Mistral Small 3.2 vs Nemotron Super 49B: API Cost Comparison
Compare the API pricing, context windows, features, and real-world cost projections for Mistral Small 3.2 (Mistral AI) and Nemotron Super 49B (Nvidia NIM). Use the interactive calculator below to compute your exact monthly cost based on your token usage and request volume.
Prices verified Apr 30, 2026
Interactive Cost Calculator
Fills in typical token counts for a workload type
Tokens in each prompt sent to the model
Tokens generated in each response
Total API calls per month
Showing costs for 2 models. Cheapest: Mistral Small 3.2 at $2.50/month.
| Alert | |||||||
|---|---|---|---|---|---|---|---|
BestMistral Small 3.2 | Mistral AI | $2.50 | $0.000250 | $1.00 | $1.50 | 16.7% | Alerts coming soon |
Nemotron Super 49B | Nvidia NIM | $3.00 | $0.000300 | $1.00 | $2.00 | — | Alerts coming soon |
Monthly Cost Comparison
Price Comparison at a Glance
All prices are in USD per 1 million tokens ($/M tokens). Lower is cheaper.
| Pricing Type | Mistral Small 3.2 | Nemotron Super 49B | Cheaper |
|---|---|---|---|
| Input (standard) | $0.10/M | $0.10/M | — |
| Output | $0.30/M | $0.40/M | Mistral Small 3.2 |
Prices last verified: 2026-03-11 – 2026-04-30
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 | Mistral Small 3.2Monthly | Nemotron Super 49BMonthly | Mistral Small 3.2Per request | Nemotron Super 49BPer request |
|---|---|---|---|---|
| 1K requests/mo | $0.25 | $0.30 | $0.000250 | $0.000300 |
| 10K requests/mo | $2.50 | $3.00 | $0.000250 | $0.000300 |
| 100K requests/mo | $25.00 | $30.00 | $0.000250 | $0.000300 |
| 1M requests/mo | $250.00 | $300.00 | $0.000250 | $0.000300 |
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 Mistral Small 3.2
by Mistral AI
- Text classification
- Data extraction
- Customer support
Input / 1M tokens
$0.10/M
Output / 1M tokens
$0.30/M
Context window
32,768
Tier
budget
When to Choose Nemotron Super 49B
by Nvidia NIM
- General chatbot
- Content Creation
- Summarization
Input / 1M tokens
$0.10/M
Output / 1M tokens
$0.40/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 | Mistral Small 3.2 | Nemotron Super 49B |
|---|---|---|
| Context window | 32,768 tokens | 128,000 tokens |
| Max output tokens | 4,096 tokens | 8,192 tokens |
| Performance tier | Budget | Budget |
| Vision / image input | No | No |
| Function calling | Yes | Yes |
| JSON mode | Yes | Yes |
| Prompt caching | No | No |
| Batch API (50% discount) | No | No |
| Extended reasoning | No | No |
| Fine-tuning | Yes | No |
Mistral Small 3.2 notes
Supports fine-tuning. Good for specialized classification tasks.
Nemotron Super 49B notes
Nemotron Super 49B on NVIDIA NIM. Budget-tier foundation model with TensorRT-LLM optimization for high-throughput inference on NVIDIA infrastructure.
Frequently Asked Questions
Is Mistral Small 3.2 cheaper than Nemotron Super 49B?
At standard usage (1,000 input tokens, 500 output tokens, 100,000 requests/month), Mistral Small 3.2 costs $25.00/month versus $30.00/month for Nemotron Super 49B — a 17% 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, Mistral Small 3.2 or Nemotron Super 49B?
Nemotron Super 49B has a larger context window at 128,000 tokens, compared to 32,768 tokens for Mistral Small 3.2. A larger context window is important for processing long documents, multi-turn conversations, or large codebases without truncation.
Do Mistral Small 3.2 and Nemotron Super 49B support the Batch API?
Neither Mistral Small 3.2 nor Nemotron Super 49B 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 Mistral Small 3.2 nor Nemotron Super 49B 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 Mistral Small 3.2 vs Nemotron Super 49B?
Mistral Small 3.2 is best suited for Text classification, Data extraction, Customer support, while Nemotron Super 49B is optimized for General chatbot, Content Creation, 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 Mistral Small 3.2 vs Nemotron Super 49B?
At 1,000 input tokens and 500 output tokens per request — a typical conversational workload — Mistral Small 3.2 costs $0.000250 per request and Nemotron Super 49B costs $0.000300 per request. At 100,000 requests/month, that translates to $25.00 and $30.00 respectively. Use the interactive calculator to adjust these parameters for your actual workload.
Mistral Small 3.2 vs Nemotron Super 49B: Summary
When comparing Mistral Small 3.2 and Nemotron Super 49B for API cost, the right choice depends on your workload's token profile, required features, and tolerance for latency. Mistral Small 3.2 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 $30.00/month for Nemotron Super 49B.
Both models are priced in USD per million tokens, the standard unit across all major AI API providers. Mistral Small 3.2 charges $0.10/M for input tokens and $0.30/M for output tokens. Nemotron Super 49B charges $0.10/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.
Context window capacity differs between the two: Nemotron Super 49B supports up to 128,000 tokens in a single request, versus 32,768 tokens for Mistral Small 3.2. 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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