GPT-5.2 vs GPT-5 Pro vs Gemini 3 Pro Preview
Gemini 3 Pro Preview comes out ahead, 67 to 61 and 54 on our weighted score, and it is the cheaper option too.
OpenAIGPT-5.2
61/100- ECI153.5
- Price$1.75 / $14.00
- Context400K
- OpenAI
GPT-5 Pro
54/100- ECI150.3
- Price$15.00 / $120.00
- Context400K
- Our pick
GoogleGemini 3 Pro Preview
67/100- ECI153.0
- Price$2.00 / $12.00
- Context1.05M
Gemini 3 Pro Preview is our pick
Gemini 3 Pro Preview is the better all-round choice, scoring 67/100 against GPT-5.2 (61) and GPT-5 Pro (54). It leads on inputs & features and context window. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.
- CapabilityGPT-5.2Capabilities Index (ECI): GPT-5.2 153.5 · Gemini 3 Pro Preview 153.0 · GPT-5 Pro 150.3
- Lowest priceGemini 3 Pro PreviewGemini 3 Pro Preview $4.50 · GPT-5.2 $4.81 · GPT-5 Pro $41.25 per 1M tokens (3:1 blend)
- Longest contextGemini 3 Pro PreviewGemini 3 Pro Preview 1,048,576 · GPT-5.2 400,000 · GPT-5 Pro 400,000 tokens
- Widest inputsGemini 3 Pro PreviewGPT-5.2: Text, Images · GPT-5 Pro: Text, Images · Gemini 3 Pro Preview: Text, Images, PDFs, Audio, Video
- Self-hostingNo open weightsAll three are available only through APIs
| Measure | Weight | GPT-5.2 | GPT-5 Pro | Gemini 3 Pro Preview |
|---|---|---|---|---|
| CapabilityCapabilities Index (ECI) | 50% | 83 | 78 | 82 |
| Price | 25% | 18 | 0 | 19 |
| Inputs & features | 15% | 70 | 70 | 100 |
| Context window | 10% | 44 | 44 | 61 |
| Overall | 100% | 61/100 | 54/100 | 67/100 |
Every spec in one table
Highlighted cells lead their row. Dashes mean the data is not published.
| Specification | GPT-5.2OpenAI | GPT-5 ProOpenAI | Gemini 3 Pro PreviewGoogle |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | 153.5 (best) | 150.3 | 153.0 |
| ECI rank | #38 of 148 (best) | #46 of 148 | #39 of 148 |
| GPQA DiamondGraduate-level science questions | 91.4% | — | 92.6% (best) |
| FrontierMath Tiers 1–3Research-level mathematics | 67.4% (best) | 55.8% | — |
| OTIS Mock AIME 2024–2025Competition mathematics | 96.1% (best) | — | 91.4% |
| SWE-bench VerifiedFixing real GitHub issues | 73.8% (best) | — | 72.9% |
| SimpleQA VerifiedShort factual questions | 37.1% | — | — |
| Price per million tokens | |||
| Input | $1.75 (best) | $15.00 | $2.00 |
| Output | $14.00 | $120.00 | $12.00 (best) |
| Cached input | $0.175 | — | — |
| Blended (3:1) | $4.81 | $41.25 | $4.50 (best) |
| Long-context rate | Same rate | Same rate | Same rate |
| Price source | Official OpenAI API | Official OpenAI API | Median of 2 providers |
| Limits | |||
| Context window | 400,000 tokens | 400,000 tokens | 1,048,576 tokens (best) |
| Max output | 128,000 tokens | 272,000 tokens (best) | 65,536 tokens |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | Yes | Yes | Yes |
| PDFs | No | No | Yes |
| Audio | No | No | Yes |
| Video | No | No | Yes |
| Reasoning | Yeslow · medium · high · xhigh | Yeshigh | Yes |
| Tool calling | Yes | Yes | Yes |
| Structured output | Yes | Yes | Yes |
| Availability | |||
| Weights | Proprietary | Proprietary | Proprietary |
| API model ID | gpt-5.2 | gpt-5-pro | — |
| API providers | 21 (best) | 12 | 3 |
| Released | Dec 11, 2025 | Oct 6, 2025 | Nov 18, 2025 |
| Knowledge cutoff | Aug 31, 2025 | Sep 30, 2024 | Jan 2025 |
What would a month cost?
Enter your expected volume in millions of tokens. List prices only; caching and batch discounts would lower these.
- GPT-5.2$45.50
- GPT-5 Pro$390.00
- Gemini 3 Pro Preview$44.00
Which should you choose?
Which is better: GPT-5.2, GPT-5 Pro or Gemini 3 Pro Preview?
Gemini 3 Pro Preview is the better all-round choice, scoring 67/100 against GPT-5.2 (61) and GPT-5 Pro (54). It leads on inputs & features and context window. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.
Which is cheaper, GPT-5.2, GPT-5 Pro or Gemini 3 Pro Preview?
Gemini 3 Pro Preview is cheaper at $2.00 input / $12.00 output per million tokens (median across 2 API providers). GPT-5.2 costs $1.75 input / $14.00 output per million tokens (official OpenAI API price); GPT-5 Pro costs $15.00 input / $120.00 output per million tokens (official OpenAI API price). At a typical mix of three input tokens to one output token, that is $4.50 per million tokens for Gemini 3 Pro Preview versus $4.81 for GPT-5.2 (1.1× as much) and $41.25 for GPT-5 Pro (9.2× as much).
Which scores higher on benchmarks?
GPT-5.2 scores higher on the Capabilities Index (ECI): GPT-5.2 153.5 (#38 of 148), Gemini 3 Pro Preview 153.0 (#39 of 148) and GPT-5 Pro 150.3 (#46 of 148). The confidence ranges of the top two overlap (151.7–155.4 vs 150.6–155.2), so treat the gap as small.
Which is better for coding?
There are no published SWE-bench Verified results for GPT-5 Pro yet, so there is no like-for-like coding score. On overall capability, GPT-5.2 leads, which tends to carry over to coding, but test on your own codebase. All three support tool calling for agent workflows.
Which has the bigger context window?
Gemini 3 Pro Preview has the largest context window at 1,048,576 tokens, against 400,000 for GPT-5.2 and 400,000 for GPT-5 Pro. Maximum output per response: GPT-5.2 up to 128,000, GPT-5 Pro up to 272,000, Gemini 3 Pro Preview up to 65,536 tokens.
Which can read images, PDFs, audio or video?
GPT-5.2 accepts text and images; GPT-5 Pro accepts text and images; Gemini 3 Pro Preview accepts text, images, PDFs, audio and video. Gemini 3 Pro Preview handles the widest range of inputs.
Are any of these open source?
No. GPT-5.2, GPT-5 Pro and Gemini 3 Pro Preview are proprietary and only available through APIs and apps.
Which is newer?
GPT-5.2 is the newest, released Dec 11, 2025. Gemini 3 Pro Preview came out Nov 18, 2025; GPT-5 Pro came out Oct 6, 2025. Knowledge cutoff: GPT-5.2 Aug 31, 2025, GPT-5 Pro Sep 30, 2024, Gemini 3 Pro Preview Jan 2025.
How do you decide the winner?
Each model gets a 0–100 score on capability (50%, independent benchmark results); price (25%, blended price per million tokens (3 input : 1 output), log scale); inputs & features (15%, image, PDF, audio and video input, tool calling, structured output and reasoning); context window (10%, maximum tokens per request, log scale). Dimensions missing for any model are dropped and the remaining weights rescaled, so every model is judged on the same evidence. Specs and prices come from public model listings and the labs’ own API pages; capability scores come from independent benchmark runs. Data updated Oct 4, 2026.
