Gemma 4 31B vs GPT-5 nano: API Cost Comparison
Compare the API pricing, context windows, features, and real-world cost projections for Gemma 4 31B (Google) 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 Apr 3, 2026
Interactive Cost Calculator
Fills in typical token counts for a workload type
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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 | 26.5% | Alerts coming soon |
Gemma 4 31B | $3.40 | $0.000340 | $1.40 | $2.00 | — | Alerts coming soon |
Monthly Cost Comparison
Price Comparison at a Glance
All prices are in USD per 1 million tokens ($/M tokens). Lower is cheaper.
| Pricing Type | Gemma 4 31B | GPT-5 nano | Cheaper |
|---|---|---|---|
| Input (standard) | $0.14/M | $0.05/M | GPT-5 nano |
| Output | $0.40/M | $0.40/M | — |
| Cached input | N/A | $0.01/M | — |
Prices last verified: 2026-03-06 – 2026-04-03
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 4 31BMonthly | GPT-5 nanoMonthly | Gemma 4 31BPer request | GPT-5 nanoPer request |
|---|---|---|---|---|
| 1K requests/mo | $0.34 | $0.25 | $0.000340 | $0.000250 |
| 10K requests/mo | $3.40 | $2.50 | $0.000340 | $0.000250 |
| 100K requests/mo | $34.00 | $25.00 | $0.000340 | $0.000250 |
| 1M requests/mo | $340.00 | $250.00 | $0.000340 | $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 4 31B
by Google
- General chatbot
- Code generation
- Document Analysis
Input / 1M tokens
$0.14/M
Output / 1M tokens
$0.40/M
Context window
262,144
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 4 31B | GPT-5 nano |
|---|---|---|
| Context window | 262,144 tokens | 400,000 tokens |
| Max output tokens | 131,072 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 | Yes | No |
| Fine-tuning | No | No |
| Rate limit (req/min) | Not published | 10,000 |
Gemma 4 31B notes
Open-weight model (Apache 2.0). Pricing reflects Google AI Studio hosted API.
GPT-5 nano notes
Cheapest GPT-5 model. 1M context at budget pricing.
Frequently Asked Questions
Is Gemma 4 31B 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 $34.00/month for Gemma 4 31B — a 26% 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 4 31B or GPT-5 nano?
GPT-5 nano has a larger context window at 400,000 tokens, compared to 262,144 tokens for Gemma 4 31B. A larger context window is important for processing long documents, multi-turn conversations, or large codebases without truncation.
Do Gemma 4 31B and GPT-5 nano support the Batch API?
Neither Gemma 4 31B 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 4 31B 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 4 31B vs GPT-5 nano?
Gemma 4 31B is best suited for General chatbot, Code generation, Document Analysis, 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 4 31B vs GPT-5 nano?
At 1,000 input tokens and 500 output tokens per request — a typical conversational workload — Gemma 4 31B costs $0.000340 per request and GPT-5 nano costs $0.000250 per request. At 100,000 requests/month, that translates to $34.00 and $25.00 respectively. Use the interactive calculator to adjust these parameters for your actual workload.
Gemma 4 31B vs GPT-5 nano: Summary
When comparing Gemma 4 31B 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 $34.00/month for Gemma 4 31B.
Both models are priced in USD per million tokens, the standard unit across all major AI API providers. Gemma 4 31B charges $0.14/M for input tokens and $0.40/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 4 31B. 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 262,144 tokens for Gemma 4 31B. 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
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