Gemini 2.5 Computer Use preview 10 2025
Google Vertex AI chatGemini 2.5 Computer Use preview 10 2025 is a Google Vertex AI chat model.It supports a 128,000-token context windowwith up to 64,000 output tokens.Input is priced at $1.25/M tokens and output at $10.00/M tokens. Capabilities include function calling, vision. Route Gemini 2.5 Computer Use preview 10 2025 via Future AGI's Agent Command Center for unified observability, caching, and 15 routing strategies including cost-optimized fallback.
Estimate Gemini 2.5 Computer Use preview 10 2025 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 Oct 22, 2026.
| Input | $1.25/M | |
| Output | $10.00/M | |
| Blended (3:1 in:out) | $3.44/M Cross-model comparable price |
Context & limits
- Context window
- 128,000 tokens
- Max input
- 128,000 tokens
- Max output
- 64,000 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 — not advertised
- Prompt caching — not advertised
- Reasoning — not advertised
Strengths & caveats — when to pick Gemini 2.5 Computer Use preview 10 2025
Data-driven from Gemini 2.5 Computer Use preview 10 2025's percentile within chat peers.
Where it's strong
- +pricing — cheaper than 76% of priced chat models on Future AGI
Watch out for
- !strict structured output — no JSON-schema enforcement, expect retry loops
Benchmarks pending
We haven't logged public benchmark scores for Gemini 2.5 Computer Use preview 10 2025 yet. Have one to contribute? Submit a source — citations help us prioritise.
Call Gemini 2.5 Computer Use preview 10 2025 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 2.5 Computer Use preview 10 2025 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-2-5-computer-use-preview-10-2025",
messages=[{"role": "user", "content": "Hello, Gemini 2.5 Computer Use preview 10 2025!"}],
)
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-2-5-computer-use-preview-10-2025",
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-2-5-computer-use-preview-10-2025 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 | $1.25/M | $10.00/M | Oct 22, 2026 |
Explore similar models
Gemini 2.5 Computer Use preview 10 2025 doesn't have a public Arena ELO score yet, so we group by provider only — quality-tier comparisons need a benchmark. Side-by-side links appear where a comparison page exists; otherwise, open the model profile.
- Claude Opus 4.7Google Vertex AI · $5.00/M in · $25.00/M out · 1,000,000 ctxView model →
- Claude Opus 4.6Google Vertex AI · $5.00/M in · $25.00/M out · 1,000,000 ctxView model →
- Gemini 3.1 Pro previewGoogle Vertex AI · $2.00/M in · $12.00/M out · 1,048,576 ctxView model →
- Gemini 3 Pro PreviewGoogle Vertex AI · $2.00/M in · $12.00/M out · 1,048,576 ctxView model →
FAQ
How much does Gemini 2.5 Computer Use preview 10 2025 cost?
Input is priced at $1.25 per 1M tokens and output at $10.00 per 1M tokens (Google Vertex AI, last verified Oct 22, 2026).
What is the context window of Gemini 2.5 Computer Use preview 10 2025?
Gemini 2.5 Computer Use preview 10 2025 supports a 128,000-token context window with up to 64,000 output tokens.
Does Gemini 2.5 Computer Use preview 10 2025 support function calling?
Yes — Gemini 2.5 Computer Use preview 10 2025 supports function (tool) calling.
Is Gemini 2.5 Computer Use preview 10 2025 good for production?
Gemini 2.5 Computer Use preview 10 2025 is well-suited for pricing — cheaper than 76% of priced chat models on Future AGI. Consider alternatives if you need strict structured output — no JSON-schema enforcement, expect retry loops.
How can I route to Gemini 2.5 Computer Use preview 10 2025 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 2.5 Computer Use preview 10 2025
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.