GEMINI 3.5 LITE GA1M CONTEXTMULTIMODALHIGH THROUGHPUTNO AUDIO SURCHARGE
Gemini 3.5 Flash-Lite API Pricing
Gemini 3.5 Flash-Lite shipped GA on July 21, 2026 for high-volume agentic tasks, translation and simple data processing. It lists $0.30/M input and $2.50/M output, with cache hits at $0.03/M. Note the rate card before switching: per token it is dearer than Gemini 3.1 Flash-Lite. Checked by hand against ai.google.dev.
Input - per 1M tokens
$0.30/M
Covers audio too new
Output - per 1M tokens
$2.50/M
Incl. thinking tokens new
Cached input - per 1M tokens
$0.03/M
Storage $1/M-hour -90%
Effective - agentic blend
$0.272/M
92/8 split - 82% cache
§ 01 / TERMINAL
Gemini 3.5 Flash-Lite API cost calculator.
Live calculator pre-loaded with current Gemini 3.5 Flash-Lite rates. Tweak spend, output mix, or cache assumptions and share the URL to share the calculation.
$ /mo
Workload split
Prompt cache hit rate
Tokens you can process
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Words equivalent (English)
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Effective rate
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§ 02 / SCENARIOS
Gemini 3.5 Flash-Lite cost on real workloads.
BULK
High-volume classification
$0.00313/item
ASSISTANT
Research planning turn
$0.00641/turn
CODING AGENT
Codebase-scale migration
$0.034/task
LONG DOC
Reading 100-page contracts
$0.034/doc
Estimate · gemini-tokenizer-estimate · ≈3.85 chars/token Auto-counts as you type
This is a chars-per-token approximation, not a real tokenizer. Actual tokens vary by language, code density, and tool-call overhead — counts are typically ±10–20% off for English prose, more for code or non-Latin scripts. For exact billing, use the vendor's official tokenizer.
Characters 683
Words 107
Tokens (estimated) 177 tokens
Cost as input · uncached $0.00005 USD
Cost as output · uncached $0.00044 USD
Cost as cached input $0.00001 USD
| Model | Input /M | Output /M | Effective blended | Context | Best for |
|---|---|---|---|---|---|
| Gemini 3.5 Flash-Lite Current | $0.30 cache $0.03 | $2.50 | $0.272 agentic 92/8 | 1M | High-volume agentic + translation |
| Gemini 3.1 Flash-Lite | $0.25 cache $0.025 | $1.50 | $0.18 deprecated · −34% | 1M | Cheaper per token, retiring May 2027 |
| Gemini 2.5 Flash | $0.30 cache $0.03 | $2.50 | $0.272 deprecated · same | 1M | Prior-gen twin of this rate card |
| Gemini 3.6 Flash | $0.75 cache $0.075 | $3.75 | $0.481 +77% · promo | 1M | Step up for harder agentic work |
| GPT-6 Luna | $0.10 cache $0.01 | $0.50 | $0.0682 −4.0× | 1.05M | OpenAI's budget tier |
| DeepSeek V4.1 Flash | $0.30 cache $0.006 | $1.20 | $0.15 −45% | 1M | Budget reasoning and coding |
Gemini 3.5 Flash-Lite has published scores on 8 benchmarks we track; its best placing is #3 of 6 on SWE-Bench Pro. 2 of these scores come from an independent leaderboard; the rest are the lab's own reports.
| Benchmark | Score | Rank | Leader | Source |
|---|---|---|---|---|
| SWE-Bench Pro Coding · Public set (731 tasks) | 54.2% public set | #3 of 6 | Gemini 3.6 Flash · 58.7% | Vendor-reported Google DeepMind |
| ARC-AGI-2 Reasoning | 10.3% ARC Prize verified, best result | #62 of 105 | GPT-6 Astra · 95% | Official leaderboard ARC Prize Foundation |
| ARC-AGI-1 Reasoning | 53.5% ARC Prize verified, best result | #68 of 99 | 6 tied · 98.5% | Official leaderboard ARC Prize Foundation |
| MLE-bench AI research | 39.2% as reported | #4 of 5 | Gemini 3.6 Flash · 63.9% | Vendor-reported Google DeepMind |
| MRCR v2 Long context · 8-needle, up to 128K | 72.2% 128K average | #6 of 7 | Gemini 3.7 Flash · 97% | Vendor-reported Google DeepMind |
| OSWorld-Verified Agents and computer use | 74% as reported | #7 of 8 | Kimi K3 · 84.8% | Vendor-reported Google DeepMind |
| CharXiv Reasoning Vision and documents · No tools | 74.5% no tools | #8 of 9 | Kimi K3.1 Pro · 89% | Vendor-reported Google DeepMind |
| Terminal-Bench 2 Agents and computer use · Terminal-Bench 2.1 | 54% Terminus-2 harness | #16 of 17 | DeepSeek V4.1 Flash · 90.6% | Vendor-reported Google DeepMind |
Gemini 3.5 Flash-Lite API pricing FAQ.
Practical pricing questions, separated from calculator assumptions and regional taxes.
Q · 01 What is Gemini 3.5 Flash-Lite priced at? +
Google's paid-tier pricing page lists
$0.30/M input, $2.50/M output and $0.03/M cached input, plus $1.00 per 1M tokens per hour of explicit cache storage. The single input rate covers text, image, video and audio.Q · 02 Google calls it the most cost-efficient GA model. Is it the cheapest Gemini? +
Not per token. Gemini 3.1 Flash-Lite is cheaper on both sides —
$0.25/M input and $1.50/M output against $0.30 and $2.50 here — and Gemini 2.5 Flash carries an identical rate card. Any saving has to come from this model finishing a task in fewer tokens, which is a claim to test on your own workload, not a lower rate.Q · 03 When is it cheaper than Gemini 3.1 Flash-Lite? +
On audio. 3.1 Flash-Lite charges
$0.50/M for audio input against $0.25/M for text, while this model bills every modality at $0.30/M. Audio-heavy pipelines can therefore land cheaper here; text-only bulk work will not.Q · 04 Does output pricing include thinking tokens? +
Yes. Google's price table labels the output row "including thinking tokens", so reasoning is billed at the same
$2.50/M. Thinking is supported on this model and there is no separate reasoning rate.Q · 05 How is the effective price calculated? +
AI//COST uses the same 92/8 agentic blend everywhere: 92% of tokens are input, 82% of which are served from cache. That gives a blended input of
$0.0786/M and an effective cost of $0.27/M. Every shelf row above uses the same formula.Q · 06 What does Batch or Flex inference cost? +
Batch and Flex are half the standard rate for input and output:
$0.15/M input and $1.25/M output, with a discounted cache rate as well. Priority costs 1.8x the standard input and output rates. Read from Google's pricing page on October 13, 2026.Q · 07 What context window does it support? +
1,048,576 input tokens and 65,536 output tokens. Inputs cover text, image, video, audio and PDF; output is text only. Computer use, Live API, audio generation and image generation are not supported — for computer use, see Gemini 3.6 Flash.
Q · 08 How accurate is the tokenizer estimate? +
The browser widget uses a
gemini-tokenizer-estimate chars-per-token ratio for English text — Google publishes no downloadable tokenizer, so this is an estimate, not exact counting. Actual billing comes from the API's usage metadata and differs for code, non-Latin scripts and multimodal input.