Gemini 3 Pro Preview is described in preview guides and community reports as a multimodal large language model (LLM) focused on improved reasoning, native multimodal understanding (text + images + audio/video signals), and support for very long contexts for enterprise workloads.
Key features
- Native multimodal input / output: text, images, and reported audio/video handling improvements—continuing Gemini’s push into integrated multimodal tasks.
- Very large context window: preview reports cite context windows on the order of hundreds of thousands to ~1,000,000 tokens for specialized long-context modes—aimed at whole codebases, books, or long legal/technical documents.
- Reasoning / coding optimizations: preview writeups emphasize a “Deep Think” / improved reasoning mode lineage from prior Gemini Pro releases, with polishing for math, logic, and code tasks.
Benchmark performance
- The Gemini3Pro achieved first place in LMARE with a score of 1501, surpassing Grok-4.1-thinking’s 1484 points and also leading Claude Sonnet 4.5 and Opus 4.1.
- It also achieved first place in the WebDevArena programming arena with a score of 1487.
- In Humanity’s Last Exam academic reasoning, it achieved 37.5% (without tools); in GPQA Diamond science, 91.9%; and in the MathArena Apex math competition, 23.4%, setting a new record.
- In multimodal capabilities, the MMMU-Pro achieved 81%; and in Video-MMMU video comprehension, 87.6%.
Technical details & architecture
Three key layers:
- Multimodal encoder-decoder core — ingesting text, images, and other data and representing them in a shared latent space.
- Agentic orchestration / function calling — the model can decide to call functions, run code, or invoke external APIs (a robust function-calling system is available through Vertex AI / the Gemini API). This is how it bridges natural language with deterministic actions.
- “Deep Think” reasoning pipeline — an internal mechanism (configurable in preview) that allocates more steps of chain-of-thought-style reasoning and internal planning to difficult problems (math, multi-stage coding tasks, dataset analysis). Google treats this as a distinct mode with higher compute and stricter safety gating.
How Gemini 3 Pro Preview compares to other top models
High level comparison (preview → qualitative):
- Vs Gemini 2.5 Pro: preview reporting positions 3 Pro as a step up in reasoning, multimodal depth, and context size.
- Vs OpenAI GPT family (GPT-4o / GPT-5 rumors): Gemini 3 Pro as a competitor to the latest OpenAI models on reasoning and multimodal tasks.
- Vs Anthropic Claude 4.5: Gemini 3 Pro preview can rival Claude 4.5 on many reasoning/coding tests, though differences vary by domain and prompt.
Typical and high-value use cases
- Large document / book summarization & Q&A: long context support makes it attractive for legal, research, and compliance teams.
- Code understanding & generation at repo scale: integration with coding toolchains and improved reasoning helps large codebase refactors and automated code review workflows.
- Multimodal product assistants: image + text + audio workflows (customer support that ingests screenshots, call snippets, and documents).
- Media generation & editing (photo → video): earlier Gemini family features now include Veo / Flow-style photo→video capabilities; preview suggests deeper multimedia generation for prototypes and media workflows.
How to call gemini-3-pro-preview-11-2025 API from CometAPI
Gemini 3 Pro Preview Pricing in CometAPI，20% off the official price：
| Input Tokens | $1.60 |
|---|---|
| Output Tokens | $9.60 |
Required Steps
- Log in to cometapi.com. If you are not our user yet, please register first.
- Sign into your CometAPI console.
- Get the access credential API key of the interface. Click “Add Token” at the API token in the personal center, get the token key: sk-xxxxx and submit.
Use Method
- Select the “
gemini-3-pro-preview” endpoint to send the API request and set the request body. The request method and request body are obtained from our website API doc. Our website also provides Apifox test for your convenience. - Replace <YOUR_API_KEY> with your actual CometAPI key from your account.
- Insert your question or request into the content field—this is what the model will respond to.
- . Process the API response to get the generated answer.
CometAPI provides a fully compatible REST API—for seamless migration. Key details to Chat :
- Base URL: https://api.cometapi.com/v1/chat/completions
- Model Names:
gemini-3-pro-preview - Authentication:
Bearer YOUR_CometAPI_API_KEYheader - Content-Type:
application/json.
