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Embed v3 vs Gemini 3.1 Flash-Lite: API Cost Comparison

Compare the API pricing, context windows, features, and real-world cost projections for Embed v3 (Cohere) and Gemini 3.1 Flash-Lite (Google). Use the interactive calculator below to compute your exact monthly cost based on your token usage and request volume.

Prices verified Mar 8, 2026

Interactive Cost Calculator

CohereEmbed v3GoogleGemini 3.1 Flash-Lite

Fills in typical token counts for a workload type

Tokens in each prompt sent to the model

Tokens generated in each response

Total API calls per month

Showing costs for 2 models. Cheapest: Embed v3 at $1.50/month.

Cheapest: Embed v3 at $1.50/mo — save 85.0% vs Gemini 3.1 Flash-Lite
Alert
BestEmbed v3
Cohere$1.50$0.000150$1.00$0.5085.0%Alerts coming soon
Gemini 3.1 Flash-Lite
Google$10.00$0.001000$2.50$7.50Alerts coming soon

Monthly Cost Comparison

Price Comparison at a Glance

All prices are in USD per 1 million tokens ($/M tokens). Lower is cheaper.

Pricing TypeEmbed v3Gemini 3.1 Flash-LiteCheaper
Input (standard)$0.10/M$0.25/MEmbed v3
Output$0.10/M$1.50/MEmbed v3
Cached inputN/A$0.03/M
Batch inputN/A$0.13/M
Batch outputN/A$0.75/M

Prices last verified: 2026-03-06 – 2026-03-08

Cost Breakdown by Usage Volume

Estimated monthly costs at different request volumes, assuming 1,000 input tokens and 500 output tokens per request. Adjust in the calculator above for your specific use case.

VolumeEmbed v3MonthlyGemini 3.1 Flash-LiteMonthlyEmbed v3Per requestGemini 3.1 Flash-LitePer request
1K requests/mo$0.15$1.00$0.000150$0.001000
10K requests/mo$1.50$10.00$0.000150$0.001000
100K requests/mo$15.00$100.00$0.000150$0.001000
1M requests/mo$150.00$1,000.00$0.000150$0.001000

Green values indicate the lower-cost option at each volume tier. Cost per request is calculated at 1,000 input + 500 output tokens using standard (non-batch, non-cached) pricing.

Price History

Input price per 1M tokens

When to Choose Embed v3

by Cohere

  • RAG / Semantic search

Input / 1M tokens

$0.10/M

Output / 1M tokens

$0.10/M

Context window

512

Tier

budget

When to Choose Gemini 3.1 Flash-Lite

by Google

  • Text classification
  • Data extraction
  • Customer support

Input / 1M tokens

$0.25/M

Output / 1M tokens

$1.50/M

Context window

1,048,576

Tier

budget

Key Differences Beyond Price

Cost is only one factor in choosing an AI model. Context window size, rate limits, supported features, and latency all affect whether a model fits your use case.

CapabilityEmbed v3Gemini 3.1 Flash-Lite
Context window512 tokens1,048,576 tokens
Max output tokens1,024 tokens65,536 tokens
Performance tierBudgetBudget
Vision / image inputNoYes
Function callingNoYes
JSON modeNoYes
Prompt cachingNoYes
Batch API (50% discount)NoYes
Extended reasoningNoNo
Fine-tuningNoNo
Rate limit (req/min)Not published4,000

Embed v3 notes

Embedding model only. Output tokens represent embedding dimensions, not text. Multilingual variant also available.

Gemini 3.1 Flash-Lite notes

Preview model. Budget-friendly Gemini 3.1 option with 1M context window.

Frequently Asked Questions

Is Embed v3 cheaper than Gemini 3.1 Flash-Lite?

At standard usage (1,000 input tokens, 500 output tokens, 100,000 requests/month), Embed v3 costs $15.00/month versus $100.00/month for Gemini 3.1 Flash-Lite — a 85% saving. Your actual savings will vary based on your token profile; output-heavy workloads amplify differences in output pricing.

Which model has a larger context window, Embed v3 or Gemini 3.1 Flash-Lite?

Gemini 3.1 Flash-Lite has a larger context window at 1,048,576 tokens, compared to 512 tokens for Embed v3. A larger context window is important for processing long documents, multi-turn conversations, or large codebases without truncation.

Do Embed v3 and Gemini 3.1 Flash-Lite support the Batch API?

Gemini 3.1 Flash-Lite supports the Batch API (50% discount for async processing), while Embed v3 does not. If your workload tolerates up to 24-hour latency, routing to Gemini 3.1 Flash-Lite with batch pricing could significantly cut costs versus Embed v3's standard rate.

Which model offers better prompt caching?

Gemini 3.1 Flash-Lite supports prompt caching at $0.03/M for cached input, while Embed v3 does not offer prompt caching. For RAG applications or chatbots with large, repeated context, Gemini 3.1 Flash-Lite's caching capability can substantially reduce effective costs.

What are the best use cases for Embed v3 vs Gemini 3.1 Flash-Lite?

Embed v3 is best suited for RAG / Semantic search, while Gemini 3.1 Flash-Lite is optimized for Text classification, Data extraction, Customer support. Choose based on which use case matches your primary workload — and validate with the cost calculator above to confirm the total monthly spend fits your budget.

What is the cost per request for Embed v3 vs Gemini 3.1 Flash-Lite?

At 1,000 input tokens and 500 output tokens per request — a typical conversational workload — Embed v3 costs $0.000150 per request and Gemini 3.1 Flash-Lite costs $0.001000 per request. At 100,000 requests/month, that translates to $15.00 and $100.00 respectively. Use the interactive calculator to adjust these parameters for your actual workload.

Embed v3 vs Gemini 3.1 Flash-Lite: Summary

When comparing Embed v3 and Gemini 3.1 Flash-Lite for API cost, the right choice depends on your workload's token profile, required features, and tolerance for latency. Embed v3 offers lower total cost at standard usage volumes (1,000 input + 500 output tokens per request at 100,000 requests/month) at $15.00/month, compared to $100.00/month for Gemini 3.1 Flash-Lite.

Both models are priced in USD per million tokens, the standard unit across all major AI API providers. Embed v3 charges $0.10/M for input tokens and $0.10/M for output tokens. Gemini 3.1 Flash-Lite charges $0.25/M input and $1.50/M output. If your workload is output-heavy (more tokens generated than consumed as input), the model with the lower output price compounds cost savings significantly at scale.

Prompt caching is supported by Gemini 3.1 Flash-Lite but not Embed v3. For workloads with large, repeated system prompts or document context — such as RAG pipelines or multi-turn conversations with a fixed knowledge base — prompt caching can reduce effective input costs by 60–90%, which may change the cost ranking between these two models at your specific usage pattern.

Context window capacity differs between the two: Gemini 3.1 Flash-Lite supports up to 1,048,576 tokens in a single request, versus 512 tokens for Embed v3. A larger context window is essential for document summarization, large codebase analysis, and multi-document retrieval-augmented generation (RAG) applications.

Use the interactive calculator at the top of this page to enter your actual token usage and monthly request volume for a precise cost comparison tailored to your workload. Adjust for batch API discounts and prompt caching to find the most cost-effective option for your specific deployment.

Explore other model comparisons from the same providers or performance tiers.

Related Provider Pages

View complete pricing tables and model lineups for the providers behind these models.

Relevant Use Cases

See cost recommendations for workloads where Embed v3 or Gemini 3.1 Flash-Lite is recommended.