Inception Mercury 2 (OpenRouter) vs Nemotron Nano 9B: API Cost Comparison
Compare the API pricing, context windows, features, and real-world cost projections for Inception Mercury 2 (OpenRouter) (OpenRouter) 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 Mar 11, 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 | 80.8% | Alerts coming soon |
Inception Mercury 2 (OpenRouter) | OpenRouter | $6.25 | $0.000625 | $2.50 | $3.75 | — | Alerts coming soon |
Monthly Cost Comparison
Price Comparison at a Glance
All prices are in USD per 1 million tokens ($/M tokens). Lower is cheaper.
| Pricing Type | Inception Mercury 2 (OpenRouter) | Nemotron Nano 9B | Cheaper |
|---|---|---|---|
| Input (standard) | $0.25/M | $0.04/M | Nemotron Nano 9B |
| Output | $0.75/M | $0.16/M | Nemotron Nano 9B |
Prices last verified: 2026-03-10 – 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 | Inception Mercury 2 (OpenRouter)Monthly | Nemotron Nano 9BMonthly | Inception Mercury 2 (OpenRouter)Per request | Nemotron Nano 9BPer request |
|---|---|---|---|---|
| 1K requests/mo | $0.62 | $0.12 | $0.000625 | $0.000120 |
| 10K requests/mo | $6.25 | $1.20 | $0.000625 | $0.000120 |
| 100K requests/mo | $62.50 | $12.00 | $0.000625 | $0.000120 |
| 1M requests/mo | $625.00 | $120.00 | $0.000625 | $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 Inception Mercury 2 (OpenRouter)
by OpenRouter
- Document summarization
- General chatbot
Input / 1M tokens
$0.25/M
Output / 1M tokens
$0.75/M
Context window
128,000
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 | Inception Mercury 2 (OpenRouter) | Nemotron Nano 9B |
|---|---|---|
| Context window | 128,000 tokens | 128,000 tokens |
| Max output tokens | 50,000 tokens | 8,192 tokens |
| Performance tier | Budget | Budget |
| Vision / image input | No | No |
| Function calling | No | Yes |
| JSON mode | No | Yes |
| Prompt caching | No | No |
| Batch API (50% discount) | No | No |
| Extended reasoning | No | No |
| Fine-tuning | No | No |
Inception Mercury 2 (OpenRouter) notes
OpenRouter offers 200+ models — showing top 15 unique models not available from other listed providers. Prices include OpenRouter markup.
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 Inception Mercury 2 (OpenRouter) 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 $62.50/month for Inception Mercury 2 (OpenRouter) — a 81% 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, Inception Mercury 2 (OpenRouter) or Nemotron Nano 9B?
Both Inception Mercury 2 (OpenRouter) and Nemotron Nano 9B have the same context window: 128,000 tokens.
Do Inception Mercury 2 (OpenRouter) and Nemotron Nano 9B support the Batch API?
Neither Inception Mercury 2 (OpenRouter) 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 Inception Mercury 2 (OpenRouter) 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 Inception Mercury 2 (OpenRouter) vs Nemotron Nano 9B?
Inception Mercury 2 (OpenRouter) is best suited for Document summarization, General chatbot, 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 Inception Mercury 2 (OpenRouter) vs Nemotron Nano 9B?
At 1,000 input tokens and 500 output tokens per request — a typical conversational workload — Inception Mercury 2 (OpenRouter) costs $0.000625 per request and Nemotron Nano 9B costs $0.000120 per request. At 100,000 requests/month, that translates to $62.50 and $12.00 respectively. Use the interactive calculator to adjust these parameters for your actual workload.
Inception Mercury 2 (OpenRouter) vs Nemotron Nano 9B: Summary
When comparing Inception Mercury 2 (OpenRouter) 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 $62.50/month for Inception Mercury 2 (OpenRouter).
Both models are priced in USD per million tokens, the standard unit across all major AI API providers. Inception Mercury 2 (OpenRouter) charges $0.25/M for input tokens and $0.75/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: Both models support 128,000 tokens per request. 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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