.2 Pro's real-world coding performance as unverified against this dataset.
What we do have: Gemini 3.1 Pro Preview posts an Artificial Analysis coding index of 68.8, an intelligence index of 46.5, and an agentic index of 21.4. On Design Arena's model-level categories it ranks well in SVG generation (rank 2, 70.3% win rate) and ASCII art (rank 4, 63.4% win rate), with weaker showings in game dev (rank 26) and 3D (rank 17). In the agent-arena categories it's mid-pack — rank 5 on agentic HTML slides, rank 25 on Android-native tasks.
Reasoning effort and modalities
Both models require reasoning mode — it's mandatory, not optional. Gemini 3.1 Pro Preview offers low, medium, and high effort (default: medium). GPT-5.2 Pro offers medium, high, and xhigh (default: medium), giving it a top tier Gemini doesn't have — relevant if you need to push reasoning depth beyond what Gemini's high setting delivers.
Modality is the other split. Gemini accepts audio, file, image, text, and video input; GPT-5.2 Pro accepts image, text, and file only. If your pipeline needs audio or video input directly (not pre-transcribed), Gemini is the only option of the two. Both output text only.
Which model for which job
| Use case | Pick | Why |
|---|---|---|
| High-volume batch coding jobs | Gemini 3.1 Pro Preview | $44.00 vs $546.00 on a 10M-in/2M-out workload — a 12.4x cost difference |
| Long-document or large-codebase ingestion | Gemini 3.1 Pro Preview | 1,048,576-token context is 2.62x GPT-5.2 Pro's 400,000-token limit |
| Audio or video input pipelines | Gemini 3.1 Pro Preview | Only model of the two with audio and video input modalities |
| Single-response very long output (full app, long report) | GPT-5.2 Pro | 128,000 max output tokens vs Gemini's 65,536 |
| Tasks needing maximum reasoning depth | GPT-5.2 Pro | Only model offering an xhigh reasoning effort tier |
| Cost-sensitive prototyping with caching | Gemini 3.1 Pro Preview | Provider-side cache read at $0.20/M and cache write at $0.375/M; GPT-5.2 Pro has no listed cache pricing |
Questions
- How much cheaper is Gemini 3.1 Pro Preview than GPT-5.2 Pro?
- On a 10M-input/2M-output workload, Gemini costs $44.00 on OpenKey versus $546.00 for GPT-5.2 Pro — a 12.4x difference. The input price ratio alone is 0.1, meaning Gemini's input tokens cost one-tenth of GPT-5.2 Pro's per-token rate.
- Which model has a bigger context window?
- Gemini 3.1 Pro Preview supports 1,048,576 tokens of context, 2.62x GPT-5.2 Pro's 400,000-token limit. If you're processing large codebases or long documents in one call, Gemini gives you more headroom before chunking.
- Can I compare coding benchmarks directly?
- Not fully. This dataset has Design Arena and Artificial Analysis scores for Gemini 3.1 Pro Preview (coding index 68.8, intelligence index 46.5) but no equivalent benchmark data for GPT-5.2 Pro, so a direct numeric comparison isn't possible from these inputs.
- What reasoning effort levels does each model support?
- Gemini 3.1 Pro Preview offers low, medium, and high effort, defaulting to medium. GPT-5.2 Pro offers medium, high, and xhigh, also defaulting to medium — its xhigh tier is the one option Gemini doesn't have.