KymaKyma
Google

Google

Gemini 3.1 Pro

The first Gemini Pro tier on Kyma. Every other Gemini here is a Flash or a Flash Lite; this is the step above them, for work those tiers cannot carry. It is a preview model upstream, and it is priced above the Flash family.

Modalities

Text+Image → Text

Input

$2.70 /1M

Output

$16.20 /1M

Cached input

$0.27 /1M90% off

Context

1M

Speed

medium

Below release

Not established

Weights

Not published

Pricing

Pay per token. Cached input bills at this model’s own cached rate, listed below.

$2.70 /1M input$16.20 /1M output
Hobby10 req/day · 2K in / 500 out
~$4.05/mo
Production1,000 req/day · 2K in / 500 out
~$405/mo
Scale20,000 req/day · 2K in / 500 out
~$8,100/mo
+ Estimate your workload
1,000
2,000
500
30%

Estimated monthly cost

$361

$12.04 / day on Gemini 3.1 Pro

Same workload on:

Gemini 3.5 Flash Lite$74.92-79%
Gemini 3.6 Flash$137-62%

Estimates use list pricing with cached input at this model's own cached rate. Actual bills depend on real token counts, and every response includes its exact cost.

When to use Gemini 3.1 Pro

Updated 2026-08-14

Where this model earns its cost — and where it doesn't.

Gemini 3.1 Pro is Google's Pro-tier reasoning model. It takes a 1M-token context, emits up to 65,536 tokens in one response, and accepts text, image, audio, video and file input, returning text. Tool calling, reasoning and structured outputs are all supported.

The rate steps up above 200,000 prompt tokens: input and output both roughly double past that threshold. Kyma publishes the base rate on the model and pricing pages and the step alongside it, so a request that will cross 200K can be costed before it is sent.

Google labels this release a preview. Behaviour may change before a stable build, so test before locking it into a critical path. On Kyma it serves through an OpenAI-compatible endpoint with automatic failover to a second independent route. Prompt caching is supported and repeated prefixes bill at this model's cached input rate. Every response carries the exact request cost in usage.cost and names the model that answered in the X-Kyma-Model header.

Reasoning past the Flash ceiling

Problems where a Flash-tier answer is not good enough and the extra cost per token is worth paying.

Long-horizon agentic work

Tool calling and reasoning across a 1M-token context, with a 64K output ceiling for long plans and long edits.

Whole-repository and whole-corpus analysis

Reads very large inputs in one request; budget for the higher rate that applies above 200K prompt tokens.

Mixed-media analysis

Accepts text, image, audio, video and file input in a single request and returns a long written result.

Not ideal for: Do not reach for this on high-volume or short-answer work. It lists well above the Gemini Flash tiers, and for prompts a Flash model already answers correctly the extra cost buys nothing. It is also a preview build, so it is the wrong choice where behaviour must not shift.

How it compares

Against the peers people actually weigh it against.

SpecGemini 3.1 ProGemini 3.5 Flash LiteGemini 3.6 Flash
Input /1M$2.70$0.405$1.013
Output /1M$16.20$3.375$5.063
Context1M1M1M
ToolsYesYesYes
ReasoningYesYesYes
Speedmediumfastfast

Quick start

Up and running in under two minutes.

  1. 1

    Create an API key

    Sign up and grab a key from the dashboard — $0.50 free credit, no card required.

    Get API key →
  2. 2

    Make your first request

    Drop in your key and send a chat completion — fully OpenAI-compatible.

    curl https://kymaapi.com/v1/chat/completions \
  -H "Authorization: Bearer YOUR_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "gemini-3.1-pro",
    "messages": [
      {"role": "user", "content": "Explain prompt caching in one paragraph."}
    ]
  }'
  3. 3

    Stream responses

    Add "stream": true to receive tokens as they arrive.

    curl https://kymaapi.com/v1/chat/completions \
  -H "Authorization: Bearer YOUR_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "gemini-3.1-pro",
    "stream": true,
    "messages": [{"role": "user", "content": "Hello!"}]
  }'

FAQ

Common questions about this model.

What is the context window of Gemini 3.1 Pro?

Gemini 3.1 Pro has a 1M-token context window — roughly 1542 pages of text in a single request.

How much does the Gemini 3.1 Pro API cost?

$2.70 per 1M input tokens and $16.20 per 1M output tokens, with cached input at $0.27/1M — 90% off the input rate on repeated prompt prefixes. No subscription; you pay only for what you use.

Does Gemini 3.1 Pro support function calling?

Yes — Gemini 3.1 Pro supports tool/function calling and structured outputs (JSON mode), so it works with agent frameworks out of the box.

Are the weights for Gemini 3.1 Pro publicly available?

No. Google does not publish Gemini 3.1 Pro's weights — it is reachable through an API rather than as a file you can download and run (https://deepmind.google/models/model-cards/gemini-3-1-pro/, read 2026-08-14). That is Google's decision about their own product, not a limitation of Kyma.

Is Gemini 3.1 Pro ever served below the precision its creator released it at?

Kyma cannot say, and for this model nobody can. Google does not publish Gemini 3.1 Pro's weights, so there is no released checkpoint whose precision a route could be measured against. We publish "not established" rather than reading a low format as a downgrade: on several models in this catalogue a low format is exactly how the creator ships it.

How do I use Gemini 3.1 Pro?

Kyma is OpenAI-compatible: point your SDK's base URL at https://kymaapi.com/v1, use your Kyma API key, and set the model to gemini-3.1-pro. Signing up is free and includes $0.50 of credit — no card required.

How is this different from the Gemini Flash models on Kyma?

It is the Pro tier rather than the Flash tier — Google's step up for harder reasoning — and it is priced accordingly, well above every Gemini Flash model in the catalogue. It also emits up to 65,536 tokens per response and accepts file input alongside text, image, audio and video.

What happens to the price above 200K prompt tokens?

Both the input and the output rate step up above 200,000 prompt tokens. Kyma publishes the base rate and the step; the higher rate applies to the whole request once the prompt crosses the threshold.

Is this a stable release?

No. Google ships it as a preview, so weights and behaviour may change before a stable build. Test before depending on it in a critical workflow.

Does prompt caching work on this model?

Yes. Repeated prompt prefixes bill at this model's cached input rate, and the saving is reported per request in usage.cache_discount.

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