Gemini 3.1 Pro Preview vs GPT-6.1 Sol
Too close to call on our weighted score (GPT-6.1 Sol 69, Gemini 3.1 Pro Preview 66). The right pick depends on what you value most.
GoogleGemini 3.1 Pro Preview
66/100- ECI154.8
- Price$2.00 / $12.00
- Context1.05M
OpenAIGPT-6.1 Sol
69/100- ECI—
- Price$2.00 / $10.00
- Context1.05M
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Make it a three-way comparison.
Too close to call
It is close. Our weighted score puts them within 3 points (GPT-6.1 Sol 69/100, Gemini 3.1 Pro Preview 66/100), so choose by what matters most for your work: GPT-6.1 Sol for raw capability. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%. Capability uses the average of shared benchmarks (GPQA Diamond, FrontierMath Tiers 1–3, OTIS Mock AIME 2024–2025 and SimpleQA Verified), because GPT-6.1 Sol has no Capabilities Index score yet.
- CapabilityGPT-6.1 SolShared benchmarks: GPT-6.1 Sol 90.7% · Gemini 3.1 Pro Preview 80.8%
- Lowest priceGPT-6.1 SolGPT-6.1 Sol $4.00 · Gemini 3.1 Pro Preview $4.50 per 1M tokens (3:1 blend)
- Longest contextAbout the sameGPT-6.1 Sol 1,050,000 · Gemini 3.1 Pro Preview 1,048,576 tokens
- Widest inputsGemini 3.1 Pro PreviewGemini 3.1 Pro Preview: Text, Images, PDFs, Audio, Video · GPT-6.1 Sol: Text, Images, PDFs
- Self-hostingNo open weightsBoth are available only through APIs
| Measure | Weight | Gemini 3.1 Pro Preview | GPT-6.1 Sol |
|---|---|---|---|
| CapabilityShared benchmarks | 50% | 81 | 91 |
| Price | 25% | 19 | 21 |
| Inputs & features | 15% | 100 | 80 |
| Context window | 10% | 61 | 61 |
| Overall | 100% | 66/100 | 69/100 |
Every spec in one table
Highlighted cells lead their row. Dashes mean the data is not published.
| Specification | Gemini 3.1 Pro PreviewGoogle | GPT-6.1 SolOpenAI |
|---|---|---|
| Capability | ||
| Capabilities Index (ECI) | 154.8 | — |
| ECI rank | #31 of 148 | — |
| GPQA DiamondGraduate-level science questions | 94.4% | 95.4% (best) |
| FrontierMath Tiers 1–3Research-level mathematics | 59.7% | 93.7% (best) |
| OTIS Mock AIME 2024–2025Competition mathematics | 95.6% | 100% (best) |
| SWE-bench VerifiedFixing real GitHub issues | 75.6% | — |
| SimpleQA VerifiedShort factual questions | 73.5% | 73.9% (best) |
| Price per million tokens | ||
| Input | $2.00 | $2.00 |
| Output | $12.00 | $10.00 (best) |
| Cached input | $0.20 | $0.10 (best) |
| Blended (3:1) | $4.50 | $4.00 (best) |
| Long-context rate | Over 200K: $4.00 / $18.00 | Over 272K: $4.00 / $15.00 |
| Price source | Official Google API | Official OpenAI API |
| Limits | ||
| Context window | 1,048,576 tokens | 1,050,000 tokens (best) |
| Max output | 65,536 tokens | 128,000 tokens (best) |
| Inputs and features | ||
| Text | Yes | Yes |
| Images | Yes | Yes |
| PDFs | Yes | Yes |
| Audio | Yes | No |
| Video | Yes | No |
| Reasoning | Yeslow · medium · high | Yeslow · medium · high · xhigh · max |
| Tool calling | Yes | Yes |
| Structured output | Yes | Yes |
| Availability | ||
| Weights | Proprietary | Proprietary |
| API model ID | gemini-3.1-pro-preview | gpt-6.1-sol |
| API providers | 26 (best) | 21 |
| Released | Feb 19, 2026 | Sep 29, 2026 |
| Knowledge cutoff | Jan 2025 | Apr 30, 2026 |
What would a month cost?
Enter your expected volume in millions of tokens. List prices only; caching and batch discounts would lower these.
- Gemini 3.1 Pro Preview$44.00
- GPT-6.1 Sol$40.00
Which should you choose?
Which is better: Gemini 3.1 Pro Preview or GPT-6.1 Sol?
It is close. Our weighted score puts them within 3 points (GPT-6.1 Sol 69/100, Gemini 3.1 Pro Preview 66/100), so choose by what matters most for your work: GPT-6.1 Sol for raw capability. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%. Capability uses the average of shared benchmarks (GPQA Diamond, FrontierMath Tiers 1–3, OTIS Mock AIME 2024–2025 and SimpleQA Verified), because GPT-6.1 Sol has no Capabilities Index score yet.
Which is cheaper, Gemini 3.1 Pro Preview or GPT-6.1 Sol?
GPT-6.1 Sol is cheaper at $2.00 input / $10.00 output per million tokens (official OpenAI API price). Gemini 3.1 Pro Preview costs $2.00 input / $12.00 output per million tokens (official Google API price). At a typical mix of three input tokens to one output token, that is $4.00 per million tokens for GPT-6.1 Sol versus $4.50 for Gemini 3.1 Pro Preview (1.1× as much).
Which scores higher on benchmarks?
Not every model here has a Capabilities Index score, so we compare the average of shared benchmarks (GPQA Diamond, FrontierMath Tiers 1–3, OTIS Mock AIME 2024–2025 and SimpleQA Verified): GPT-6.1 Sol 90.7% and Gemini 3.1 Pro Preview 80.8%. On individual benchmarks: GPQA Diamond — GPT-6.1 Sol 95.4%, Gemini 3.1 Pro Preview 94.4%; FrontierMath Tiers 1–3 — GPT-6.1 Sol 93.7%, Gemini 3.1 Pro Preview 59.7%; OTIS Mock AIME 2024–2025 — GPT-6.1 Sol 100%, Gemini 3.1 Pro Preview 95.6%; SimpleQA Verified — GPT-6.1 Sol 73.9%, Gemini 3.1 Pro Preview 73.5%.
Which is better for coding?
There are no published SWE-bench Verified results for GPT-6.1 Sol yet, so there is no like-for-like coding score. On overall capability, GPT-6.1 Sol leads, which tends to carry over to coding, but test on your own codebase. Both support tool calling for agent workflows.
Which has the bigger context window?
Their context windows are effectively the same size: Gemini 3.1 Pro Preview 1,048,576 and GPT-6.1 Sol 1,050,000 tokens. Maximum output per response: Gemini 3.1 Pro Preview up to 65,536, GPT-6.1 Sol up to 128,000 tokens.
Which can read images, PDFs, audio or video?
Gemini 3.1 Pro Preview accepts text, images, PDFs, audio and video; GPT-6.1 Sol accepts text, images and PDFs. Gemini 3.1 Pro Preview handles the widest range of inputs.
Are any of these open source?
No. Gemini 3.1 Pro Preview and GPT-6.1 Sol are proprietary and only available through APIs and apps.
Which is newer?
GPT-6.1 Sol is the newest, released Sep 29, 2026. Gemini 3.1 Pro Preview came out Feb 19, 2026. Knowledge cutoff: Gemini 3.1 Pro Preview Jan 2025, GPT-6.1 Sol Apr 30, 2026.
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.
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