What is the context window for Gemini 3.1 Pro in Atlas?

Gemini 3.1 Pro provides a substantial 1,048,576 token context window for Atlas, enabling the agent to handle very large codebases and extensive project context in 2026. This large window is a key advantage for complex development tasks.

How much does Gemini 3.1 Pro cost per token for Atlas?

For Atlas users in 2026, Gemini 3.1 Pro costs $2 per Mtok for input tokens and $12 per Mtok for output tokens. This makes its input pricing highly competitive for a million-token frontier model.

What are the output token limits for Gemini 3.1 Pro with Atlas?

Gemini 3.1 Pro has a maximum output token limit of 65,536 tokens when used with Atlas. This is half the 128,000 tokens offered by some other frontier models, which might lead to truncation for extremely large single-turn diffs.

Is Gemini 3.1 Pro good for Atlas's tool use?

Yes, Gemini 3.1 Pro is particularly well-suited for Atlas's tool use in 2026. Its custom tools variant (`gemini-3.1-pro-preview-customtools`) is specifically tuned for structured tool schemas, which perfectly matches the shape of Atlas's Model Context Protocol (MCP) tool surface.

When should I use a different model instead of Gemini 3.1 Pro with Atlas?

You should consider a different model for Atlas if you require output exceeding 65,536 tokens in a single turn, or if you need to minimize output costs for tasks that don't demand frontier reasoning, where Gemini 3 Flash's $3 per Mtok output might be more economical.

How do I set up Gemini 3.1 Pro in Atlas?

To set up Gemini 3.1 Pro in Atlas, export your API key (e.g., `GEMINI_API_KEY`), confirm model resolution with `atlas models google`, then select Google and Gemini 3.1 Pro from the `/models` dialog. For enterprise, use Vertex with `GOOGLE_VERTEX_PROJECT` and `GOOGLE_VERTEX_LOCATION`.

Atlas with Gemini 3.1 Pro in 2026

Gemini 3.1 Pro is an excellent choice for driving Atlas in 2026, offering a massive 1,048,576 token context window at a competitive $2 per Mtok for input. It excels at complex code understanding and structured tool interactions, making it ideal for Atlas's agentic workflows.

Why Choose Gemini 3.1 Pro for Atlas?

Gemini 3.1 Pro, Google's frontier model, offers a 1,048,576 token context window, making it the cheapest million-token frontier model from a major lab in 2026. Its custom tools variant is specifically tuned for structured tool schemas, which perfectly aligns with Atlas's Model Context Protocol (MCP) tool surface.

Gemini 3.1 Pro is particularly well-suited for Atlas's demanding agentic workflows due to its robust understanding of complex codebases. The model's 1,048,576 token context window allows Atlas to process extensive code files, git diffs, and project context without losing critical information. Furthermore, the `gemini-3.1-pro-preview-customtools` variant is explicitly optimized for structured tool schemas, directly benefiting Atlas's Model Context Protocol (MCP) tool surface. This tuning ensures that Atlas's permission-gated tool calls, which are checked against allow, ask, and deny rules, are interpreted accurately and efficiently by the model. Atlas's ability to search code with Axis, its hybrid semantic and keyword retrieval fused by reciprocal rank fusion, and to index code by AST declarations using tree-sitter, rather than blind line windows, is significantly enhanced by Gemini 3.1 Pro's deep contextual understanding. This model's capabilities support Atlas in drafting plans in a read-only plan agent before switching to a build agent, and in computing unified diffs for every file edit, surfacing them for approval.

Understanding Gemini 3.1 Pro's Cost and Context Tradeoffs

Gemini 3.1 Pro provides a substantial 1,048,576 token context window at an input cost of $2 per Mtok, significantly undercutting GPT-5.6's $5 at a comparable window in 2026. However, developers should note its output pricing of $12 per Mtok and a 65,536 max output token ceiling.

While Gemini 3.1 Pro offers a highly competitive input price of $2 per Mtok for its 1,048,576 token context window, making it the cheapest million-token frontier model from a major lab, its output pricing is $12 per Mtok. This output cost is higher than Gemini 3 Flash's $3 per Mtok, which might be a consideration for tasks that do not require frontier reasoning capabilities. Another important tradeoff is the model's 65,536 max output tokens. This ceiling is half the 128,000 tokens allowed by models like Claude Opus 4.8 and the GPT-5 family. Consequently, very large single-turn diffs or extensive code generations requested by Atlas might be truncated, requiring Atlas to make multiple calls or for the developer to manually review and complete the output. Atlas's ability to snapshot file changes as git patches for diffing and rollback, and to compute unified diffs for approval, means that while the model can process large inputs, its output limitations could impact the efficiency of very large code modifications.

When to Consider Alternatives to Gemini 3.1 Pro for Atlas

While Gemini 3.1 Pro is a strong contender for Atlas in 2026, especially with its 1,048,576 token context window and $2 input cost, its $12 per Mtok output price and 65,536 token output ceiling present specific scenarios where other models might be more cost-effective or capable.

Developers using Atlas should consider alternative models when their primary concern is minimizing output costs for tasks that do not demand frontier reasoning. For instance, if the work involves generating extensive code or very large single-turn diffs where the 65,536 max output token ceiling of Gemini 3.1 Pro becomes a limiting factor, leading to truncation, models like Claude Opus 4.8 or the GPT-5 family, which allow up to 128,000 output tokens, might be more suitable despite potentially higher input costs. Additionally, for tasks where the advanced reasoning of a frontier model isn't strictly necessary, and output volume is high, a model like Gemini 3 Flash, with its $3 per Mtok output price, could offer significant cost savings compared to Gemini 3.1 Pro's $12 per Mtok output. Atlas allows switching the active model and provider on the fly with favorites and recents, making it easy to experiment and find the optimal model for different types of coding tasks.

Setup

01Export your API key under any of the names Atlas accepts: `export GEMINI_API_KEY="YOUR_API_KEY"` (or `GOOGLE_GENERATIVE_AI_API_KEY`, `GOOGLE_API_KEY`).
02Confirm the model resolved by running: `atlas models google`.
03Select Google, then Gemini 3.1 Pro, from the `/models` dialog within Atlas.
04For enterprise authentication instead of an API key, use the Vertex provider and set `GOOGLE_VERTEX_PROJECT` plus `GOOGLE_VERTEX_LOCATION` environment variables.

Frequently asked questions

What is the context window for Gemini 3.1 Pro in Atlas?: Gemini 3.1 Pro provides a substantial 1,048,576 token context window for Atlas, enabling the agent to handle very large codebases and extensive project context in 2026. This large window is a key advantage for complex development tasks.
How much does Gemini 3.1 Pro cost per token for Atlas?: For Atlas users in 2026, Gemini 3.1 Pro costs $2 per Mtok for input tokens and $12 per Mtok for output tokens. This makes its input pricing highly competitive for a million-token frontier model.
What are the output token limits for Gemini 3.1 Pro with Atlas?: Gemini 3.1 Pro has a maximum output token limit of 65,536 tokens when used with Atlas. This is half the 128,000 tokens offered by some other frontier models, which might lead to truncation for extremely large single-turn diffs.
Is Gemini 3.1 Pro good for Atlas's tool use?: Yes, Gemini 3.1 Pro is particularly well-suited for Atlas's tool use in 2026. Its custom tools variant (`gemini-3.1-pro-preview-customtools`) is specifically tuned for structured tool schemas, which perfectly matches the shape of Atlas's Model Context Protocol (MCP) tool surface.
When should I use a different model instead of Gemini 3.1 Pro with Atlas?: You should consider a different model for Atlas if you require output exceeding 65,536 tokens in a single turn, or if you need to minimize output costs for tasks that don't demand frontier reasoning, where Gemini 3 Flash's $3 per Mtok output might be more economical.
How do I set up Gemini 3.1 Pro in Atlas?: To set up Gemini 3.1 Pro in Atlas, export your API key (e.g., `GEMINI_API_KEY`), confirm model resolution with `atlas models google`, then select Google and Gemini 3.1 Pro from the `/models` dialog. For enterprise, use Vertex with `GOOGLE_VERTEX_PROJECT` and `GOOGLE_VERTEX_LOCATION`.

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