Google: Gemini 3.1 Pro Preview
google/gemini-3.1-pro-preview
Our take
AI-assisted analysis based on the sources below. Suitability is an editorial assessment; test it on your own workload.
According to the OpenRouter catalog, google/gemini-3.1-pro-preview is a Google preview model that accepts text, image, file, audio, and video inputs and returns text, with a context window of about one million tokens. Reasoning is mandatory, with low, medium, and high effort settings, and the catalog lists support for tools, structured outputs, and response formats. Google's catalog description positions it as a frontier reasoning model for software engineering and agentic work, while Design Arena and Artificial Analysis figures published there offer some measured results. An independent model card was not available in this source pack.[1]
Strengths
- The catalog lists a wide multimodal input set (text, image, file, audio, video) paired with a roughly one-million-token context window, suiting long or media-heavy prompts.[1]
- Reasoning effort is adjustable across low, medium, and high settings, and the parameter list includes tools, tool choice, structured outputs, seeds, and response formats for controlled integrations.[1]
- Catalog-published Design Arena results are comparatively stronger in visual and front-end categories such as SVG and UI components than in areas like spreadsheets, per the reported entries.[1]
Limitations
- All evidence comes from the OpenRouter catalog only; no independent model card or vendor documentation was included, so capabilities and reported figures should be validated on real workloads.[1]
- Reasoning is listed as mandatory and internal reasoning is billed separately, which may add latency and cost that cannot be switched off.[1]
- Knowledge cutoff, license terms, hardware needs, and release status beyond the preview label are not stated, and the reported agentic index is modest relative to the coding index in the same catalog data.[1]
Where to use it
- Analysis of long documents or mixed media, where the large context window and audio/video inputs could help, subject to workload testing.[1]
- Front-end and visual prototyping tasks such as UI components or SVG generation, where catalog-reported arena results look relatively favorable.[1]
- Structured or tool-calling pipelines that benefit from response formats, JSON schema output, and tunable reasoning effort.[1]
Sources
- [1] OpenRouter catalog · Google: Gemini 3.1 Pro PreviewSources checked: Nov 13, 2026
About this model
Description below is the original text supplied by OpenRouter, shown in the source language.
Gemini 3.1 Pro Preview is Google’s frontier reasoning model, delivering enhanced software engineering performance, improved agentic reliability, and more efficient token usage across complex workflows. Building on the multimodal foundation...
Specifications
- Model ID
- google/gemini-3.1-pro-preview
- Canonical ID
- google/gemini-3.1-pro-preview-20260219
- Creator
- Added to OpenRouter
- 19.02.2026
- Context length
- 1,048,576
- Modality
- text+image+file+audio+video->text
- Input modalities
- audio, file, image, text, video
- Output modalities
- text
- Token pricing
- USD per 1M tokens: in $2 / out $12
- Knowledge cutoff
- —
- Expiration date
- —
Tasks and capabilities
A grade appears only where the source supplies a matching measurement for that task, the model is active and the cohort holds at least 10 comparable models. The capability column lists facts the source declares — supported formats, reasoning and tool parameters — which are not measured quality.
| Task | Grade | Source-declared capability |
|---|---|---|
| General quality | No measurement | reasoning: mandatory · default medium · efforts: high, medium, low · parameters: include_reasoning, reasoning, reasoning_effort |
| Coding | AA — next 20% of the cohort | — |
| Agents | CC — below the B band | parameters: structured_outputs, tool_choice, tools |
| Writing | No measurement | output: text |
| Reasoning | No measurement | reasoning: mandatory · default medium · efforts: high, medium, low · parameters: include_reasoning, reasoning, reasoning_effort |
| Document analysis | No measurement | input: file |
| Vision | No measurement | input: image |
| Image generation | No measurement | — |
| Audio | No measurement | input: audio |
| Video | No measurement | input: video |
| Embeddings | No measurement | — |
Evaluations
| Source | Benchmark | Value | Grade | Data retrieved |
|---|---|---|---|---|
| Artificial Analysis | Coding index | 68.8 | AA — next 20% of the cohort | 13.11.2026 |
| Artificial Analysis | Agentic index | 8.2 | CC — below the B band | 13.11.2026 |
| Design Arena | agents · agenticgamedevwin rate 43.9% · rank 23 | 1,061Elo | CC — below the B band | 13.11.2026 |
| Design Arena | agents · agentichtmlslideswin rate 55.8% · rank 4 | 1,226Elo | —Not rated | 13.11.2026 |
| Design Arena | agents · agenticslideswin rate 33.8% · rank 7 | 1,112Elo | —Not rated | 13.11.2026 |
| Design Arena | agents · agenticslides(html)win rate 54.4% · rank 4 | 1,219Elo | —Not rated | 13.11.2026 |
| Design Arena | agents · agenticslides(python-pptx)win rate 33.9% · rank 7 | 1,107Elo | —Not rated | 13.11.2026 |
| Design Arena | agents · androidnativewin rate 41.1% · rank 40 | 1,035Elo | CC — below the B band | 13.11.2026 |
| Design Arena | agents · blender3dwin rate 39.8% · rank 18 | 1,037Elo | CC — below the B band | 13.11.2026 |
| Design Arena | agents · codetovideowin rate 44.8% · rank 15 | 1,122Elo | CC — below the B band | 13.11.2026 |
| Design Arena | agents · fullstackwin rate 40.5% · rank 34 | 1,047Elo | CC — below the B band | 13.11.2026 |
| Design Arena | agents · godotgamedevwin rate 54.4% · rank 19 | 1,145Elo | BB — next 30% of the cohort | 13.11.2026 |
| Design Arena | agents · htmlslideswin rate 48.5% · rank 18 | 1,048Elo | CC — below the B band | 13.11.2026 |
| Design Arena | agents · mobileappswin rate 42.3% · rank 42 | 1,088Elo | CC — below the B band | 13.11.2026 |
| Design Arena | agents · pdfwin rate 39.7% · rank 29 | 1,107Elo | CC — below the B band | 13.11.2026 |
| Design Arena | agents · pptxslideswin rate 34.1% · rank 7 | 1,110Elo | —Not rated | 13.11.2026 |
| Design Arena | agents · python-pptxslideswin rate 31.9% · rank 25 | 1,109Elo | CC — below the B band | 13.11.2026 |
| Design Arena | agents · spreadsheetwin rate 32.5% · rank 28 | 1,020Elo | CC — below the B band | 13.11.2026 |
| Design Arena | agents · webappswin rate 44.2% · rank 35 | 1,108Elo | CC — below the B band | 13.11.2026 |
| Design Arena | models · 3dwin rate 58.5% · rank 46 | 1,217Elo | BB — next 30% of the cohort | 13.11.2026 |
| Design Arena | models · asciiartwin rate 63.5% · rank 14 | 1,265Elo | AA — next 20% of the cohort | 13.11.2026 |
| Design Arena | models · codecategorieswin rate 64.4% · rank 48 | 1,234Elo | BB — next 30% of the cohort | 13.11.2026 |
| Design Arena | models · datavizwin rate 61.8% · rank 40 | 1,237Elo | BB — next 30% of the cohort | 13.11.2026 |
| Design Arena | models · gamedevwin rate 52.4% · rank 60 | 1,192Elo | BB — next 30% of the cohort | 13.11.2026 |
| Design Arena | models · svgwin rate 67.9% · rank 13 | 1,276Elo | AA — next 20% of the cohort | 13.11.2026 |
| Design Arena | models · uicomponentwin rate 69.4% · rank 32 | 1,271Elo | AA — next 20% of the cohort | 13.11.2026 |
| Design Arena | models · websitewin rate 64.4% · rank 47 | 1,245Elo | BB — next 30% of the cohort | 13.11.2026 |
How grades work
Each letter grade compares a model only against other models scored by the same source and metric in the current snapshot. S means the top 10%, A the next 20%, B the next 30%, C the rest. Models without a published measurement are shown as not rated — a supported format alone never implies measured quality.
- S — S — top 10% of the cohort
- A — A — next 20% of the cohort
- B — B — next 30% of the cohort
- C — C — below the B band
Providers
Optional live provider statistics from OpenRouter. Missing values are unknown, not zero.
| Provider | Context length | Price in /1M | Price out /1M | Latency p50 (30m, s) | Throughput p50 (30m, tok/s) | Uptime (30m) |
|---|---|---|---|---|---|---|
| 1,048,576 | $1 | $6 | — | — | — | |
| Google AI Studio | 1,048,576 | $1 | $6 | — | — | 100% |
| 1,048,576 | $2 | $12 | — | — | 100% | |
| Google AI Studio | 1,048,576 | $2 | $12 | — | — | 100% |
| 1,048,576 | $3.6 | $21.6 | — | — | 100% | |
| Google AI Studio | 1,048,576 | $3.6 | $21.6 | — | — | — |
Provider data retrieved: 13.11.2026
Related articles
No published articles identify this model yet.