Gemini 2.0 Flash

Google Vertex AI chat Deprecated 156d ago
Heads-up: Google Vertex AI has scheduled Gemini 2.0 Flash for deprecation on Jun 1, 2026. Plan a migration. Use Agent Command Center's model fallback routing to swap models without code changes.

Gemini 2.0 Flash is a Google Vertex AI chat model.Input is priced at $0.150/M tokens and output at $0.600/M tokens. Route Gemini 2.0 Flash 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 2.0 Flash spend

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

~3K in / ~400 out · 5K req/day
3,000
0200,000
400
016,000
5,000
01,000,000
Per request
$0.000690
in $0.000450 · out $0.000240
Per day
$3.45
5,000 requests
Per month
$105
152,188 requests

Estimate uses $0.1500/M input · $0.6000/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 $0.150/M
Output $0.600/M
Blended (3:1 in:out) $0.262/M
Cross-model comparable price
Batch input $0.0750/M
Batch output $0.300/M

Context & limits

Context window
—
Max input
—
Max output
—
Modalities
text

Capabilities

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

Strengths & caveats — when to pick Gemini 2.0 Flash

Data-driven from Gemini 2.0 Flash's percentile within chat peers.

Where it's strong

Watch out for

  • !agentic workflows — no advertised function-calling; use a tool-capable model and route via Agent Command Center for fallback
  • !strict structured output — no JSON-schema enforcement, expect retry loops
  • !already deprecated — provider stopped accepting new traffic 156 days ago

Benchmark scores

Reported public benchmark numbers. Each row links to the source. Faded bar shows 6-peer average for context.

HumanEvalcode· 0-shot↑7% vs peers
Captured Aug 8, 2026
Arena ELO (coding)code· style control↓7% vs peers
Captured Oct 20, 2026
Chatbot Arena ELOgeneral· style control↓5% vs peers
Captured Oct 20, 2026
MMLUgeneral· 5-shot
Captured Aug 8, 2026
MMMUmultimodal· 0-shot
Captured Aug 8, 2026
GPQAreasoning· 0-shot
Captured Aug 8, 2026
LiveCodeBenchcode· pass@1
Captured Aug 8, 2026
Captured Oct 19, 2026
Try it

Call Gemini 2.0 Flash 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 2.0 Flash 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="vertex-ai/gemini-2-0-flash",
    messages=[{"role": "user", "content": "Hello, Gemini 2.0 Flash!"}],
)

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="vertex-ai/gemini-2-0-flash",
    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-2-0-flash
    provider: vertex-ai
    weight: 80
fallbacks:
  - model: claude-haiku-4-5
    provider: azure-ai-foundry
  - model: claude-haiku-4-5-20251001
    provider: anthropic
guardrails: [pii, prompt-injection, secrets]
cache: { exact: true, semantic: true }

Same model on other providers

gemini-2-0-flash is also available via 1 other route. Pricing, regions, and capabilities can differ — compare before routing production traffic.

ProviderInput / 1MOutput / 1MVerified
Google AI$0.1000/M$0.400/MAug 6, 2026

Explore similar models

Grouped by Chatbot Arena tier (Gemini 2.0 Flash sits at 1360 ELO). Side-by-side links appear where a comparison page exists; otherwise, open the model profile.

FAQ

How much does Gemini 2.0 Flash cost?

Input is priced at $0.150 per 1M tokens and output at $0.600 per 1M tokens (Google Vertex AI, last verified Oct 22, 2026).

What is the context window of Gemini 2.0 Flash?

Context window for Gemini 2.0 Flash is not currently public.

Does Gemini 2.0 Flash support function calling?

Gemini 2.0 Flash does not currently advertise function-calling support. For agentic workloads, prefer a tool-calling-capable model and route via Agent Command Center for fallback.

Is Gemini 2.0 Flash good for production?

Gemini 2.0 Flash is best evaluated against your own production traces. Pipe traffic through Agent Command Center to compare it head-to-head against alternatives in shadow mode.

How can I route to Gemini 2.0 Flash 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 2.0 Flash

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