Gemini 3.5 Flash Lite is a cost-optimized, high-throughput model built for processing massive context windows. Reach for it when you need fast, inexpensive text generation from multimodal inputs at scale.
Modalities
Text+Image → Text
Below release
Not established
Weights
Not published
Where it sits in the catalogue Kyma measures
Every number against every text model Kyma prices per token — a stated rule, not a chosen line-up.
$0.405
output $3.375 · cached $0.0405
median $1.009 · best $0.0494
$3.375
per 1M tokens generated
median $3.528 · best $0.2164
97.89%
1,377 observations since 2026-07-29
median 93.5% · best 100.0%
53.4 tok/s
probe median, one fixed prompt
median 39.3 tok/s · best 321.8 tok/s
1.12 s
probe median, to a complete answer
median 2.54 s · best 0.86 s
1.05M
max output 8,192
published by Google, not measured here
Tick above each rail is this model, below it the other 68. Dashed rule is the field median, solid is its best. Better is left; the axis stops at the 90th percentile, so a few models sit past its right edge.
Usage
How much this model is actually called here.
Rank
#22
of 98 active models
Tokens served
12.0M
all-time
Platform share
0.4%
of all tokens
How it behaves under real clients
The same model answering different prompt shapes — measured, not benchmarked.
| Client | Requests | Tokens | Throughput | To first token | p95 total | Completed |
|---|---|---|---|---|---|---|
| Python App | 132 | 11.4M | 216 tok/s | 2.45 s | 26 s | 99.2% |
Grouped by the client that sent the request. Not a benchmark: the same model on different prompt shapes. Throughput and time-to-first-token are medians; p95 is the slowest response in twenty. 1 client under 100 requests not shown.
Two clocks, and why they disagree
Kyma measures this model twice. Both are real; they answer different questions.
Probe · every 6h · 30 days
1.12s to answer
One fixed prompt, on a schedule, to every model. Comparable, because the model is the only thing that changes.
- Observations
- 1,377
- Answered by a substitute
- 14
Real traffic · last 7 days
2.25s to answer
Your requests, at the lengths clients actually send. Not comparable between models, but it is what running this one feels like.
- Requests
- 48
- Completed
- 93.8%
- p95
- 5.2 s
Caching, as realised · last 7 days
0.0% of input cached
The share of input that actually hit cache, so the effective rate below is what was charged, not a best case.
- Cached input
- 0
- Fresh input
- 20.3K
- List input
- $0.405 /1M
- Effective input
- $0.405 /1M
The gap is prompt length, not the model degrading. Use the probe figure to choose between models, the traffic figure to budget for your own.
Pricing
Pay per token. Cached input bills at this model’s own cached rate, listed below.
+ Estimate your workload− Estimate your workload
Estimated monthly cost
$68.36
$2.28 / day on Gemini 3.5 Flash Lite
Same workload on:
Estimates use list pricing with cached input at this model's own cached rate. Actual bills depend on real token counts, and every response includes its exact cost.
When to use Gemini 3.5 Flash Lite
Where this model earns its cost — and where it doesn't.
This model is Google's entry-level tier for 1M-token context windows. It accepts text, images, audio, and video as input, but generates text-only output. The architecture prioritizes throughput and low latency, making it suitable for batch processing and high-volume workloads.
On Kyma, the model runs through an OpenAI-compatible endpoint with automatic request failover. It supports tool calling and prompt caching, which bills repeated prefixes at this model's cached input rate. Every response includes exact usage costs in the usage.cost field and identifies the routed model via the X-Kyma-Model header.
The model caps output at 8,192 tokens and does not support native structured outputs or explicit reasoning traces. Thinking tokens are included in the output pricing, so monitor token counts if your prompts trigger internal processing.
High Volume Document Analysis
Process long reports or transcripts to extract key data points without hitting context limits.
Automated Content Categorization
Route large batches of user messages or logs into predefined labels using tool integration.
Audio And Video Summarization
Condense multimedia recordings and image sets into concise text summaries.
Fast Interactive Chat Routing
Handle lightweight conversational turns where response speed matters more than complex reasoning.
Not ideal for: Do not use this model for tasks requiring explicit reasoning chains, strict JSON schema enforcement, or outputs longer than 8,192 tokens.
How it compares
Against the peers people actually weigh it against.
| Spec | Gemini 3.5 Flash Lite | Gemini 3.8 Flash | Gemini 3.1 Pro |
|---|---|---|---|
| Input /1M | $0.405 | $1.013 | $2.70 |
| Output /1M | $3.375 | $5.063 | $16.20 |
| Context | 1M | 1M | 1M |
| Tools | Yes | Yes | Yes |
| Reasoning | Yes | Yes | Yes |
| Throughput | 53.4 tok/s | 35 tok/s | 95.3 tok/s |
Quick start
Up and running in under two minutes.
- 1
Create an API key
Sign up and grab a key from the dashboard. Gemini 3.5 Flash Lite needs a top-up — the signup credit covers the free tier.
Get API key → - 2
Make your first request
Drop in your key and send a chat completion — fully OpenAI-compatible.
curl https://kymaapi.com/v1/chat/completions \ -H "Authorization: Bearer YOUR_API_KEY" \ -H "Content-Type: application/json" \ -d '{ "model": "gemini-3.5-flash-lite", "messages": [ {"role": "user", "content": "Explain prompt caching in one paragraph."} ] }' - 3
Stream responses
Add
"stream": trueto receive tokens as they arrive.curl https://kymaapi.com/v1/chat/completions \ -H "Authorization: Bearer YOUR_API_KEY" \ -H "Content-Type: application/json" \ -d '{ "model": "gemini-3.5-flash-lite", "stream": true, "messages": [{"role": "user", "content": "Hello!"}] }'
FAQ
Common questions about this model.
What is the context window of Gemini 3.5 Flash Lite?
How much does the Gemini 3.5 Flash Lite API cost?
Does Gemini 3.5 Flash Lite support function calling?
Are the weights for Gemini 3.5 Flash Lite publicly available?
Is Gemini 3.5 Flash Lite ever served below the precision its creator released it at?
How do I use Gemini 3.5 Flash Lite?
Does this model support structured JSON outputs natively?
How does prompt caching affect my input costs?
Can I send audio and video files directly to the API?
More models by Google
See all 14 →| Model | Context | Input | Output |
|---|---|---|---|
| 1M | $1.013 | $5.063 | |
| — | $0.00675 / min | ||
| 1M | $1.013 | $5.063 | |
| 1M | $1.013 | $5.063 | |
| 1M | $2.025 | $12.15 | |
| 128K | $0.0763 | $0.218 | |
| — | $0.061 / image | ||
| 1M | $2.70 | $16.20 | |