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Google · Frontier

Gemini 3.1 Pro (Preview Custom Tools)

Added Feb 27, 2026

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Gemini 3.1 Pro preview variant tuned for better tool selection behavior in coding agents and multi-tool workflows. It reduces overuse of generic bash tools and improves function-calling reliability while retaining Gemini 3.1 Pro's multimodal reasoning and 1M-token context. NOTE: Inputs > 200k tokens are charged at 2x input and 1.5x output rates.

  • Reasoning
  • Tools
  • Vision
  • Structured output
  • Audio input
  • Video input
Input
Text, Images, Video, Audio
Output
Text
Reasoning effort
low · medium · high
Discovery tier
Frontier

Pricing

USD per 1M tokens
Input
$2.00
Output
$12.00
Cache read
$0.20
Cache write
$0.38

Reference prices as published by the model provider. API example

Specifications

Context window
1M
Max output
65.5K
Average output (7 days)
903 tokens
Longer than 68% of 465 models

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TryGPT 6 LunaClaude Sonnet 4.6 ThinkingMiniMax M3All 3

Public evaluations

Benchmarks

Independent evaluation results, with how each score ranks among the models in the Noumen catalog.

Intelligence Index

29.7

Better than 71% of 326 scored models

3.8Catalog models by score55.1

Indexes

  • Coding Index

    68.8

    Composite of the coding evaluations

    Better than 66% of 168 scored models

Agentic work

  • AutomationBench-AA

    35.4%

    Workflow automation, penalized for guardrail violations

    Better than 52% of 173 scored models

  • AutomationBench-AA tasks completed

    9.4%

    Workflows finished end to end without a guardrail violation

    Better than 50% of 173 scored models

  • Harvey LAB-AAv1.1

    0.0%

    Legal tasks passed in full, with no material hallucination

    Better than 0% of 29 scored models

  • AA-Briefcasev1.1

    456 Elo

    Agentic knowledge work, rated head to head

    Better than 15% of 166 scored models

  • GDPval-AAv2.1

    791 Elo

    Economically valuable occupational tasks, rated head to head

    Better than 25% of 187 scored models

Document reasoning

  • GDP.pdf

    17.8%

    Professional reasoning over PDF documents, all-pass rate

    Better than 70% of 171 scored models

  • AA-LCRv1.1

    82.0%

    Reasoning across long documents

    Better than 85% of 309 scored models

  • MLCR-AA

    11.1%

    Long-context reasoning over medical records

    Better than 38% of 121 scored models

Reasoning and knowledge

  • Humanity’s Last Exam

    47.0%

    Expert-level questions across academic fields

    Better than 90% of 323 scored models

  • GPQA Diamond

    94.1%

    Graduate-level science questions

    Better than 96% of 291 scored models

  • IFBench

    77.1%

    Following precise output instructions

    Better than 93% of 215 scored models

Coding

  • Terminal-Benchv4.0

    4.0%

    Practical software engineering in a terminal

    Better than 51% of 171 scored models

  • SciCode

    58.7%

    Scientific computing in Python

    Better than 85% of 174 scored models

Legacy evaluations

  • Terminal-Bench Hard

    53.8%

    Earlier terminal task suite

    Better than 93% of 212 scored models

  • τ²-Bench Telecom

    95.6%

    Tool use in a customer-support simulation

    Better than 87% of 214 scored models

  • AA-LCR (unversioned)

    82.0%

    Long-context reasoning, earlier grading

    Better than 85% of 309 scored models

Scores from Artificial Analysis, updated Oct 26, 2026. Artificial Analysis

Developers

Use it through the API

Noumen’s API is OpenAI-compatible: any Chat Completions client works with a base URL and a key.

Read the quickstart
curl https://www.noumen.xyz/api/v1/chat/completions \
  -H "Authorization: Bearer $NOUMEN_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "google/gemini-3.1-pro-preview-customtools",
    "reasoning_effort": "medium",
    "messages": [{ "role": "user", "content": "Explain this stack trace." }]
  }'
import os
from openai import OpenAI

client = OpenAI(base_url="https://www.noumen.xyz/api/v1", api_key=os.environ["NOUMEN_API_KEY"])
reply = client.chat.completions.create(
    model="google/gemini-3.1-pro-preview-customtools",
    messages=[{"role": "user", "content": "Explain this stack trace."}],
)
print(reply.choices[0].message.content)

Google

Other Google models, starting with the same family.