GPT-6 Sol vs Gemini 3.1 Pro Preview
Too close to call on our weighted score (GPT-6 Sol 67, Gemini 3.1 Pro Preview 66). The right pick depends on what you value most.
OpenAIGPT-6 Sol
67/100- ECI—
- Price$2.00 / $10.00
- Context1.05M
GoogleGemini 3.1 Pro Preview
66/100- ECI154.8
- Price$2.00 / $12.00
- 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 a point (GPT-6 Sol 67/100, Gemini 3.1 Pro Preview 66/100), so choose by what matters most for your work: GPT-6 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 Sol has no Capabilities Index score yet.
- CapabilityGPT-6 SolShared benchmarks: GPT-6 Sol 86.2% · Gemini 3.1 Pro Preview 80.8%
- Lowest priceGPT-6 SolGPT-6 Sol $4.00 · Gemini 3.1 Pro Preview $4.50 per 1M tokens (3:1 blend)
- Longest contextAbout the sameGPT-6 Sol 1,050,000 · Gemini 3.1 Pro Preview 1,048,576 tokens
- Widest inputsGemini 3.1 Pro PreviewGPT-6 Sol: Text, Images, PDFs · Gemini 3.1 Pro Preview: Text, Images, PDFs, Audio, Video
- Self-hostingNo open weightsBoth are available only through APIs
| Measure | Weight | GPT-6 Sol | Gemini 3.1 Pro Preview |
|---|---|---|---|
| CapabilityShared benchmarks | 50% | 86 | 81 |
| Price | 25% | 21 | 19 |
| Inputs & features | 15% | 80 | 100 |
| Context window | 10% | 61 | 61 |
| Overall | 100% | 67/100 | 66/100 |
Every spec in one table
Highlighted cells lead their row. Dashes mean the data is not published.
| Specification | GPT-6 SolOpenAI | Gemini 3.1 Pro PreviewGoogle |
|---|---|---|
| Capability | ||
| Capabilities Index (ECI) | — | 154.8 |
| ECI rank | — | #31 of 148 |
| GPQA DiamondGraduate-level science questions | 94.3% | 94.4% (best) |
| FrontierMath Tiers 1–3Research-level mathematics | 89.8% (best) | 59.7% |
| OTIS Mock AIME 2024–2025Competition mathematics | 100% (best) | 95.6% |
| SWE-bench VerifiedFixing real GitHub issues | — | 75.6% |
| SimpleQA VerifiedShort factual questions | 60.7% | 73.5% (best) |
| Price per million tokens | ||
| Input | $2.00 | $2.00 |
| Output | $10.00 (best) | $12.00 |
| Cached input | $0.20 | $0.20 |
| Blended (3:1) | $4.00 (best) | $4.50 |
| Long-context rate | Over 272K: $4.00 / $15.00 | Over 200K: $4.00 / $18.00 |
| Price source | Official OpenAI API | Official Google API |
| Limits | ||
| Context window | 1,050,000 tokens (best) | 1,048,576 tokens |
| Max output | 128,000 tokens (best) | 65,536 tokens |
| Inputs and features | ||
| Text | Yes | Yes |
| Images | Yes | Yes |
| PDFs | Yes | Yes |
| Audio | No | Yes |
| Video | No | Yes |
| Reasoning | Yeslow · medium · high · xhigh · max | Yeslow · medium · high |
| Tool calling | Yes | Yes |
| Structured output | Yes | Yes |
| Availability | ||
| Weights | Proprietary | Proprietary |
| API model ID | gpt-6-sol | gemini-3.1-pro-preview |
| API providers | 25 | 26 (best) |
| Released | Sep 22, 2026 | Feb 19, 2026 |
| Knowledge cutoff | Apr 20, 2026 | 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-6 Sol$40.00
- Gemini 3.1 Pro Preview$44.00
Which should you choose?
Which is better: GPT-6 Sol or Gemini 3.1 Pro Preview?
It is close. Our weighted score puts them within a point (GPT-6 Sol 67/100, Gemini 3.1 Pro Preview 66/100), so choose by what matters most for your work: GPT-6 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 Sol has no Capabilities Index score yet.
Which is cheaper, GPT-6 Sol or Gemini 3.1 Pro Preview?
GPT-6 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 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 Sol 86.2% and Gemini 3.1 Pro Preview 80.8%. On individual benchmarks: GPQA Diamond — Gemini 3.1 Pro Preview 94.4%, GPT-6 Sol 94.3%; FrontierMath Tiers 1–3 — GPT-6 Sol 89.8%, Gemini 3.1 Pro Preview 59.7%; OTIS Mock AIME 2024–2025 — GPT-6 Sol 100%, Gemini 3.1 Pro Preview 95.6%; SimpleQA Verified — Gemini 3.1 Pro Preview 73.5%, GPT-6 Sol 60.7%.
Which is better for coding?
There are no published SWE-bench Verified results for GPT-6 Sol yet, so there is no like-for-like coding score. On overall capability, GPT-6 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: GPT-6 Sol 1,050,000 and Gemini 3.1 Pro Preview 1,048,576 tokens. Maximum output per response: GPT-6 Sol up to 128,000, Gemini 3.1 Pro Preview up to 65,536 tokens.
Which can read images, PDFs, audio or video?
GPT-6 Sol accepts text, images and PDFs; Gemini 3.1 Pro Preview accepts text, images, PDFs, audio and video. Gemini 3.1 Pro Preview handles the widest range of inputs.
Are any of these open source?
No. GPT-6 Sol and Gemini 3.1 Pro Preview are proprietary and only available through APIs and apps.
Which is newer?
GPT-6 Sol is the newest, released Sep 22, 2026. Gemini 3.1 Pro Preview came out Feb 19, 2026. Knowledge cutoff: GPT-6 Sol Apr 20, 2026, Gemini 3.1 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.
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