# Google: Gemini 3.1 Pro Preview

google/gemini-3.1-pro-preview

[Chat](/content/platform/chat?model=google/gemini-3.1-pro-preview/index.html)

Gemini 3.1 Pro is the next generation in the Gemini series of models, a suite of highly-capable, natively multimodal, reasoning models. Gemini 3 Pro is now Google’s most advanced model for complex tasks, and can comprehend vast datasets, challenging problems from different information sources, including text, audio, images, video, and entire code repositories

by [Google](/content/google/index.html)  
Input type: Output type  
Publish time: 2026-02-19

## Recent activity on Gemini 3.1 Pro Preview

### Tokens processed per day

## Throughput

(tokens/s)

| Providers | Min (tokens/s) | Max (tokens/s) | Avg (tokens/s) |
| --- | --- | --- | --- |
| Google Vertex | 7.89 | 83.64 | 42.67 |
| SkyRouter | 25.33 | 25.33 | 25.33 |

## First Token Latency

(ms)

| Providers | Min (ms) | Max (ms) | Avg (ms) |
| --- | --- | --- | --- |
| Google Vertex | 3626 | 10021 | 7078.97 |
| SkyRouter | 6437 | 6437 | 6437.00 |

## Uptime stats for Gemini 3.1 Pro Preview

Uptime stats for Gemini 3.1 Pro Preview across all providers

| Providers | Uptime (Percent) |
| --- | --- |
| Google Vertex | 100.00 |
| SkyRouter |  - |

Price

Tiered Pricing

| Input Size | Price |
| --- | --- |
| 0 ≤ Input < 200k | $2/ M tokens |

## Model limitation

Context: 1.05M  
Max output: 65.53K  
Supported Parameters: max_completion_tokens, temperature, top_p, frequency_penalty, presence_penalty, seed, logit_bias, logprobs, top_logprobs, response_format, stop, tools, tool_choice, parallel_tool_calls

## Sample code and API for Gemini 3.1 Pro Preview

ZenMux normalizes requests and responses across providers for you.

OpenAI: Python-SDK

```python
from openai import OpenAI

client = OpenAI(
  base_url="https://zenmux.ai/api/v1",
  api_key="<ZENMUX_API_KEY>",
)

# Chat Completion
completion = client.chat.completions.create(
  model="google/gemini-3.1-pro-preview",
  messages=[
    {
      "role": "user",
      "content": "What is the meaning of life?"
    }
  ]
)
print(completion.choices[0].message.content)

# Responses API
responses = client.responses.create(
  model="google/gemini-3.1-pro-preview",
  input="What is the meaning of life?"
)
print(responses)
```