Gemini Pro latest

Google AI chat

Gemini Pro latest 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 Pro latest via Future AGI's Agent Command Center for unified observability, caching, and 15 routing strategies including cost-optimized fallback.

Pricing source: litellm Last verified: Oct 22, 2026 View source ↗
Cost calculator

Estimate Gemini Pro latest 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 Oct 22, 2026.

Input $2.00/M
Output $12.00/M
Blended (3:1 in:out) $4.50/M
Cross-model comparable price
Cached input $0.200/M
Batch input $1.00/M
Batch output $6.00/M

Context & 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

Strengths & caveats — when to pick Gemini Pro latest

Data-driven from Gemini Pro latest's percentile within chat peers.

Where it's strong

  • +pricing — cheaper than 81% of priced chat models on Future AGI
  • +long-context tasks — context window in the top 2% of peers
  • +audio input — only 3% of chat models on Future AGI advertise this
  • +PDF input — only 18% of chat models on Future AGI advertise this

Watch out for

  • No major caveats flagged from public spec.

Benchmark scores

Reported public benchmark numbers. Each row links to the source.

Captured Oct 20, 2026
Captured Oct 20, 2026
Try it

Call Gemini Pro latest 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 Pro latest 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-pro-latest",
    messages=[{"role": "user", "content": "Hello, Gemini Pro latest!"}],
)

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-pro-latest",
    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 ↗
Advanced: fallback + cache config (YAML) ▸
strategy: cost-optimized
targets:
  - model: gemini-pro-latest
    provider: google
    weight: 80
fallbacks:
  - model: llama-3-3-70b-instruct
    provider: azure-ai-foundry
  - model: claude-3-opus-20240229
    provider: anthropic
guardrails: [pii, prompt-injection, secrets]
cache: { exact: true, semantic: true }

Explore similar models

Grouped by Chatbot Arena tier (Gemini Pro latest sits at 1224 ELO). Side-by-side links appear where a comparison page exists; otherwise, open the model profile.

FAQ

How much does Gemini Pro latest cost?

Input is priced at $2.00 per 1M tokens and output at $12.00 per 1M tokens (Google AI, last verified Oct 22, 2026).

What is the context window of Gemini Pro latest?

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

Does Gemini Pro latest support function calling?

Yes — Gemini Pro latest supports function (tool) calling.

Is Gemini Pro latest good for production?

Gemini Pro latest is well-suited for pricing — cheaper than 81% 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 Pro latest 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 Pro latest

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