Gemini · Fast / Budget · 1.0M context window

Gemini 3.5 Flash-Lite pricing for invoice parsing

$0.002100 per call at 2,000 input / 600 output tokens.

Per call

$0.002100

10K calls/mo

$21

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 invoice parsing spend. Prices verified daily against provider pricing pages.

Configure your usage

2,000
100100K
600
5050K
10,000
1001M

Estimated cost

Monthly cost
$21
10,000 calls/month
Cost per call$0.002100
Daily cost$0.70
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: ~$0.002100 per call at standard rates
# Input:  $0.30/MTok
# Output: $2.50/MTok

What drives invoice parsing cost

Invoices are short, highly repetitive documents processed in bulk: the ideal batch API workload. Per-document cost is low; total cost is set by volume and by whether you are paying full rate for a job that could have run asynchronously overnight at a discount. The extraction schema is constant, so it should never be paying full input rate either.

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 2,000/600 token split, output accounts for 71% of the $0.002100 per-call cost.

Complete Gemini 3.5 Flash-Lite pricing breakdown

Standard token rates

Direction$/MTokTokens per call
Input$0.302,000
Output$2.50600

Prompt caching: 90% off input tokens

Caching drops input cost from $0.30 to $0.03/MTok. For repeated system prompts, that saves $0.000540 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$0.002100$21$15.6$5.4
50,000 calls$0.002100$105$78$27
100,000 calls$0.002100$210$156$54
500,000 calls$0.002100$1,050$780$270
1,000,000 calls$0.002100$2,100$1,560$540

Gemini 3.5 Flash-Lite quality benchmarks for invoice parsing

Consider alternatives for invoice parsing

Scores 69/100 (rank #30 of 88). Better options exist at similar price points for invoice parsing.

Top-ranked: Claude Haiku 4.5 (88/100) at $0.005000/call

Performance across all task types

Gemini 3.5 Flash-Lite scores by task type. Invoice Parsing highlighted.

Classification85Q&A78Extraction *69Summarization67Creative Writing67Reasoning60Code Generation58Code Review52
Task typeConfidence scoreRank out of 88
Classification85/100#4
Q&A78/100#6
Extraction(current page)69/100#30
Summarization67/100#16
Creative Writing67/100#23
Reasoning60/100#30
Code Generation58/100#23
Code Review52/100#8

Confidence scores are a third-party benchmark snapshot from week 26 of 2026. This snapshot is 17 weeks old, so treat the scores as directional and validate against your own evals.

Alternative models for invoice parsing

2 models score 80+ on invoice parsing benchmarks, sorted by input rate. Cheapest: Gemini 3 Flash (33% more, 86/100 quality).

ModelProviderInput $/MTokOutput $/MTokQualityPer callvs Gemini
Gemini 3 FlashGemini$0.50$3.0086/100$0.00280033% more
Claude Haiku 4.5Claude$1.00$5.0088/100$0.005000138% more

About Gemini 3.5 Flash-Lite

Provider

Gemini

Tier

Fast / Budget

Context

1.0M tokens

Released

Jun 2026

Other models from Gemini

ModelTierInput $/MTokOutput $/MTokContext
Gemini 3.1 ProMid-tier$2.00$12.001.0M
Gemini 3.5 FlashFast / Budget$1.50$9.001.0M
Gemini 3 FlashFast / Budget$0.50$3.001.0M
Gemini 2.5 Computer UseFast / Budget$1.25$10.00128K
Gemini 2.5 FlashFast / Budget$0.30$2.501.0M
Gemini 2.5 Flash-LiteFast / Budget$0.10$0.401.0M
Gemini 2.5 ProMid-tier$1.25$10.001.0M
Gemini 3.1 Flash-LiteFast / Budget$0.25$1.501.0M
Gemini 3.1 Pro Custom ToolsMid-tier$2.00$12.001.0M
Gemini 3.6 FlashFast / Budget$0.75$3.751.0M
Gemini 3.7 FlashFast / Budget$0.75$3.751.0M
Gemini 3.8 FlashFast / Budget$0.75$3.751.0M
Gemini Omni 1.1 FlashFast / Budget$1.50$9.001.0M
Gemini Omni FlashFast / Budget$1.50$9.001.0M
Gemini Robotics ER 2Fast / Budget$1.00$5.00131K

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 invoice parsing per API call?

A typical invoice parsing call using Gemini 3.5 Flash-Lite costs about $0.002100 per call. This estimate uses 2,000 input tokens and 600 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 invoice parsing?

Gemini 3.5 Flash-Lite scores 69 out of 100 on invoice parsing benchmarks overall. It ranks #30 across all 88 models in our cross-provider registry. The highest-ranked model for this task is Claude Haiku 4.5 from Claude. That model scores 88/100 on this task type. Confidence scores are a third-party benchmark snapshot from week 26 of 2026. This snapshot is 17 weeks old, so treat the scores as directional and validate against your own evals.

What is the cheapest model for invoice parsing with good quality?

The most affordable model for invoice parsing above 80/100 quality is Gemini 3 Flash. It comes from Gemini at $0.50 per million input tokens. Output costs $3.00 per million tokens with a quality score of 86/100. Gemini 3 Flash costs more per call than Gemini 3.5 Flash-Lite but scores higher on quality benchmarks for this task type.

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

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 $0.002100 to about $0.000105 per call.

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

Gemini has 15 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), Gemini 2.5 Computer Use at $1.25/$10.00 per million tokens (fast / budget), Gemini 2.5 Flash at $0.30/$2.50 per million tokens (fast / budget), Gemini 2.5 Flash-Lite at $0.10/$0.40 per million tokens (fast / budget), Gemini 2.5 Pro at $1.25/$10.00 per million tokens (mid-tier), Gemini 3.1 Flash-Lite at $0.25/$1.50 per million tokens (fast / budget), Gemini 3.1 Pro Custom Tools at $2.00/$12.00 per million tokens (mid-tier), Gemini 3.6 Flash at $0.75/$3.75 per million tokens (fast / budget), Gemini 3.7 Flash at $0.75/$3.75 per million tokens (fast / budget), Gemini 3.8 Flash at $0.75/$3.75 per million tokens (fast / budget), Gemini Omni 1.1 Flash at $1.50/$9.00 per million tokens (fast / budget), Gemini Omni Flash at $1.50/$9.00 per million tokens (fast / budget), Gemini Robotics ER 2 at $1.00/$5.00 per million tokens (fast / budget). The right choice depends on whether your invoice parsing 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 1.0M tokens per API call. This sets the maximum combined length of your input prompt and generated response. For invoice parsing, typical calls use 2,000 input and 600 output tokens. That is well within this limit, leaving room for longer prompts or multi-turn conversations.

Track what you spend on AI

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.