Embed v3 vs Gemini 2.0 Flash-Lite: API Cost Comparison
Compare the API pricing, context windows, features, and real-world cost projections for Embed v3 (Cohere) and Gemini 2.0 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 24, 2026
Interactive Cost Calculator
Fills in typical token counts for a workload type
Tokens in each prompt sent to the model
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Total API calls per month
Showing costs for 2 models. Cheapest: Embed v3 at $1.50/month.
| Alert | |||||||
|---|---|---|---|---|---|---|---|
BestEmbed v3 | Cohere | $1.50 | $0.000150 | $1.00 | $0.50 | 33.3% | Alerts coming soon |
Gemini 2.0 Flash-Lite | $2.25 | $0.000225 | $0.75 | $1.50 | — | Alerts coming soon |
Monthly Cost Comparison
Price Comparison at a Glance
All prices are in USD per 1 million tokens ($/M tokens). Lower is cheaper.
| Pricing Type | Embed v3 | Gemini 2.0 Flash-Lite | Cheaper |
|---|---|---|---|
| Input (standard) | $0.10/M | $0.08/M | Gemini 2.0 Flash-Lite |
| Output | $0.10/M | $0.30/M | Embed v3 |
| Batch input | N/A | $0.04/M | — |
| Batch output | N/A | $0.15/M | — |
Prices last verified: 2026-03-06 – 2026-03-24
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.
| Volume | Embed v3Monthly | Gemini 2.0 Flash-LiteMonthly | Embed v3Per request | Gemini 2.0 Flash-LitePer request |
|---|---|---|---|---|
| 1K requests/mo | $0.15 | $0.22 | $0.000150 | $0.000225 |
| 10K requests/mo | $1.50 | $2.25 | $0.000150 | $0.000225 |
| 100K requests/mo | $15.00 | $22.50 | $0.000150 | $0.000225 |
| 1M requests/mo | $150.00 | $225.00 | $0.000150 | $0.000225 |
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 tokensWhen 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 2.0 Flash-Lite
by Google
- Text classification
- Data extraction
Input / 1M tokens
$0.08/M
Output / 1M tokens
$0.30/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.
| Capability | Embed v3 | Gemini 2.0 Flash-Lite |
|---|---|---|
| Context window | 512 tokens | 1,048,576 tokens |
| Max output tokens | 1,024 tokens | 8,192 tokens |
| Performance tier | Budget | Budget |
| Vision / image input | No | Yes |
| Function calling | No | Yes |
| JSON mode | No | Yes |
| Prompt caching | No | No |
| Batch API (50% discount) | No | Yes |
| Extended reasoning | No | No |
| Fine-tuning | No | No |
| Rate limit (req/min) | Not published | 4,000 |
Embed v3 notes
Embedding model only. Output tokens represent embedding dimensions, not text. Multilingual variant also available.
Gemini 2.0 Flash-Lite notes
Lowest cost Google model. No prompt caching support.
Frequently Asked Questions
Is Embed v3 cheaper than Gemini 2.0 Flash-Lite?
At standard usage (1,000 input tokens, 500 output tokens, 100,000 requests/month), Embed v3 costs $15.00/month versus $22.50/month for Gemini 2.0 Flash-Lite — a 33% 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 2.0 Flash-Lite?
Gemini 2.0 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 2.0 Flash-Lite support the Batch API?
Gemini 2.0 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 2.0 Flash-Lite with batch pricing could significantly cut costs versus Embed v3's standard rate.
Which model offers better prompt caching?
Neither Embed v3 nor Gemini 2.0 Flash-Lite currently supports prompt caching. For prompt-caching capable alternatives, consider Claude models from Anthropic or GPT-4o from OpenAI.
What are the best use cases for Embed v3 vs Gemini 2.0 Flash-Lite?
Embed v3 is best suited for RAG / Semantic search, while Gemini 2.0 Flash-Lite is optimized for Text classification, Data extraction. 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 2.0 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 2.0 Flash-Lite costs $0.000225 per request. At 100,000 requests/month, that translates to $15.00 and $22.50 respectively. Use the interactive calculator to adjust these parameters for your actual workload.
Embed v3 vs Gemini 2.0 Flash-Lite: Summary
When comparing Embed v3 and Gemini 2.0 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 $22.50/month for Gemini 2.0 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 2.0 Flash-Lite charges $0.08/M input and $0.30/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.
Context window capacity differs between the two: Gemini 2.0 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.
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Relevant Use Cases
See cost recommendations for workloads where Embed v3 or Gemini 2.0 Flash-Lite is recommended.