Gemini 2.5 Flash-Lite API
NewLLMGemini 2.5 Flash-Lite is the cheapest Gemini route on the gateway, keeping 1M context, vision, and tool use.
- Input · USD / 1M tokens$0.085 USDOfficial price
$0.1 USD - Output · USD / 1M tokens$0.34 USDOfficial price
$0.4 USD - Savings15%
- Context1M
- View tool pricing and billing rules
What are we making today?
Bring an idea, a question, or a first draft.
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What this model is for
Gemini 2.5 Flash-Lite is the cheapest Gemini route on the gateway, keeping 1M context, vision, and tool use.
Gemini 2.5 Flash-Lite is the lowest-cost Gemini model in the OmniaKey catalog, listed under the id gemini-2.5-flash-lite. It still carries a 1M-token context window, image input, tool use, the fast label and the same three coding clients as the rest of the family. All three of its rates, input, output and cached input, are below every other Gemini entry, including Gemini 3.5 Flash-Lite and Gemini 2.5 Flash. The catalog marks it as a new model even though its generation name is 2.5.
That combination sets the job it suits: a narrow request, a short answer, and a count high enough that the cheapest tier is what makes the feature viable. Spam screening, intent labels, receipt fields, language detection and short dispatch tags all fit. The 1M window is a bonus rather than the reason to choose it, since a model at this tier does its best work on a short, specific prompt with one clear output shape.
Design for a small model rather than hoping for a large one. Give it an enumerated answer space, ask for one object and nothing else, validate the result, and send failures to a higher tier. The catalog flags this id as new while a newer 3.x Lite model sits above it in rate, so the flag says the listing is recent, not that the model is the newest generation. Check both before assuming which one is right for a new pipeline.
Best-fit coding workloads
Abuse screening at scale
Score every new listing or comment for a short list of policy categories and return a label plus a one-line reason. A binary or three-way answer keeps this tier cheap enough for the whole feed. Practical tip: hold a human-reviewed sample every week and watch the false-negative rate more closely than the average.
Receipt line extraction
Photograph a receipt and ask for merchant, date, total and the line items as a small array. Image input covers the photo and the short answer keeps the output side minimal. Practical tip: accept nulls for unreadable lines, and send any receipt with a missing total to a model at a higher tier instead of letting a guess through.
Intent labels for search logs
Reduce thousands of raw search phrases to a fixed set of intents so a dashboard stops counting noise. One word per row suits the tier, and the 1M window lets you put a full taxonomy in the system message. Practical tip: version the taxonomy, and re-run a fixed sample whenever labels change so trends stay comparable.
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Technical specification
Catalog facts and integration details verified for this route.
- Model ID
- gemini-2.5-flash-lite
- Context
- 1M
- Inputs and tools
- Vision · Tool use · Fast responses
- API endpoint
- /v1/chat/completions
- Cache hit / 1M
- $0.0085 USD
- Coding clients
- Cursor · Cline · Aider
Limits to plan around
- It is the cheapest Gemini listing but also the one with the least headroom. Prompts that need multi-step reasoning, careful arithmetic or long tool chains fail here more often, and a failed cheap call still costs the retry.
- The catalog flags this id as new while its generation name is 2.5 and Gemini 3.5 Flash-Lite sits above it in rate. Read the flag as listing recency, and compare the two on your own prompts before picking one for a new pipeline.
- No thinking-level control or batch mode is listed for this id. Volume work therefore needs your own queue, retry policy and validator, and long outputs should be avoided rather than encouraged.
- The 1M window invites very large prompts, which is the wrong shape for a small model: more unrelated context tends to dilute a narrow question rather than improve it.
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Compare nearby models
Compare workload fit and current listed token rates before choosing a route.
| Model | Best for | Context | Input | Output |
|---|---|---|---|---|
| Gemini 2.5 Flash-LiteThis page gemini-2.5-flash-lite | The lowest-cost Gemini listing, for narrow high-frequency tasks with a fixed answer space. | 1M | $0.085 USD Official price $0.1 USD | $0.34 USD Official price $0.4 USD |
| Gemini 2.5 Flash gemini-2.5-flash | A higher rate band and more headroom, for tasks that outgrow one-word answers. | 1M | $0.255 USD Official price $0.3 USD | $2.125 USD Official price $2.5 USD |
| Gemini 3.5 Flash-Lite gemini-3.5-flash-lite | The newer Lite entry at higher rates, worth testing when quality matters more than the smallest bill. | 1M | $0.255 USD Official price $0.3 USD | $2.125 USD Official price $2.5 USD |
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SDK quickstarts
Use one base URL and model ID from cURL, Python, or TypeScript.
curl https://api.omniakey.com/v1/chat/completions \
-H "Authorization: Bearer $OMNIAKEY_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"model": "gemini-2.5-flash-lite",
"messages": [
{"role": "user", "content": "Review this pull request"}
],
"stream": true
}'05
Estimate token cost
Enter expected input and output tokens to compare current listed rates.
- OmniaKey estimate
- $0.0153
- Official-rate estimate
- $0.018
- Estimated savings
- $0.0027
Estimate covers input and output tokens only. Cache usage, retries, tools, and client-side token accounting can change the final charge.
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Related coding guides
Deeper selection, setup, and troubleshooting guidance for this model family.
Gemini 3.8 Flash API Pricing and Agent Cost
Google's introductory rate is $0.75 input and $3.75 output per million tokens, but retries and thinking decide the cost of an accepted result.
Read guideGemini 4 Argon review: a powerful launch, not a public API yet
Argon looks like a serious frontier upgrade, but the sensible launch-day decision is to evaluate the evidence and wait for a callable contract before migrating production traffic.
Read guide07
Sources and verification
Model facts and links were checked on 2026-10-27. Provider documentation remains the authority for upstream behavior.
Frequently asked questions
How much does Gemini 2.5 Flash-Lite cost on OmniaKey?
OmniaKey charges $0.085 USD per 1M input tokens and $0.34 USD per 1M output tokens, in USD. Official prices are $0.1 USD and $0.4 USD; you save 15%.
What is the context window for Gemini 2.5 Flash-Lite?
The listed context window is 1M. Actual usable limits can also depend on the client and upstream request format.
Is Gemini 2.5 Flash-Lite the cheapest Gemini model?
Yes. Its input, output and cached-input rates are the lowest of any Gemini entry in the catalog, below Gemini 2.5 Flash and Gemini 3.5 Flash-Lite. The live price table on the model page carries the current numbers, and the catalog is the place to confirm that no cheaper listing has appeared.
How is it billed?
Three rates apply: one per input token, one per output token and a lower one for cached input. The catalog shows a single band, so prompt length does not move a call into a second tier. Cached input is worth checking on repeated prompts with a long shared prefix, such as a fixed taxonomy or instruction block.
How do I call Gemini 2.5 Flash-Lite on OmniaKey?
POST to https://api.omniakey.com/v1/chat/completions with gemini-2.5-flash-lite as the model. The body is OpenAI-compatible, so image parts and tool definitions go in the messages array beside the text. The id is case-sensitive and contains dots, and one key reaches every listed model.
Can it read images?
The catalog lists vision, and clients can send image parts in the same message as text. Keep the visual question narrow, such as one field on a form or one product in a photo, because a small model drifts when asked for an open reading. Test on your own scans, since photographed pages vary far more than screenshots.
What should I not use it for?
Long reasoning chains, careful counting across a document, and multi-step tool use are poor fits. Code review, policy reading and anything where a wrong number is expensive belong on a Pro model. Use this tier for the parts of a pipeline where the answer space is small and a validator can reject a bad result.