Gemma 3 27B (Bedrock) vs GPT-5 nano: API Cost Comparison
Compare the API pricing, context windows, features, and real-world cost projections for Gemma 3 27B (Bedrock) (AWS Bedrock) and GPT-5 nano (OpenAI). Use the interactive calculator below to compute your exact monthly cost based on your token usage and request volume.
Prices verified Mar 11, 2026
Interactive Cost Calculator
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Showing costs for 2 models. Cheapest: GPT-5 nano at $2.50/month.
| Alert | |||||||
|---|---|---|---|---|---|---|---|
BestGPT-5 nano | OpenAI | $2.50 | $0.000250 | $0.50 | $2.00 | 40.5% | Alerts coming soon |
Gemma 3 27B (Bedrock) | AWS Bedrock | $4.20 | $0.000420 | $2.30 | $1.90 | — | Alerts coming soon |
Monthly Cost Comparison
Price Comparison at a Glance
All prices are in USD per 1 million tokens ($/M tokens). Lower is cheaper.
| Pricing Type | Gemma 3 27B (Bedrock) | GPT-5 nano | Cheaper |
|---|---|---|---|
| Input (standard) | $0.23/M | $0.05/M | GPT-5 nano |
| Output | $0.38/M | $0.40/M | Gemma 3 27B (Bedrock) |
| Cached input | N/A | $0.01/M | — |
Prices last verified: 2026-03-06 – 2026-03-11
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 | Gemma 3 27B (Bedrock)Monthly | GPT-5 nanoMonthly | Gemma 3 27B (Bedrock)Per request | GPT-5 nanoPer request |
|---|---|---|---|---|
| 1K requests/mo | $0.42 | $0.25 | $0.000420 | $0.000250 |
| 10K requests/mo | $4.20 | $2.50 | $0.000420 | $0.000250 |
| 100K requests/mo | $42.00 | $25.00 | $0.000420 | $0.000250 |
| 1M requests/mo | $420.00 | $250.00 | $0.000420 | $0.000250 |
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 Gemma 3 27B (Bedrock)
by AWS Bedrock
- Translation
- Summarization
- Content Creation
Input / 1M tokens
$0.23/M
Output / 1M tokens
$0.38/M
Context window
128,000
Tier
budget
When to Choose GPT-5 nano
by OpenAI
- Text classification
- Data extraction
Input / 1M tokens
$0.05/M
Output / 1M tokens
$0.40/M
Context window
400,000
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 | Gemma 3 27B (Bedrock) | GPT-5 nano |
|---|---|---|
| Context window | 128,000 tokens | 400,000 tokens |
| Max output tokens | 8,192 tokens | 128,000 tokens |
| Performance tier | Budget | Budget |
| Vision / image input | Yes | Yes |
| Function calling | Yes | Yes |
| JSON mode | Yes | Yes |
| Prompt caching | No | Yes |
| Batch API (50% discount) | No | No |
| Extended reasoning | No | No |
| Fine-tuning | No | No |
| Rate limit (req/min) | Not published | 10,000 |
Gemma 3 27B (Bedrock) notes
Google Gemma 3 27B via AWS Bedrock. Supports vision inputs. Good multilingual model for cost-sensitive workloads on AWS infrastructure.
GPT-5 nano notes
Cheapest GPT-5 model. 1M context at budget pricing.
Frequently Asked Questions
Is Gemma 3 27B (Bedrock) cheaper than GPT-5 nano?
At standard usage (1,000 input tokens, 500 output tokens, 100,000 requests/month), GPT-5 nano costs $25.00/month versus $42.00/month for Gemma 3 27B (Bedrock) — a 40% 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, Gemma 3 27B (Bedrock) or GPT-5 nano?
GPT-5 nano has a larger context window at 400,000 tokens, compared to 128,000 tokens for Gemma 3 27B (Bedrock). A larger context window is important for processing long documents, multi-turn conversations, or large codebases without truncation.
Do Gemma 3 27B (Bedrock) and GPT-5 nano support the Batch API?
Neither Gemma 3 27B (Bedrock) nor GPT-5 nano currently supports a batch API with discounted pricing. For batch-eligible alternatives, consider models from OpenAI, Anthropic, or Google that include batch API support.
Which model offers better prompt caching?
GPT-5 nano supports prompt caching at $0.01/M for cached input, while Gemma 3 27B (Bedrock) does not offer prompt caching. For RAG applications or chatbots with large, repeated context, GPT-5 nano's caching capability can substantially reduce effective costs.
What are the best use cases for Gemma 3 27B (Bedrock) vs GPT-5 nano?
Gemma 3 27B (Bedrock) is best suited for Translation, Summarization, Content Creation, while GPT-5 nano 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 Gemma 3 27B (Bedrock) vs GPT-5 nano?
At 1,000 input tokens and 500 output tokens per request — a typical conversational workload — Gemma 3 27B (Bedrock) costs $0.000420 per request and GPT-5 nano costs $0.000250 per request. At 100,000 requests/month, that translates to $42.00 and $25.00 respectively. Use the interactive calculator to adjust these parameters for your actual workload.
Gemma 3 27B (Bedrock) vs GPT-5 nano: Summary
When comparing Gemma 3 27B (Bedrock) and GPT-5 nano for API cost, the right choice depends on your workload's token profile, required features, and tolerance for latency. GPT-5 nano offers lower total cost at standard usage volumes (1,000 input + 500 output tokens per request at 100,000 requests/month) at $25.00/month, compared to $42.00/month for Gemma 3 27B (Bedrock).
Both models are priced in USD per million tokens, the standard unit across all major AI API providers. Gemma 3 27B (Bedrock) charges $0.23/M for input tokens and $0.38/M for output tokens. GPT-5 nano charges $0.05/M input and $0.40/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 GPT-5 nano but not Gemma 3 27B (Bedrock). 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: GPT-5 nano supports up to 400,000 tokens in a single request, versus 128,000 tokens for Gemma 3 27B (Bedrock). 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 Gemma 3 27B (Bedrock) or GPT-5 nano is recommended.