Gemini 3.1 Pro Preview Custom Tools
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Google | 1,048,576 token context | $2.00/M input, $12.00/M output. Gemini 3.1 Pro Preview Custom Tools is a variant of Gemini 3.1 Pro that improves tool selection behavior by preventing overuse of a general bash tool when more efficient third-party or user-defined functions are available. This specialized preview endpoint significantly increases function calling reliability and ensures the model selects the most appropriate tool in coding agents and complex, multi-tool workflows. It retains the core strengths of Gemini 3.1 Pro, including multimodal reasoning across text, image, video, audio, and code, a 1M-token context window, and strong software engineering performance.
Guides for this model
How to choose an AI model in October 2026: the closed source news, then the open weights worth downloading
Open weights vs open source vs API-only: what you are actually allowed to do
The 10 cheapest ChatGPT alternatives in 2026: free local models, free tiers and flat-rate plans
Captain's notes
Notes from 2026-10-13
Gemini 3.1 Pro Preview Custom Tools is a specialized endpoint from Google built for agentic and multi-tool workflows. Its defining change over standard Gemini 3.1 Pro is smarter tool selection: it stops defaulting to a generic bash tool when a more precise user-defined or third-party function is available. If you are building coding agents or pipelines where tool choice reliability matters, this variant is worth the detour.
Known for
- Improved function-calling reliability in multi-tool and agentic pipelines
- Avoids over-relying on a generic bash tool when better functions exist
- One-million-token context window for long documents and codebases
- Multimodal: handles text, image, video, audio and code in one model
- Strong baseline software engineering performance from Gemini 3.1 Pro
Watch out for
- API-only, closed weights — no local deployment, no self-hosting.
- Output is priced at $12.00 per million tokens, which adds up fast in agentic loops.
- This is a preview endpoint; production stability and long-term availability are not guaranteed.
Prompts to try
Multi-tool agent task
You have three tools available: search_web(query), read_file(path), and run_python(code). A user asks: find the current population of Tokyo, save it to a file called tokyo.txt, then read that file back and confirm the content. Plan and call the correct tools in sequence, explaining each choice.
Code review on large file
Here is a 500-line Python module for a REST API. Identify any security vulnerabilities, suggest the two most impactful refactors for maintainability, and flag any functions that are doing more than one job. Be specific about line ranges.
Reason over a long document
I am pasting a lengthy technical specification below. After reading it, tell me: what are the three biggest unresolved ambiguities that would block an engineering team from starting implementation, and what clarifying questions should they ask the product owner?
Compare with
- Gemma 4 31BOpen-weights model262,144 token context · $0.20/M input, $0.40/M output
- Gemma 4 26B A4BOpen-weights model262,144 token context · $0.09/M input, $0.30/M output
- gemma 4 31B it turboOpen-weights model262,144 token context · $0.09/M input, $0.34/M output
- Gemini 3.8 FlashAPI-only model1,048,576 token context · $0.83/M input, $4.12/M output
More text models from google
Questions people ask
- Can I run Gemini 3.1 Pro Preview Custom Tools locally?
- No. This is a closed-weights, API-only model from Google — there is no download and no self-hosting option.
- What does this variant cost and how large is its context?
- Input is priced at $2.00 per million tokens and output at $12.00 per million tokens, with a context window of 1,048,576 tokens.
- How is this different from standard Gemini 3.1 Pro?
- The core model is the same, but this endpoint specifically improves tool selection behavior — it reduces the tendency to fall back on a generic bash tool when a more appropriate user-defined or third-party function is available.
Captain's verdictA narrow but genuine fix for a real agentic pain point — worth the premium only if tool-selection reliability is actually breaking your pipeline.
Captain writes these notes from the model's own description and model card. Prices and context sizes are the provider's at the time of writing and can change.
Ranking badge
Updated Oct 22, 2026
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How this score adds up
This model has no popularity data from any source yet, so it carries a stand-in number below 7,000° that keeps the lists complete. It never ranks above a model with data. The breakdown appears here as soon as a source reports it.
Glossary: the terms used here
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- Download-equivalents
- Everything the score treats as a download, added up: downloads themselves, each torrent seeder as 1,000, each AI Horde image and each run on a generation site as one.
- Log scale
- Counting by tens, not by ones: going from 1,000 to 10,000 downloads adds the same degrees as going from 10,000 to 100,000. It keeps giants from crowding out everything else.
- Likes
- Thumbs up and likes from every source, worth half a download each on the log scale.
- Adoption rate
- How many downloads a day a model gets right now, from the difference between two readings of a source. A quarter of the weight of the download term.
- Measured and estimated
- Measured means two readings of a source exist and the difference is real. Estimated means only today's total is known and the past is spread over the model's life; the site says which one it is showing.
- Seeder
- Someone who keeps a copy of the weights online for others to download over a torrent, or a hosted mirror doing the same. Each one counts as 1,000 downloads.
- AI Horde
- A volunteer network that generates images for free on donated computers. The number of images it has made with a model is public, and each counts as one download.
- Generation sites
- Sites that host their own copies of a model and let people generate with it, such as PixAI, SeaArt and Yodayo. Their downloads count like Civitai's and each generation run as one download.
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- A text model served through an API, such as Claude or GPT, has no weights to download, so its usage is measured in tokens: the pieces of text it read and wrote through OpenRouter, a gateway many apps use, over the last 30 days. Every 10,000,000 tokens count as one download. Source: OpenRouter (openrouter.ai/rankings), CC BY 4.0.
- Full model (checkpoint)
- The weights themselves, the file that generates on its own. It gets a bonus because add-ons depend on it.
- LoRA and embedding
- Small add-on files that steer someone else's weights toward a style, a character or a concept. They cannot run alone.
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- Degrees taken off for how long ago the family's weights came out: 150° a year, up to 750°. It keeps old downloads that had years to pile up from freezing the top of the list.
- Family boost
- A small, bounded nudge for LoRAs of a family this site is pushing forward right now, always listed in the breakdown.
- Stand-in score
- A stable number below the floor given to a model no source reports on yet, so lists stay complete. It never ranks above a model with data.
- New! (grace period)
- A model less than 7 days old shows New! instead of a score and holds no place in the rankings. Its score is computed from day one, but a model one day old grows faster than anything, so without the wait the week's #1 would always be whatever came out yesterday rather than what held up for a week.
- Trend
- How a model's growth over a period compares with the typical model's growth over the same period. Faster than typical reads as a rise, slower as a fall.
- Typical model
- The middle of the catalog: half the models with a figure grew faster over the period, half slower.
Gemini 3.1 Pro Preview Custom Tools is a text model for the Text / LLM family listed on ModelTrends.ai, a read-only catalog of open source AI image, video and text models. Compare it with other Text / LLM models and check its heat score to see how it is trending.
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