Usage Level	Daily Tokens	Daily	Monthly	Yearly
Light~50 requests/day	100K in / 20K out	$0.02	$0.72	$9
Medium~200 requests/day	500K in / 100K out	$0.12	$3.60	$44
Heavy~1K requests/day	2,000K in / 500K out	$0.50	$15.00	$183
Enterprise~5K requests/day	10,000K in / 2,000K out	$2.40	$72.00	$876

Cost Calculator

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Alternatives to Gemini Embedding 2

💰 Cheaper Options

Llama 4 ScoutMeta (via Together AI)

5% cheaper

$0.08/M in · $0.3/M out

Gemini 2.0 Flash-LiteGoogle

6% cheaper

$0.075/M in · $0.3/M out

Llama 3.1 8BMeta (via Together AI)

10% cheaper

$0.18/M in · $0.18/M out

Ministral 3 8BMistral AI

25% cheaper

$0.15/M in · $0.15/M out

🚀 More Powerful

DeepSeek V4 FlashDeepSeek

5% more

$0.14/M in · $0.28/M out

GPT-5 nanoOpenAI

13% more

$0.05/M in · $0.4/M out

GPT-4.1 nanoOpenAI

25% more

$0.1/M in · $0.4/M out

Gemini 2.0 FlashGoogle

25% more

$0.1/M in · $0.4/M out

Frequently Asked Questions

How much does Gemini Embedding 2 API cost per million tokens?▼

Gemini Embedding 2 costs $0.2 per million input tokens and $0.2 per million output tokens as of 2026. These are the standard API rates from Google.

What is the Gemini Embedding 2 context window?▼

Gemini Embedding 2 supports a 8.192K context window (8,192 tokens), which means you can process up to 8.192K tokens in a single API call.

How much does Gemini Embedding 2 cost per month?▼

At medium usage (~200 requests/day with 500K input and 100K output tokens/day), Gemini Embedding 2 costs approximately $3.60/month. Light usage runs about $0.72/month, and heavy usage (~1K requests/day) around $15.00/month.

Is there a cheaper alternative to Gemini Embedding 2?▼

Yes — Llama 4 Scout by Meta (via Together AI) is a cheaper option at $0.08/M input tokens vs $0.2/M for Gemini Embedding 2. Other budget alternatives include models in the efficient tier.

Is Gemini Embedding 2 good for ai chatbot?▼

Gemini Embedding 2 is a embedding model with support for text, vision, audio. For ai chatbot, it offers 8.192K context and costs $0.2/M input tokens — a budget-friendly choice for this use case.