Gemini 3 Flash preview

Google AI chat

Gemini 3 Flash preview 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 $0.500/M tokens and output at $3.00/M tokens. Capabilities include function calling, vision, reasoning, audio input. Route Gemini 3 Flash preview 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 3 Flash preview 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 @ $0.0500/M
Per request
$0.002700
in $0.001500 · out $0.001200
Per day
$13.50
5,000 requests
Per month
$411
152,188 requests

Estimate uses $0.5000/M input · $3.00/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 $0.500/M
Output $3.00/M
Blended (3:1 in:out) $1.13/M
Cross-model comparable price
Cached input $0.0500/M
Batch input $0.250/M
Batch output $1.50/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, text

Capabilities

  • Function calling ✓ supported
  • Parallel tool calls ✓ supported
  • 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 3 Flash preview

Data-driven from Gemini 3 Flash preview's percentile within chat peers.

Where it's strong

  • +long-context tasks — context window in the top 2% of peers
  • +audio input — only 3% of chat models on Future AGI advertise this
  • +parallel tool calls — only 18% 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
Captured Oct 19, 2026
Try it

Call Gemini 3 Flash preview 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 Flash preview 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-flash-preview",
    messages=[{"role": "user", "content": "Hello, Gemini 3 Flash preview!"}],
)

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-flash-preview",
    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-3-flash-preview
    provider: google
    weight: 80
fallbacks:
  - model: gemini-4-argon
    provider: vertex-ai
  - model: claude-opus-5-5
    provider: azure-ai-foundry
guardrails: [pii, prompt-injection, secrets]
cache: { exact: true, semantic: true }

Same model on other providers

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

ProviderInput / 1MOutput / 1MVerified
Google Vertex AI$0.500/M$3.00/MOct 22, 2026

Explore similar models

Grouped by Chatbot Arena tier (Gemini 3 Flash preview sits at 1473 ELO). Side-by-side links appear where a comparison page exists; otherwise, open the model profile.

FAQ

How much does Gemini 3 Flash preview cost?

Input is priced at $0.500 per 1M tokens and output at $3.00 per 1M tokens (Google AI, last verified Oct 22, 2026).

What is the context window of Gemini 3 Flash preview?

Gemini 3 Flash preview supports a 1,048,576-token context window with up to 65,536 output tokens.

Does Gemini 3 Flash preview support function calling?

Yes — Gemini 3 Flash preview supports function (tool) calling, including parallel tool calls.

Is Gemini 3 Flash preview good for production?

Gemini 3 Flash preview is well-suited for long-context tasks — context window in the top 2% of peers and audio input — only 3% of chat models on Future AGI advertise this.

How can I route to Gemini 3 Flash preview 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 Flash preview

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