Gemma 4 31B vs Nemotron Nano 9B: API Cost Comparison
Compare the API pricing, context windows, features, and real-world cost projections for Gemma 4 31B (Google) and Nemotron Nano 9B (Nvidia NIM). 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
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Showing costs for 2 models. Cheapest: Nemotron Nano 9B at $1.20/month.
| Alert | |||||||
|---|---|---|---|---|---|---|---|
BestNemotron Nano 9B | Nvidia NIM | $1.20 | $0.000120 | $0.40 | $0.80 | 64.7% | 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 | Nemotron Nano 9B | Cheaper |
|---|---|---|---|
| Input (standard) | $0.14/M | $0.04/M | Nemotron Nano 9B |
| Output | $0.40/M | $0.16/M | Nemotron Nano 9B |
Prices last verified: 2026-03-11 – 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 | Nemotron Nano 9BMonthly | Gemma 4 31BPer request | Nemotron Nano 9BPer request |
|---|---|---|---|---|
| 1K requests/mo | $0.34 | $0.12 | $0.000340 | $0.000120 |
| 10K requests/mo | $3.40 | $1.20 | $0.000340 | $0.000120 |
| 100K requests/mo | $34.00 | $12.00 | $0.000340 | $0.000120 |
| 1M requests/mo | $340.00 | $120.00 | $0.000340 | $0.000120 |
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 Nemotron Nano 9B
by Nvidia NIM
- Customer support
- Text classification
- Summarization
Input / 1M tokens
$0.04/M
Output / 1M tokens
$0.16/M
Context window
128,000
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 | Nemotron Nano 9B |
|---|---|---|
| Context window | 262,144 tokens | 128,000 tokens |
| Max output tokens | 131,072 tokens | 8,192 tokens |
| Performance tier | Budget | Budget |
| Vision / image input | Yes | No |
| Function calling | Yes | Yes |
| JSON mode | Yes | Yes |
| Prompt caching | No | No |
| Batch API (50% discount) | No | No |
| Extended reasoning | Yes | No |
| Fine-tuning | No | No |
Gemma 4 31B notes
Open-weight model (Apache 2.0). Pricing reflects Google AI Studio hosted API.
Nemotron Nano 9B notes
Nemotron Nano 9B on NVIDIA NIM. Ultra-low-cost compact model for high-volume tasks requiring fast, efficient inference at minimal per-token cost.
Frequently Asked Questions
Is Gemma 4 31B cheaper than Nemotron Nano 9B?
At standard usage (1,000 input tokens, 500 output tokens, 100,000 requests/month), Nemotron Nano 9B costs $12.00/month versus $34.00/month for Gemma 4 31B — a 65% 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 Nemotron Nano 9B?
Gemma 4 31B has a larger context window at 262,144 tokens, compared to 128,000 tokens for Nemotron Nano 9B. A larger context window is important for processing long documents, multi-turn conversations, or large codebases without truncation.
Do Gemma 4 31B and Nemotron Nano 9B support the Batch API?
Neither Gemma 4 31B nor Nemotron Nano 9B 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?
Neither Gemma 4 31B nor Nemotron Nano 9B 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 Gemma 4 31B vs Nemotron Nano 9B?
Gemma 4 31B is best suited for General chatbot, Code generation, Document Analysis, while Nemotron Nano 9B is optimized for Customer support, Text classification, Summarization. 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 Nemotron Nano 9B?
At 1,000 input tokens and 500 output tokens per request — a typical conversational workload — Gemma 4 31B costs $0.000340 per request and Nemotron Nano 9B costs $0.000120 per request. At 100,000 requests/month, that translates to $34.00 and $12.00 respectively. Use the interactive calculator to adjust these parameters for your actual workload.
Gemma 4 31B vs Nemotron Nano 9B: Summary
When comparing Gemma 4 31B and Nemotron Nano 9B for API cost, the right choice depends on your workload's token profile, required features, and tolerance for latency. Nemotron Nano 9B offers lower total cost at standard usage volumes (1,000 input + 500 output tokens per request at 100,000 requests/month) at $12.00/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. Nemotron Nano 9B charges $0.04/M input and $0.16/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: Gemma 4 31B supports up to 262,144 tokens in a single request, versus 128,000 tokens for Nemotron Nano 9B. 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 4 31B or Nemotron Nano 9B is recommended.