Gemini 3.1 Pro preview Customtools

Google AI chat

Gemini 3.1 Pro preview Customtools is a Google AI chat model.It supports a 1,048,576-token context windowwith up to 65,536 output tokens.Input is priced at $2.00/M tokens and output at $12.00/M tokens. Capabilities include function calling, vision, reasoning, audio input. Route Gemini 3.1 Pro preview Customtools via Future AGI's Agent Command Center for unified observability, caching, and 15 routing strategies including cost-optimized fallback.

Pricing source: litellm Last verified: May 12, 2026 View source ↗
Cost calculator

Estimate Gemini 3.1 Pro preview Customtools spend

Pick a workload, fine-tune the sliders, and see the monthly bill.

~3K in / ~400 out · 5K req/day
3,000
01,048,576
400
065,536
5,000
01,000,000
cached @ $0.2000/M
Per request
$0.0108
in $0.006000 · out $0.004800
Per day
$54.00
5,000 requests
Per month
$1,644
152,188 requests

Estimate uses $2.00/M input · $12.00/M output. Provider pricing changes. Production costs vary with retries, streaming overhead, and tool-call rounds.
Want this for free? Cache + route via Agent Command Center — first 100K requests and 100K cache hits free every month.

Pricing

Per-token rates, expressed in USD per 1M tokens. Verified May 12, 2026.

Input $2.00/M
Output $12.00/M
Cached input $0.200/M
Batch input $1.00/M
Batch output $6.00/M

Limits

Context window
1,048,576 tokens
Max input
1,048,576 tokens
Max output
65,536 tokens
Modalities
vision, audio_in, pdf, video, text

Capabilities

  • Function calling ✓ supported
  • Parallel tool calls — not advertised
  • Vision input ✓ supported
  • Audio input ✓ supported
  • Audio output — not advertised
  • PDF input ✓ supported
  • Streaming ✓ supported
  • Structured output ✓ supported
  • Prompt caching ✓ supported
  • Reasoning ✓ supported

Where it's strong

  • +pricing — cheaper than 83% of priced chat models on Future AGI
  • +long-context tasks — context window in the top 2% of peers
  • +audio input — only 4% of chat models on Future AGI advertise this
  • +PDF input — only 16% of chat models on Future AGI advertise this
  • +prompt caching — only 23% of chat models on Future AGI advertise this

Watch out for

  • No major caveats flagged from public spec.

Benchmarks pending

We haven't logged public benchmark scores for Gemini 3.1 Pro preview Customtools yet. Have one to contribute? Submit a source — citations help us prioritise.

Try it

Call Gemini 3.1 Pro preview Customtools via Agent Command Center

One OpenAI-compatible endpoint. Routing, fallback, semantic caching, guardrails, and cost tracking come along for the ride. First 100K requests + 100K cache hits free every month.

SDK
Native Future AGI client (agentcc / @agentcc/client). Per-call metadata — provider, cost, latency, cache hit, request id — is returned on x-agentcc-* response headers, so any HTTP client can read it.
# Gemini 3.1 Pro preview Customtools via the Agent Command Center Python SDK
# pip install agentcc
import os
from agentcc import AgentCC

client = AgentCC(
    api_key=os.environ["AGENTCC_API_KEY"],   # from app.futureagi.com → Settings → API Keys
    base_url="https://gateway.futureagi.com/v1",
)

resp = client.chat.completions.create(
    model="google/gemini-3-1-pro-preview-customtools",
    messages=[{"role": "user", "content": "Hello, Gemini 3.1 Pro preview Customtools!"}],
)

print(resp.choices[0].message.content)
print(f"Tokens: {resp.usage.total_tokens}")

# Per-call gateway metadata is returned on x-agentcc-* response headers.
# When you need it programmatically, use .with_raw_response to get them:
raw = client.chat.completions.with_raw_response.create(
    model="google/gemini-3-1-pro-preview-customtools",
    messages=[{"role": "user", "content": "Same call, but I want the headers."}],
)
print("Provider:", raw.headers.get("x-agentcc-provider"))
print("Latency:", raw.headers.get("x-agentcc-latency-ms"), "ms")
print("Cost:   ", raw.headers.get("x-agentcc-cost"), "USD")
print("Cache:  ", raw.headers.get("x-agentcc-cache"))
Set AGENTCC_API_KEY with a key fromapp.futureagi.com.Gateway docs ↗

Same model on other providers

gemini-3-1-pro-preview-customtools is also available via 1 other route. Pricing, regions, and capabilities can differ — compare before routing production traffic.

ProviderInput / 1MOutput / 1MVerified
Google Vertex AI$2.00/M$12.00/MMay 12, 2026

Compare with similar models

Gemini 3.1 Pro preview Customtools doesn't have a public Arena ELO score yet, so we group by provider only — quality-tier comparisons need a benchmark.

FAQ

How much does Gemini 3.1 Pro preview Customtools cost?

Input is priced at $2.00 per 1M tokens and output at $12.00 per 1M tokens (Google AI, last verified May 12, 2026).

What is the context window of Gemini 3.1 Pro preview Customtools?

Gemini 3.1 Pro preview Customtools supports a 1,048,576-token context window with up to 65,536 output tokens.

Does Gemini 3.1 Pro preview Customtools support function calling?

Yes — Gemini 3.1 Pro preview Customtools supports function (tool) calling.

Is Gemini 3.1 Pro preview Customtools good for production?

Gemini 3.1 Pro preview Customtools is well-suited for pricing — cheaper than 83% of priced chat models on Future AGI and long-context tasks — context window in the top 2% of peers.

How can I route to Gemini 3.1 Pro preview Customtools with fallback?

Use Agent Command Center: a single OpenAI-compatible endpoint that supports cost-optimized routing, latency-aware retries, model fallback, and shadow traffic. Configure once, swap models without app changes.

Useful links for Gemini 3.1 Pro preview Customtools

Official sources, independent benchmarks, and pricing aggregators — no random search-engine guesses.