Gemini · Fast / Budget · 1,000K context window

Gemini 3.5 Flash-Lite pricing for categorization

$0.000615 per call at 800 input / 150 output tokens.

Per call

$0.000615

10K calls/mo

$6.15

Cache savings

90% off input

Batch savings

50% off all

Calculate your Gemini 3.5 Flash-Lite costs

Adjust token counts, volume, and discount toggles to model your categorization spend. Prices verified daily against provider pricing pages.

Configure your usage

800
100100K
150
5050K
10,000
1001M

Estimated cost

Monthly cost
$6
10,000 calls/month
Cost per call$0.000615
Daily cost$0.205
Input rate$0.30/MTok
Output rate$2.50/MTok
Analyze your real spend

Quick start

Call Gemini 3.5 Flash-Lite with the Google Generative AI SDK:

import google.generativeai as genai

model = genai.GenerativeModel("gemini-3.5-flash-lite")
response = model.generate_content("Your prompt here")
# Cost: ~$0.000615 per call at standard rates
# Input:  $0.30/MTok
# Output: $2.50/MTok

How Gemini 3.5 Flash-Lite compares on cost

Per-call cost for all models scoring 50+ on categorization benchmarks. Hover for details.

Cheapest viable option: GPT 5.6 Luna at $0.000340/call (45% less, 91/100 quality).

What drives categorization cost

Classification into a fixed taxonomy is token-efficient by construction: the taxonomy is the same on every call and the output is one label. Put the taxonomy in the cached prefix and the marginal cost per item approaches the cost of the item text alone. Model tier matters less here than in any other use case tracked.

For Gemini 3.5 Flash-Lite specifically, that means output tokens cost 8.3x more than input, at $2.50 vs $0.30 per MTok. At this use case’s 800/150 token split, output accounts for 61% of the $0.000615 per-call cost.

Complete Gemini 3.5 Flash-Lite pricing breakdown

Standard token rates

Direction$/MTokTokens per call
Input$0.30800
Output$2.50150

Prompt caching: 90% off input tokens

Caching drops input cost from $0.30 to $0.03/MTok. For repeated system prompts, that saves $0.000216 per call.

Batch API: 50% off all tokens

Submit requests asynchronously and receive 50% off all token costs. This works best for offline pipelines where latency requirements are flexible.

Monthly cost projections

Monthly volumeCost per callStandard monthlyCached monthlyYou save with caching
10,000 calls$0.000615$6.15$3.99$2.16
50,000 calls$0.000615$30.75$19.95$10.8
100,000 calls$0.000615$61.5$39.9$21.6
500,000 calls$0.000615$307.5$199.5$108
1,000,000 calls$0.000615$615$399$216

Gemini 3.5 Flash-Lite quality benchmarks for categorization

Gemini 3.5 Flash-Lite is a solid pick for categorization

Scores 85/100 (rank #4 of 20). Good balance of quality and cost for categorization.

Top-ranked: Gemini 3.5 Flash (92/100) at $0.002550/call

Performance across all task types

Gemini 3.5 Flash-Lite scores by task type. Categorization highlighted.

Classification *85Extraction83Summarization79Q&A78Code Generation55Code Review52Reasoning50Creative Writing45
Task typeConfidence scoreRank out of 20
Classification(current page)85/100#4
Extraction83/100#5
Summarization79/100#6
Q&A78/100#6
Code Generation55/100#8
Code Review52/100#8
Reasoning50/100#8
Creative Writing45/100#9

Confidence scores are a third-party benchmark snapshot from week 29 of 2026. This snapshot is 8 weeks old, so treat the scores as directional and validate against your own evals.

Alternative models for categorization

13 models score 80+ on categorization benchmarks, sorted by input rate. Cheapest: GPT 5.6 Luna (45% less, 91/100 quality).

ModelProviderInput $/MTokOutput $/MTokQualityPer callvs Gemini
GPT 5.6 LunaGPT$0.20$1.2091/100$0.00034045% cheaper
Gemini 3 FlashGemini$0.50$3.0088/100$0.00085038% more
Claude Haiku 4.5Claude$1.00$5.0090/100$0.001550152% more
Gemini 3.5 FlashGemini$1.50$9.0092/100$0.002550315% more
Claude Sonnet 5Claude$2.00$10.0086/100$0.003100404% more
GPT 5.6 TerraGPT$2.00$12.0089/100$0.003400453% more
Gemini 3.1 ProGemini$2.00$12.0086/100$0.003400453% more
GPT 5.4GPT$2.50$15.0088/100$0.004250591% more
Claude Sonnet 4.6Claude$3.00$15.0084/100$0.004650656% more
GPT 5.6 SolGPT$4.00$20.0086/100$0.006200908% more
Claude Opus 4.8Claude$5.00$25.0080/100$0.0077501160% more
GPT 5.5GPT$5.00$30.0085/100$0.0085001282% more
Claude Fable 5Claude$10.00$50.0082/100$0.01552420% more

About Gemini 3.5 Flash-Lite

Provider

Gemini

Tier

Fast / Budget

Context

1,000K tokens

Released

Jun 2026

Other models from Gemini

ModelTierInput $/MTokOutput $/MTokContext
Gemini 3.1 ProMid-tier$2.00$12.001,000K
Gemini 3.5 FlashFast / Budget$1.50$9.001,000K
Gemini 3 FlashFast / Budget$0.50$3.001,000K

You can compare Gemini 3.5 Flash-Lite head-to-head against any other model on our model comparison pages, or track how pricing has changed over time on the pricing history tracker.

Frequently asked questions

How much does Gemini 3.5 Flash-Lite cost for categorization per API call?

A typical categorization call using Gemini 3.5 Flash-Lite costs about $0.000615 per call. This estimate uses 800 input tokens and 150 output tokens at standard rates. Standard rates are $0.30 per million input tokens and $2.50 per million output tokens.

Is Gemini 3.5 Flash-Lite the best model for categorization?

Gemini 3.5 Flash-Lite scores 85 out of 100 on categorization benchmarks overall. It ranks #4 across all 20 models in our cross-provider registry. The highest-ranked model for this task is Gemini 3.5 Flash from Gemini. That model scores 92/100 on this task type. Confidence scores are a third-party benchmark snapshot from week 29 of 2026. This snapshot is 8 weeks old, so treat the scores as directional and validate against your own evals.

What is the cheapest model for categorization with good quality?

The most affordable model for categorization above 80/100 quality is GPT 5.6 Luna. It comes from GPT at $0.20 per million input tokens. Output costs $1.20 per million tokens with a quality score of 91/100. Switching from Gemini 3.5 Flash-Lite to GPT 5.6 Luna saves about 45% per API call.

How can I reduce my Gemini 3.5 Flash-Lite costs for categorization?

Three strategies lower Gemini 3.5 Flash-Lite costs for this task type effectively. Prompt caching gives a 90% discount on input tokens when reusing system prompts. The batch API gives 50% off all tokens for asynchronous processing workloads. Prompt optimization reduces token counts through more concise instructions and context windows. Combining caching with batching brings your cost from $0.000615 to about $0.000031 per call.

How does Gemini 3.5 Flash-Lite pricing compare to other Gemini models?

Gemini has 3 other models alongside Gemini 3.5 Flash-Lite today: Gemini 3.1 Pro at $2.00/$12.00 per million tokens (mid-tier), Gemini 3.5 Flash at $1.50/$9.00 per million tokens (fast / budget), Gemini 3 Flash at $0.50/$3.00 per million tokens (fast / budget). The right choice depends on whether your categorization workload prioritizes quality, cost, or speed.

What context window does Gemini 3.5 Flash-Lite support?

Gemini 3.5 Flash-Lite supports a context window of 1,000K tokens per API call. This sets the maximum combined length of your input prompt and generated response. For categorization, typical calls use 800 input and 150 output tokens. That is well within this limit, leaving room for longer prompts or multi-turn conversations.

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This calculator estimates costs based on published rates only. Connect your API usage to see where your money goes and which models drive your spend.