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SHUT DOWN1M CONTEXTARCHIVE PRICEREPLACE WITH GEMINI-3-1-PRO-PREVIEW

Gemini 3 Pro Preview API Pricing

Google's retired first Gemini 3 Pro preview, kept here for archive pricing and migration checks: $2/M input, $12/M output, and $0.2/M cached input. Kept as an archive page.

Input - per 1M tokens
$2.00/M
Tier 1 baseline archive
Output - per 1M tokens
$12.00/M
Tier 2 $18/M archive
Cached input - per 1M
$0.20/M
Context caching listed discount
Effective - agentic blend
$1.44/M
92/8 split - 82% cache
§ 01 / TERMINAL

Run the numbers.

Calculator pre-loaded with Gemini 3 Pro Preview archive rates. Archive price mirrors the Gemini 3 Pro Preview list rate preserved in the project snapshot: $2/M input, $0.20/M cached input, and $12/M output for prompts up to 200K tokens; tier 2 above 200K was $4/$0.40/$18.

$ /mo
Workload split
Prompt cache hit rate
Tokens you can process
Words equivalent (English)
Effective rate
§ 02 / SCENARIOS

Real-world presets.

§ 03 / TAPE

Price history.

Gemini 3 Pro Preview is an archive page: endpoint shut down on 2026-03-09.

Input · $2/M
Output · $12/M
Cached · $0.20/M
NOV 18 Released gemini-3-pro-previewFEB 26 Shutdown status confirmed by Google release notesMAR 09 Endpoint shut down; replacement is gemini-3-1-pro-previewMAY 18 Archive pricing retained from verified snapshot
§ 04 / TOKENIZER

Paste text. See tokens. See cost.

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
Words
Tokens (estimated)
Cost as input · uncached
Cost as output · uncached
Cost as cached input
§ 05 / SHELF

Up against the shelf.

All models →
Model Input /M Output /M Effective blended Context Best for
Gemini 3 Pro Preview Current $2.00 cache $0.20 $12.00 $1.44 archive 92/8 1M Archive Gemini 3 Pro Preview
Gemini 3.1 Pro Preview $2.00 cache $0.20 $12.00 $1.44 current replacement 1M Current Gemini Pro preview
Gemini 3 Flash Preview $0.50 cache $0.05 $3.00 $0.36 newer flash preview 1M Current Gemini 3 Flash
Gemini 3.1 Flash-Lite $0.25 cache $0.03 $1.50 $0.18 new light tier 1M Current high-volume Gemini
Gemini 2.5 Pro $1.25 cache $0.13 $10.00 $1.10 stable pro 2M Stable Pro replacement
Gemini 2.5 Flash $0.30 cache $0.03 $2.50 $0.27 stable flash 1M Stable Flash replacement
Gemini 2.5 Flash-Lite $0.10 cache $0.01 $0.40 $0.06 stable lite 1M Stable Lite replacement
GPT-5.4 mini $0.75 cache $0.07 $4.50 $0.54 OpenAI mini 400K OpenAI mini alternative

Frequently asked.

Gemini 3 Pro Preview pricing questions, with archive/deprecation status separated from token math.

Q · 01 What is Gemini 3 Pro Preview's API price? +
This is an archive price, not a current endpoint recommendation. The page uses $2/M input and $12/M output. The archived higher prompt tier is $4/M input and $18/M output, with $0.4/M cached input.
Q · 02 Is Gemini 3 Pro Preview still available? +
No. Google says gemini-3-pro-preview was shut down on 2026-03-09. Use gemini-3-1-pro-preview for current traffic.
Q · 03 Does prompt caching apply? +
Yes. Google lists context caching for this model at $0.2/M for text, image, and video input. The calculator uses that live cache rate for the agentic blended estimate.
Q · 04 How should I use this page? +
Use it for archive pricing, old invoice reconciliation, and generation-to-generation price comparisons. Do not route new production traffic to this model, because the endpoint has already been shut down.
Q · 05 What about Batch and Flex pricing? +
The archived row follows the same headline pricing family as Gemini 3.1 Pro Preview. Use the current replacement page for live Batch, Flex, and Priority details.
Q · 06 How accurate is the tokenizer estimate? +
The widget uses 4.0 characters per token as a Gemini planning estimate. Exact billing can differ by language, media inputs, tool calls, and how Google tokenizes multimodal content.