Gemini 1.5 Pro 001

Google AI chat Deprecated 354d ago
Heads-up: Google AI has scheduled Gemini 1.5 Pro 001 for deprecation on May 24, 2025. Plan a migration. Use Agent Command Center's model fallback routing to swap models without code changes.

Gemini 1.5 Pro 001 is a Google AI chat model.It supports a 2,097,152-token context windowwith up to 8,192 output tokens.Input is priced at $3.50/M tokens and output at $10.50/M tokens. Capabilities include function calling, vision, prompt caching. Route Gemini 1.5 Pro 001 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 7, 2026 View source ↗
Cost calculator

Estimate Gemini 1.5 Pro 001 spend

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

~3K in / ~400 out · 5K req/day
3,000
02,000,000
400
08,192
5,000
01,000,000
Per request
$0.0147
in $0.0105 · out $0.004200
Per day
$73.50
5,000 requests
Per month
$2,237
152,188 requests

Estimate uses $3.50/M input · $10.50/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 7, 2026.

Input $3.50/M
Output $10.50/M

Limits

Context window
2,097,152 tokens
Max input
2,097,152 tokens
Max output
8,192 tokens
Modalities
vision, text

Capabilities

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

Where it's strong

  • +pricing — cheaper than 83% of priced chat models on Future AGI
  • +long-context work — top-4 largest context window across 1913 chat models
  • +prompt caching — only 23% of chat models on Future AGI advertise this

Watch out for

  • !already deprecated — provider stopped accepting new traffic 354 days ago

Benchmark scores

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

MMLUgeneral· 5-shot↓3% vs peers
Captured May 12, 2026
Try it

Call Gemini 1.5 Pro 001 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 1.5 Pro 001 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-1-5-pro-001",
    messages=[{"role": "user", "content": "Hello, Gemini 1.5 Pro 001!"}],
)

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-1-5-pro-001",
    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-1-5-pro-001 is also available via 1 other route. Pricing, regions, and capabilities can differ — compare before routing production traffic.

ProviderInput / 1MOutput / 1MVerified
Google Vertex AI$1.25/M$5.00/MMay 7, 2026

Compare with similar models

Gemini 1.5 Pro 001 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 1.5 Pro 001 cost?

Input is priced at $3.50 per 1M tokens and output at $10.50 per 1M tokens (Google AI, last verified May 7, 2026).

What is the context window of Gemini 1.5 Pro 001?

Gemini 1.5 Pro 001 supports a 2,097,152-token context window with up to 8,192 output tokens.

Does Gemini 1.5 Pro 001 support function calling?

Yes — Gemini 1.5 Pro 001 supports function (tool) calling.

Is Gemini 1.5 Pro 001 good for production?

Gemini 1.5 Pro 001 is well-suited for pricing — cheaper than 83% of priced chat models on Future AGI and long-context work — top-4 largest context window across 1913 chat models. Consider alternatives if you need already deprecated — provider stopped accepting new traffic 354 days ago.

How can I route to Gemini 1.5 Pro 001 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 1.5 Pro 001

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