Published: · Updated:
Exact ID: gemini-3.5-flash-lite. Check access for your key using GET /v1/models; a published model does not guarantee access for every account.
Prices and billing units
| API429: published rates | Manufacturer: base Standard |
|---|---|
$0.0900 / 1,000,000 cache-write input tokens $0.0090 / 1,000,000 cached input tokens $0.0900 / 1,000,000 input tokens $0.7500 / 1,000,000 output tokens | $0.3 / $2.5 per 1M ordinary input / output tokens Standard; text Manufacturer sourceChecked: Oct 24, 2026. Cache, tools and special modes are excluded from this rate pair. |
API429 catalog generated . This dates the catalog data, not the model’s addition.
Workload budget: input and output
Ordinary input and output are counted, excluding cache, tools, fees and repeated calls. This estimates spending; it does not validate whether a request is accepted. RUB results use only your entered rate; they are neither a bank quote nor a top-up amount.
Specifications and compatibility boundaries
The manufacturer specifies an input limit of 1,048,576 and a maximum output of 65,536 tokens for its own API (specification: Google, checked Oct 24, 2026). These are not verified effective API429 limits: the current public catalog does not publish them. Confirm the required volume and mode before migrating your workload.
API429 capabilities published for this exact ID: chat code_execution context_cache count_tokens function_calling multimodal_input reasoning search structured_output tools url_context vision . A missing property does not mean a prohibition, but it does not establish support. Check input format, tools, JSON/schema, reasoning and streaming separately for the selected method.
Document parsing: agree on missing values
A representative Flash-Lite scenario is extracting an order number, status and date from short text and passing the result to the next processing step. Google highlights throughput, document parsing and simple data extraction for this model. For a useful evaluation, prepare examples with a missing number, two similar dates and conflicting statuses. Decide in advance whether answers should contain an empty value, special marker or explanation of ambiguity. Do not reveal the correct value in an evaluation example. Your application should match extracted data against the source string and check required fields. If the response format is invalid, do not write it directly to a production system. The short text task below needs no file or image. The manufacturer describes multimodal inputs, but a specific format’s support through API429 requires a separate client contract check.
Minimal for simple tasks; check complex steps separately
In the native Gemini API, Flash-Lite defaults to minimal for fast extraction, routing and classification. For supporting agents using tools or multistep reasoning, Google recommends medium or high to avoid ending tool work prematurely. Choose settings for the task’s nature rather than desired speed alone. These are manufacturer recommendations; the API429 example uses basic Chat Completions fields without promising thinking_level support. If the workflow only needs two values from a string, measure that simple option first. If it must reconcile several sources, check solution completeness and the stopping condition separately. A sequence of answers is not a finished autonomous system: the handler must recognize incomplete results and when further checks are required. Evaluate deeper reasoning on a control sample rather than explanation length.
High-volume queues: the cost of an accepted record matters
For recurring document processing, calculate the cost of a correctly accepted record. This may include a retry after a format error, additional review of an ambiguous field and resent text. Start with a small batch of synthetic data or data permitted for processing, and record the share passing your rules. Do not invent numerical accuracy from a few successful examples. The calculator uses current ordinary API429 token rates; run count alone does not predict document sizes. Estimate typical input and output, then examine long queue items separately. Limit retries per record and retain the rejection reason. When no explanation is needed, a short specified format helps control useful output, although a generation limit cannot guarantee factual correctness. Compare with 3.8 Flash on the same sample and acceptance rules.
Moving from an earlier model and comparison boundaries
Google recommends 3.5 Flash-Lite as a migration option for 3.1 Flash-Lite and 2.5 Flash workloads. This is a workload recommendation rather than a claim that the models are aliases or return identical answers. Preserve source examples, expected fields and unknown-value handling, then compare the new and old models. The manufacturer lists input up to 1,048,576 tokens and output up to 65,536, but actual API429 and key limits are established separately. The basic example limits generation to 512 tokens; do not send a long document as your first request. Compare ordinary Standard input and text output rates. Do not substitute Batch or cache conditions without a separate check. Manufacturer and API429 prices have different sources; similar cost alone does not establish equal quality or available capabilities.
Public model observations
Over the last 24 hours: mean successful response time — 5.6 s; service error rate — 0%. Data as of .
Source: public 24-hour statistics. The mean is neither a median nor a response time guarantee; the error rate and observation window refer to the API429 service. Model quality is not measured here.
First request: curl, Python, JavaScript
Create a key, check your balance and set API429_API_KEY on the server. The generation example incurs a charge. It does not retry automatically; a timeout does not prove the operation was not charged. Inspect the content and actual usage after receiving a response. Python and JavaScript first check the available model list.
curl
Before generation, check the exact ID in the response from GET https://gateway.api429.com/v1/models using the same Bearer key.
curl --fail-with-body https://gateway.api429.com/v1/chat/completions \
-H "Authorization: Bearer $API429_API_KEY" \
-H "Content-Type: application/json" \
-d '{"model":"gemini-3.5-flash-lite","messages":[{"role":"user","content":"Extract the number and status from “Order 42, status: ready”. Reply briefly: number — value; status — value."}],"max_tokens":512,"stream":false}'Python 3
import json
import os
import urllib.request
key = os.environ["API429_API_KEY"]
base = "https://gateway.api429.com/v1"
headers = {"Authorization": "Bearer " + key, "Content-Type": "application/json"}
models_request = urllib.request.Request(base + "/models", headers=headers)
with urllib.request.urlopen(models_request, timeout=30) as response:
available = {item["id"] for item in json.load(response)["data"]}
model = "gemini-3.5-flash-lite"
if model not in available:
raise ValueError("Model is unavailable to this key")
payload = json.loads("{\"model\":\"gemini-3.5-flash-lite\",\"messages\":[{\"role\":\"user\",\"content\":\"Extract the number and status from “Order 42, status: ready”. Reply briefly: number — value; status — value.\"}],\"max_tokens\":512,\"stream\":false}")
request = urllib.request.Request(base + "/chat/completions",
data=json.dumps(payload).encode("utf-8"), headers=headers, method="POST")
with urllib.request.urlopen(request, timeout=60) as response:
result = json.load(response)
choice = result["choices"][0]
if choice.get("finish_reason") != "stop" or not choice.get("message", {}).get("content"):
raise ValueError("Incomplete or empty response")
print(choice["message"]["content"])
print(result.get("usage"))JavaScript: Node.js 18+
const key = process.env.API429_API_KEY;
if (!key) throw new Error("Set API429_API_KEY");
const base = "https://gateway.api429.com/v1";
const headers = { Authorization: "Bearer " + key, "Content-Type": "application/json" };
const model = "gemini-3.5-flash-lite";
const available = await fetch(base + "/models", { headers, signal: AbortSignal.timeout(30000) });
if (!available.ok) throw new Error("Models HTTP " + available.status);
if (!(await available.json()).data.some(item => item.id === model)) throw new Error("Model unavailable to this key");
const response = await fetch(base + "/chat/completions", {
method: "POST", headers, signal: AbortSignal.timeout(60000),
body: JSON.stringify({"model":"gemini-3.5-flash-lite","messages":[{"role":"user","content":"Extract the number and status from “Order 42, status: ready”. Reply briefly: number — value; status — value."}],"max_tokens":512,"stream":false})
});
if (!response.ok) throw new Error("Generation HTTP " + response.status);
const result = await response.json();
const choice = result.choices?.[0];
if (choice?.finish_reason !== "stop" || !choice?.message?.content) throw new Error("Incomplete or empty response");
console.log(choice.message.content);
console.log(result.usage);The examples use basic fields from the published API contract. They are checked offline; no successful paid execution or output accuracy is claimed.
n8n: minimal HTTP Request
- Create an HTTP Request with method POST and URL
https://gateway.api429.com/v1/chat/completions. - Store the Bearer key in credentials; add
Content-Type: application/json. Do not put the key in an exported workflow example. - Send the JSON from curl: the exact model
gemini-3.5-flash-lite, messages, max_tokens and stream=false. - After the HTTP node, check
choices,finish_reasonand the response content before writing the result to your production system.
HTTP Request documentation. This recipe describes HTTP Request. Compatibility with specific Agent nodes, SDKs and other API methods needs separate verification.
Three models for your own comparison
These are options for a controlled comparison on the same task, rather than a quality ranking. Base rates apply to a short text request; see the catalog for full pricing.
| Model | API429: input / output per 1M tokens |
|---|---|
Gemini 4 Argongemini-4-argon | $0.6 / $3 |
Gemini 3.8 Flashgemini-3.8-flash | $0.225 / $1.125 |
Gemini 2.5 Flashgemini-2.5-flash | $0.09 / $0.75 |
Version and release date
Manufacturer API release date, Google: . The exact predecessor has not been established in the reviewed sources. The date of addition to API429 is unknown. Current availability is determined by the catalog and key permissions, rather than the manufacturer’s historical release date.
Frequently asked questions
Does Flash-Lite support minimal?
Yes. Google documents minimal as the native default for 3.5 Flash-Lite. That does not automatically establish support for an API429 field with the same name. Use the published gateway contract and test the required mode separately on a short task.
Can I immediately request complex JSON from a document?
Define the schema, required fields and missing-data rule first. Validate both format and correspondence to the source text. Native structured outputs do not establish support for every API429 parameter; this page’s text example does not include one.
Is 3.5 Flash-Lite a new name for 2.5 Flash?
There is no basis for treating these exact IDs as aliases. Google suggests Flash-Lite as a migration direction for relevant workloads. After replacing the model, check existing instructions, value extraction and acceptance criteria on a saved control sample.
How should I compare Flash-Lite with 3.8 Flash for a large queue?
Use identical records, the same required format and predefined validation rules. Measure accepted results, retries and actual tokens. Token price and the Lite name do not determine which model will cost less for your specific process.
Sources and review
- ai.google.dev/gemini-api/docs/models/gemini-3.5-flash-lite
- ai.google.dev/gemini-api/docs/whats-new-gemini-3.6
- ai.google.dev/gemini-api/docs/pricing
- ai.google.dev/gemini-api/docs/changelog
- gateway.api429.com/api/public/openapi.json
Editorial review: . Pricing and general calculator · Getting started · Compare the family: Gemini