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Google’s Gemini API pricing page lists Nano Banana 2.1 image-output equivalents of $0.0336 for 1K, $0.0504 for 2K, and $0.113 for 4K images when processed through Standard pricing. Batch equivalents are $0.0168, $0.0252, and $0.0567. Those figures cover the image-output component only: your estimate may also need input-token, text/thinking-output, and search-grounding charges.
What Nano Banana 2.1 is—and what the listed prices mean
Google identifies the model as Gemini Nano Banana 2.1, with the API model ID gemini-nano-banana-2.1. Google’s model documentation describes it as a high-efficiency image-generation and conversational-editing model and lists an October 2026 update. The model is positioned as an update to Nano Banana 2 (Gemini 3.1 Flash Image), with improvements in visual quality, prompt adherence, multi-turn character consistency, and text rendering.
The amounts in this article are Gemini API usage prices, not the price of a consumer Gemini subscription. They are the rates listed by Google’s AI for Developers pricing documentation checked in October 2026. Cloud prices and model availability can change, so use the live pricing page and the billing configuration for your access route before approving a budget.
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Nano Banana 2.1 image-output prices
Google’s table expresses image generation as image tokens and also provides approximate per-image equivalents. Standard processing is the normal real-time option; Batch is intended for workloads that can be submitted for asynchronous processing and uses lower listed rates.
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| Output | Pixel dimensions | Image tokens per output | Standard image-output equivalent | Batch image-output equivalent |
|---|---|---|---|---|
| 1K | 1,024 × 1,024 | 1,120 | $0.0336 per image | $0.0168 per image |
| 2K | 2,048 × 2,048 | 1,680 | $0.0504 per image | $0.0252 per image |
| 4K | 4,096 × 4,096 | 3,780 | $0.113 per image | $0.0567 per image |
The underlying listed output rates are $30 per 1,000,000 image-output tokens for Standard and $15 per 1,000,000 image-output tokens for Batch. The per-image figures are therefore output-cost equivalents derived from the token allotment for each resolution. They are not a guaranteed total invoice for a request.
Other charges that can appear on the same request
A generated image can be accompanied by other billable work. Include these categories when they apply to your implementation.
| Charge category | Standard | Batch |
|---|---|---|
| Input text, image, and video tokens | $1.50 per 1,000,000 tokens | $0.75 per 1,000,000 tokens |
| Text and thinking output tokens | $7.50 per 1,000,000 tokens | $3.75 per 1,000,000 tokens |
| Image output | $30 per 1,000,000 image tokens | $15 per 1,000,000 image tokens |
For a simple prompt that returns an image and does not use substantial textual reasoning, image output may dominate. An editing workflow that sends several reference images, or a response that produces a long text explanation, can make input and text/thinking output material as well. Measure or conservatively estimate every token category rather than multiplying image count alone.
The calculation formula
Use a separate line for each resolution and billing mode:
Estimated API cost = Σ(image count at each resolution × applicable image-output rate) + input-token cost + text/thinking-output cost + grounding charges
For token charges, convert the measured token total to millions before multiplying by the applicable per-million rate. Keep Standard and Batch calculations separate; do not apply a Batch image rate while using Standard token rates.
Example: 100 Standard 1K images
One hundred 1K outputs have an image-output component of 100 × $0.0336 = $3.36. This is an arithmetic estimate from Google’s listed unit price. It excludes input tokens, text/thinking output, search grounding, and any other applicable charge.
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If the same 100 outputs qualify for Batch processing, the image-output component is 100 × $0.0168 = $1.68. The lower amount applies only to the image-output portion; include Batch input and text/thinking rates if those categories are used.
Example: a mixed-resolution run
Suppose a job contains 60 Standard 1K images, 30 Standard 2K images, and 10 Standard 4K images. Calculate each group independently:
- 60 × $0.0336 = $2.016 for 1K output.
- 30 × $0.0504 = $1.512 for 2K output.
- 10 × $0.113 = $1.13 for 4K output.
The image-output subtotal is $4.658, before token and grounding charges. Keeping the resolution mix visible prevents a low-resolution average from hiding the cost of a smaller number of 4K outputs.
How to estimate a real workload step by step
- Identify the model and route. Confirm that the request uses
gemini-nano-banana-2.1and note whether it is sent through the Gemini API or another Google-managed access route. Capability and billing details can differ by route. - Count outputs by resolution. Record expected 1K, 2K, and 4K images separately. If a retry can create another billable generation, include the expected retry rate in the count.
- Select Standard or Batch. Use Standard for interactive latency-sensitive work. Use Batch only when the workflow can tolerate asynchronous processing and the endpoint supports the required operation.
- Multiply each image group by its listed rate. Keep the result as an image-output subtotal, not a claimed final bill.
- Estimate input tokens. Include prompt text plus any supplied image or video inputs. For editing, reference assets can be a significant part of the input total.
- Estimate text and thinking output. Add generated textual responses and any thinking tokens when the selected configuration bills them.
- Count grounding queries. If Google Web or Image Search grounding is enabled, count individual queries, not merely API requests.
- Build three budgets. Prepare low, expected, and high cases by varying image volume, resolution mix, retries, token totals, and grounded-query count. Label each assumption so actual usage can be compared with the estimate.
- Validate after a pilot. Compare logged image counts and token usage with the billing report, then replace assumptions with measured values before scaling.
Search grounding can change the estimate
Google lists 5,000 free Google Web and Image Search grounding requests per month, shared across Gemini 3 and newer models. After that allowance, the listed price is $14 per 1,000 requests. Google also states that billing is based on each individual search query performed. One submitted API request can produce one or more queries, so counting HTTP requests alone can understate the charge.
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For a grounded workload, add a separate line to the formula:
Grounding charge = max(0, billable queries − 5,000) ÷ 1,000 × $14
Use the query count reported by your implementation or billing data. Do not assume that every image request consumes exactly one query, and do not apply the free allowance independently to every model or project when Google defines it as shared.
Choosing 1K, 2K, or 4K output
1K for drafts and high-volume generation
At $0.0336 Standard or $0.0168 Batch per listed image-output equivalent, 1K is the least expensive option. It is appropriate when the image is used as a draft, a thumbnail, a design concept, or an asset that will be resized later without requiring fine detail at the original output.
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2K costs $0.0504 Standard or $0.0252 Batch per listed image-output equivalent. Choose it when the output needs more detail or a larger working canvas than 1K provides, but a 4K master is unnecessary.
4K for detail-sensitive deliverables
4K costs $0.113 Standard or $0.0567 Batch per listed image-output equivalent. It uses 3,780 image tokens per output, compared with 1,120 at 1K, so the token-based cost rises substantially. Reserve it for outputs whose delivery size or detail requirements justify the additional spend.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.What Nano Banana 2.1 can accept and produce
The official model reference lists text, image, video, and PDF inputs, with image and text outputs. It also lists image generation, search grounding, and Batch API support. Google Cloud documentation describes image generation from video input, image editing, and multi-turn image editing.
The exact capability surface can depend on the access route, model configuration, and API version. Check the documentation for the endpoint you are implementing instead of assuming that every listed capability is exposed identically everywhere. In particular, verify the supported input type, output resolution controls, grounding configuration, and Batch behavior before writing a cost model around them.
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- Treating the image rate as the complete request price. The per-image figures are image-output equivalents; input, text/thinking output, and grounding can be additional lines.
- Using one average price for every resolution. 1K, 2K, and 4K have different token allocations and listed rates.
- Assuming Batch is simply a switch for interactive calls. Confirm that the workload and endpoint support Batch and that delayed completion is acceptable.
- Counting API calls instead of grounding queries. A request can generate multiple individual search queries.
- Ignoring retries and failed-workflow behavior. Add a realistic retry allowance when your application may resubmit generations.
- Quoting a permanent price. The figures are Google’s October 2026 listing and should be rechecked before a long-term commitment.
A practical budgeting worksheet
Before launch, record these inputs for each scenario:
- Number of Standard 1K, 2K, and 4K outputs.
- Number of Batch 1K, 2K, and 4K outputs, if Batch is used.
- Expected input text, image, and video tokens.
- Expected text and thinking output tokens.
- Grounded requests and the expected number of individual queries per request.
- Retry, regeneration, and moderation-review allowances that could cause another request.
Then calculate each category independently and retain the assumptions alongside the total. A useful monitoring dashboard should show output count by resolution, image-output tokens, input tokens, text/thinking tokens, grounding queries, and billed dollars. That breakdown makes it clear whether a cost increase came from more images, higher resolution, longer prompts, more generated text, or search activity.
Bottom line for planning
For Nano Banana 2.1, start with the resolution-specific image-output rates: $0.0336, $0.0504, and $0.113 per 1K, 2K, and 4K Standard image, or $0.0168, $0.0252, and $0.0567 through the listed Batch equivalents. Multiply your expected image counts, then add the applicable token and grounding lines. Treat the result as a workload estimate, validate it against a pilot and billing data, and recheck Google’s current pricing before committing funds.
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