Gemini 2.0 Pro exp 02.05
Google Vertex AI chatGemini 2.0 Pro exp 02.05 is a Google Vertex AI chat model.It supports a 2,097,152-token context windowwith up to 8,192 output tokens.Input is priced at $1.25/M tokens and output at $10.00/M tokens. Capabilities include function calling, vision, audio input, prompt caching. Route Gemini 2.0 Pro exp 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 Pro exp 02.05 spend
Pick a workload, fine-tune the sliders, and see the monthly bill.
Estimate uses $1.25/M input · $10.00/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 May 7, 2026.
| Input | $1.25/M | |
| Output | $10.00/M | |
| Cached input | $0.313/M |
Limits
- Context window
- 2,097,152 tokens
- Max input
- 2,097,152 tokens
- Max output
- 8,192 tokens
- Modalities
- vision, audio_in, pdf, video, 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 — not advertised
Where it's strong
- +pricing — cheaper than 79% of priced chat models on Future AGI
- +long-context work — top-4 largest context window across 1913 chat models
- +audio input — only 4% of chat models on Future AGI advertise this
- +PDF input — only 16% of chat models on Future AGI advertise this
- +parallel tool calls — only 21% of chat models on Future AGI advertise this
Watch out for
- No major caveats flagged from public spec.
Benchmarks pending
We haven't logged public benchmark scores for Gemini 2.0 Pro exp 02.05 yet. Have one to contribute? Submit a source — citations help us prioritise.
Call Gemini 2.0 Pro exp 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 Pro exp 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="vertex-ai/gemini-2-0-pro-exp-02-05",
messages=[{"role": "user", "content": "Hello, Gemini 2.0 Pro exp 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="vertex-ai/gemini-2-0-pro-exp-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 ↗Same model on other providers
gemini-2-0-pro-exp-02-05 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 | — | — | May 7, 2026 |
Compare with similar models
Gemini 2.0 Pro exp 02.05 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 Pro exp 02.05 cost?
Input is priced at $1.25 per 1M tokens and output at $10.00 per 1M tokens (Google Vertex AI, last verified May 7, 2026).
What is the context window of Gemini 2.0 Pro exp 02.05?
Gemini 2.0 Pro exp 02.05 supports a 2,097,152-token context window with up to 8,192 output tokens.
Does Gemini 2.0 Pro exp 02.05 support function calling?
Yes — Gemini 2.0 Pro exp 02.05 supports function (tool) calling, including parallel tool calls.
Is Gemini 2.0 Pro exp 02.05 good for production?
Gemini 2.0 Pro exp 02.05 is well-suited for pricing — cheaper than 79% of priced chat models on Future AGI and long-context work — top-4 largest context window across 1913 chat models.
How can I route to Gemini 2.0 Pro exp 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 Pro exp 02.05
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.