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Google · none caching

Gemini 2.0 Flash-Lite 001

Gemini 2.0 Flash-Lite 001 on Zumik: live pricing, context, and caching, routable by id or alias through one OpenAI-compatible endpoint.

Call it through ZumikAbout Google Gemini
$0.07
Input / 1M tokens
$0.30
Output / 1M tokens
$0.07
Cache read
1M
Context window

Specifications

At a glance.

ProviderGoogle
Familygemini-2.0
Released2024-12
LicenseProprietary
Context window1M tokens
Max output8K tokens
Modalitiestext, image, audio, video, pdf
Tool callingYes
Reasoning modeNo
Cachingnone
Batch discount50% off

Measured by Zumik

What reuse looks like here.

Not yet profiled

Pricing, context, and capabilities for Gemini 2.0 Flash-Lite 001 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.

Reuse economics

What you actually pay once caching works.

At a typical 55% prefix reuse, a million input tokens on Gemini 2.0 Flash-Lite 001 effectively costs $0.07 instead of $0.07 - blending to roughly $0.13 with a 25% output share. Background work drops a further 50% on the batch tier.

Estimate it for your workload
Best for
textimageaudiovideopdf

Route it directly by id, or let an alias pick it when it wins under policy.

Call it

Same OpenAI client, this model.

python
from openai import OpenAI

client = OpenAI(base_url="https://api.zumik.ai/v1", api_key="zk_live_...")

r = client.responses.create(
    model="gemini-2-0-flash-lite-001",
    input="Draft a fix for the failing test.",
)
print(r.usage.input_tokens_cached)   # confirm reuse

Frequently asked

Gemini 2.0 Flash-Lite 001, answered.

How much does Gemini 2.0 Flash-Lite 001 cost?

Gemini 2.0 Flash-Lite 001 is $0.07 per million input tokens and $0.30 per million output tokens through Zumik. Cache reads are $0.07 per million, a 0% discount on input.

What is Gemini 2.0 Flash-Lite 001's context window?

Gemini 2.0 Flash-Lite 001 supports a 1M-token context window with up to 8K output tokens.

Does Gemini 2.0 Flash-Lite 001 support prompt caching?

Yes. Google Gemini uses Implicit context caching caching. In the Zumik corpus, Gemini 2.0 Flash-Lite 001 shows a median cache capture of 75% on agent workloads.

Run Gemini 2.0 Flash-Lite 001 with reuse measured.

Point an OpenAI client at Zumik and see exactly how much of this model's input you are reusing.

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