Google · none caching
Gemini Pro Latest
Gemini Pro Latest on Zumik: live pricing, context, and caching, routable by id or alias through one OpenAI-compatible endpoint.
Specifications
At a glance.
| Provider | |
| Family | gemini |
| Released | — |
| License | Proprietary |
| Context window | 1M tokens |
| Max output | 66K tokens |
| Modalities | text, image |
| Tool calling | Yes |
| Reasoning mode | No |
| Caching | none |
| Batch discount | 50% off |
Measured by Zumik
What reuse looks like here.
Pricing, context, and capabilities for Gemini Pro Latest are live, but it is outside the flagship set Zumik benchmarks in depth, so measured reuse, capture, and warm TTFT are not shown yet. Run a workload estimate or route it by id to start collecting traces.
Call it
Same OpenAI client, this model.
from openai import OpenAI
client = OpenAI(base_url="https://api.zumik.ai/v1", api_key="zk_live_...")
r = client.responses.create(
model="gemini-pro-latest",
input="Draft a fix for the failing test.",
)
print(r.usage.input_tokens_cached) # confirm reuseFrequently asked
Gemini Pro Latest, answered.
How much does Gemini Pro Latest cost?
Gemini Pro Latest is an open-weights model routed through Google Gemini. It is priced on the host's serverless size tier rather than a single published per-token list price, so it shows "—" here until profiled.
What is Gemini Pro Latest's context window?
Gemini Pro Latest supports a 1M-token context window with up to 66K output tokens.
Does Gemini Pro Latest support prompt caching?
Yes. Google Gemini uses Implicit context caching caching. In the Zumik corpus, Gemini Pro Latest shows a median cache capture of 76% on agent workloads.
Run Gemini Pro Latest with reuse measured.
Point an OpenAI client at Zumik and see exactly how much of this model's input you are reusing.