Code Gecko
Google Vertex AI completionCode Gecko is a Google Vertex AI text completion model.It supports a 2,048-token context windowwith up to 64 output tokens.Input is priced at $0.125/M tokens and output at $0.125/M tokens. Route Code Gecko via Future AGI's Agent Command Center for unified observability, caching, and 15 routing strategies including cost-optimized fallback.
Estimate Code Gecko spend
Pick a workload, fine-tune the sliders, and see the monthly bill.
Estimate uses $0.1250/M input · $0.1250/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 | $0.125/M | |
| Output | $0.125/M |
Limits
- Context window
- 2,048 tokens
- Max input
- 2,048 tokens
- Max output
- 64 tokens
- Modalities
- text
Capabilities
- Function calling — not advertised
- Parallel tool calls — not advertised
- Vision input — not advertised
- 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
Where it's strong
Watch out for
- !limited context — 2,048-token window is in the bottom quartile; not ideal for long documents or large RAG
- !small context (under 16K tokens)
Benchmarks pending
We haven't logged public benchmark scores for Code Gecko yet. Have one to contribute? Submit a source — citations help us prioritise.
Call Code Gecko 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.# Code Gecko 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/code-gecko",
messages=[{"role": "user", "content": "Hello, Code Gecko!"}],
)
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/code-gecko",
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 ↗Compare with similar models
Code Gecko 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 Code Gecko cost?
Input is priced at $0.125 per 1M tokens and output at $0.125 per 1M tokens (Google Vertex AI, last verified May 7, 2026).
What is the context window of Code Gecko?
Code Gecko supports a 2,048-token context window with up to 64 output tokens.
Does Code Gecko support function calling?
Code Gecko does not currently advertise function-calling support. For agentic workloads, prefer a tool-calling-capable model and route via Agent Command Center for fallback.
Is Code Gecko good for production?
Code Gecko is best evaluated against your own production traces. Pipe traffic through Agent Command Center to compare it head-to-head against alternatives in shadow mode.
How can I route to Code Gecko 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 Code Gecko
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.