Gemini 2.0 Flash preview Image Generation
Google Vertex AI chat Deprecated 180d agomodel fallback routing to swap models without code changes.
Gemini 2.0 Flash preview Image Generation is a Google Vertex AI chat model.It supports a 1,048,576-token context windowwith up to 8,192 output tokens.Input is priced at $0.1000/M tokens and output at $0.400/M tokens. Capabilities include function calling, vision, audio input, prompt caching. Route Gemini 2.0 Flash preview Image Generation via Future AGI's Agent Command Center for unified observability, caching, and 15 routing strategies including cost-optimized fallback.
Estimate Gemini 2.0 Flash preview Image Generation spend
Pick a workload, fine-tune the sliders, and see the monthly bill.
Estimate uses $0.1000/M input · $0.4000/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 | $0.1000/M | |
| Output | $0.400/M | |
| Cached input | $0.0250/M |
Limits
- Context window
- 1,048,576 tokens
- Max input
- 1,048,576 tokens
- Max output
- 8,192 tokens
- Modalities
- vision, audio_in, audio_out, text
Capabilities
- Function calling ✓ supported
- Parallel tool calls ✓ supported
- Vision input ✓ supported
- Audio input ✓ supported
- Audio output ✓ supported
- PDF input — not advertised
- Streaming ✓ supported
- Structured output ✓ supported
- Prompt caching ✓ supported
- Reasoning — not advertised
Where it's strong
- +long-context tasks — context window in the top 2% of peers
- +audio output — only 3% of chat models on Future AGI advertise this
- +audio input — only 4% of chat models on Future AGI advertise this
- +parallel tool calls — only 21% of chat models on Future AGI advertise this
Watch out for
- !already deprecated — provider stopped accepting new traffic 180 days ago
Benchmarks pending
We haven't logged public benchmark scores for Gemini 2.0 Flash preview Image Generation yet. Have one to contribute? Submit a source — citations help us prioritise.
Call Gemini 2.0 Flash preview Image Generation 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.
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 preview Image Generation 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-preview-image-generation",
messages=[{"role": "user", "content": "Hello, Gemini 2.0 Flash preview Image Generation!"}],
)
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-preview-image-generation",
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"))AGENTCC_API_KEY with a key fromapp.futureagi.com.Gateway docs ↗Same model on other providers
gemini-2-0-flash-preview-image-generation is also available via 1 other route. Pricing, regions, and capabilities can differ — compare before routing production traffic.
| Provider | Input / 1M | Output / 1M | Verified |
|---|---|---|---|
| Google AI | $0.1000/M | $0.400/M | May 7, 2026 |
Compare with similar models
Gemini 2.0 Flash preview Image Generation doesn't have a public Arena ELO score yet, so we group by provider only — quality-tier comparisons need a benchmark.
- Claude Opus 4.7Google Vertex AI · $5.00/M in · $25.00/M out · 1,000,000 ctx
- Claude Opus 4.6Google Vertex AI · $5.00/M in · $25.00/M out · 1,000,000 ctx
- Gemini 3.1 Pro previewGoogle Vertex AI · $2.00/M in · $12.00/M out · 1,048,576 ctx
- Gemini 3 Pro PreviewGoogle Vertex AI · $2.00/M in · $12.00/M out · 1,048,576 ctx
FAQ
How much does Gemini 2.0 Flash preview Image Generation cost?
Input is priced at $0.1000 per 1M tokens and output at $0.400 per 1M tokens (Google Vertex AI, last verified May 7, 2026).
What is the context window of Gemini 2.0 Flash preview Image Generation?
Gemini 2.0 Flash preview Image Generation supports a 1,048,576-token context window with up to 8,192 output tokens.
Does Gemini 2.0 Flash preview Image Generation support function calling?
Yes — Gemini 2.0 Flash preview Image Generation supports function (tool) calling, including parallel tool calls.
Is Gemini 2.0 Flash preview Image Generation good for production?
Gemini 2.0 Flash preview Image Generation is well-suited for long-context tasks — context window in the top 2% of peers and audio output — only 3% of chat models on Future AGI advertise this. Consider alternatives if you need already deprecated — provider stopped accepting new traffic 180 days ago.
How can I route to Gemini 2.0 Flash preview Image Generation 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 preview Image Generation
Official sources, independent benchmarks, and pricing aggregators — no random search-engine guesses.
Third-party evals — verify the marketing.
Cross-check our number against the rest of the ecosystem.