Gemini 2.0 Flash Lite preview 02.05
Google AI chat Deprecated 244d agomodel fallback routing to swap models without code changes.
Gemini 2.0 Flash Lite preview 02.05 is a Google AI chat model.It supports a 1,048,576-token context windowwith up to 8,192 output tokens.Input is priced at $0.0750/M tokens and output at $0.300/M tokens. Capabilities include function calling, vision, prompt caching. Route Gemini 2.0 Flash Lite preview 02.05 via Future AGI's Agent Command Center for unified observability, caching, and 15 routing strategies including cost-optimized fallback.
Estimate Gemini 2.0 Flash Lite preview 02.05 spend
Pick a workload, fine-tune the sliders, and see the monthly bill.
Estimate uses $0.0750/M input · $0.3000/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 | $0.0750/M | |
| Output | $0.300/M | |
| Blended (3:1 in:out) | $0.131/M Cross-model comparable price | |
| Cached input | $0.0188/M |
Context & limits
- Context window
- 1,048,576 tokens
- Max input
- 1,048,576 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
Strengths & caveats — when to pick Gemini 2.0 Flash Lite preview 02.05
Data-driven from Gemini 2.0 Flash Lite preview 02.05's percentile within chat peers.
Where it's strong
- +long-context tasks — context window in the top 3% of peers
Watch out for
- !high cost — input + output rates are in the top 87% of priced chat peers; consider a cheaper sibling for high-volume workloads
- !already deprecated — provider stopped accepting new traffic 244 days ago
Benchmark scores
Reported public benchmark numbers. Each row links to the source.
Call Gemini 2.0 Flash Lite preview 02.05 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 Lite preview 02.05 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-2-0-flash-lite-preview-02-05",
messages=[{"role": "user", "content": "Hello, Gemini 2.0 Flash Lite preview 02.05!"}],
)
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-2-0-flash-lite-preview-02-05",
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 ↗Advanced: fallback + cache config (YAML) ▸
strategy: cost-optimized
targets:
- model: gemini-2-0-flash-lite-preview-02-05
provider: google
weight: 80
fallbacks:
- model: gpt-4-1-2025-04-14
provider: azure-openai
- model: gpt-4-1
provider: openai
guardrails: [pii, prompt-injection, secrets]
cache: { exact: true, semantic: true }Compare with similar models
Grouped by Chatbot Arena tier (Gemini 2.0 Flash Lite preview 02.05 sits at 1354 ELO).
≥30 ELO higher
- Claude Fable 5Azure AI Foundry · $10.00/M in · $50.00/M out · 1,000,000 ctx
- Claude Opus 4.6Azure AI Foundry · $5.00/M in · $25.00/M out · 1,000,000 ctx
- Claude Opus 4.6 (2026-02-05)Anthropic · $5.00/M in · $25.00/M out · 1,000,000 ctx
- Qwen3.8 MaxAlibaba DashScope · $2.00/M in · $6.00/M out · 1,000,000 ctx
FAQ
How much does Gemini 2.0 Flash Lite preview 02.05 cost?
Input is priced at $0.0750 per 1M tokens and output at $0.300 per 1M tokens (Google AI, last verified May 7, 2026).
What is the context window of Gemini 2.0 Flash Lite preview 02.05?
Gemini 2.0 Flash Lite preview 02.05 supports a 1,048,576-token context window with up to 8,192 output tokens.
Does Gemini 2.0 Flash Lite preview 02.05 support function calling?
Yes — Gemini 2.0 Flash Lite preview 02.05 supports function (tool) calling.
Is Gemini 2.0 Flash Lite preview 02.05 good for production?
Gemini 2.0 Flash Lite preview 02.05 is well-suited for long-context tasks — context window in the top 3% of peers. Consider alternatives if you need high cost — input + output rates are in the top 87% of priced chat peers; consider a cheaper sibling for high-volume workloads.
How can I route to Gemini 2.0 Flash Lite preview 02.05 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 Lite preview 02.05
Official sources, independent benchmarks, and pricing aggregators — no random search-engine guesses.
Start here — vendor docs are the only authoritative spec.
Third-party evals — verify the marketing.
Cross-check our number against the rest of the ecosystem.