Llama 4 Scout (Fireworks) vs Nemotron Super 49B: API Cost Comparison
Compare the API pricing, context windows, features, and real-world cost projections for Llama 4 Scout (Fireworks) (Fireworks 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 Mar 11, 2026
Interactive Cost Calculator
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Showing costs for 2 models. Cheapest: Llama 4 Scout (Fireworks) at $3.00/month.
| Alert | |||||||
|---|---|---|---|---|---|---|---|
BestLlama 4 Scout (Fireworks) | Fireworks AI | $3.00 | $0.000300 | $2.00 | $1.00 | — | 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 | Llama 4 Scout (Fireworks) | Nemotron Super 49B | Cheaper |
|---|---|---|---|
| Input (standard) | $0.20/M | $0.10/M | Nemotron Super 49B |
| Output | $0.20/M | $0.40/M | Llama 4 Scout (Fireworks) |
| Cached input | $0.10/M | N/A | — |
| Batch input | $0.10/M | N/A | — |
| Batch output | $0.10/M | N/A | — |
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 | Llama 4 Scout (Fireworks)Monthly | Nemotron Super 49BMonthly | Llama 4 Scout (Fireworks)Per request | Nemotron Super 49BPer request |
|---|---|---|---|---|
| 1K requests/mo | $0.30 | $0.30 | $0.000300 | $0.000300 |
| 10K requests/mo | $3.00 | $3.00 | $0.000300 | $0.000300 |
| 100K requests/mo | $30.00 | $30.00 | $0.000300 | $0.000300 |
| 1M requests/mo | $300.00 | $300.00 | $0.000300 | $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 Llama 4 Scout (Fireworks)
by Fireworks AI
- Customer support
- RAG / Semantic search
- General chatbot
Input / 1M tokens
$0.20/M
Output / 1M tokens
$0.20/M
Context window
10,000,000
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 | Llama 4 Scout (Fireworks) | Nemotron Super 49B |
|---|---|---|
| Context window | 10,000,000 tokens | 128,000 tokens |
| Max output tokens | 16,384 tokens | 8,192 tokens |
| Performance tier | Budget | Budget |
| Vision / image input | Yes | No |
| Function calling | Yes | Yes |
| JSON mode | Yes | Yes |
| Prompt caching | Yes | No |
| Batch API (50% discount) | Yes | No |
| Extended reasoning | No | No |
| Fine-tuning | No | No |
Llama 4 Scout (Fireworks) notes
Fireworks serverless pricing. Cached input 50% discount. Batch inference at 50% of serverless rates. 10M context window.
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 Llama 4 Scout (Fireworks) cheaper than Nemotron Super 49B?
Llama 4 Scout (Fireworks) and Nemotron Super 49B cost the same at standard usage (1,000 input + 500 output tokens, 100K requests/month): $30.00/month each. For different token ratios, use the calculator above.
Which model has a larger context window, Llama 4 Scout (Fireworks) or Nemotron Super 49B?
Llama 4 Scout (Fireworks) has a larger context window at 10,000,000 tokens, compared to 128,000 tokens for Nemotron Super 49B. A larger context window is important for processing long documents, multi-turn conversations, or large codebases without truncation.
Do Llama 4 Scout (Fireworks) and Nemotron Super 49B support the Batch API?
Llama 4 Scout (Fireworks) supports the Batch API (50% discount for async processing), while Nemotron Super 49B does not. If your workload tolerates up to 24-hour latency, routing to Llama 4 Scout (Fireworks) with batch pricing could significantly cut costs versus Nemotron Super 49B's standard rate.
Which model offers better prompt caching?
Llama 4 Scout (Fireworks) supports prompt caching at $0.10/M for cached input, while Nemotron Super 49B does not offer prompt caching. For RAG applications or chatbots with large, repeated context, Llama 4 Scout (Fireworks)'s caching capability can substantially reduce effective costs.
What are the best use cases for Llama 4 Scout (Fireworks) vs Nemotron Super 49B?
Both models are well-suited for General chatbot. Llama 4 Scout (Fireworks) is particularly strong for Customer support, RAG / Semantic search. Nemotron Super 49B is favored for Content Creation, Summarization. At the same quality level, the lower-cost model is usually preferable; use this page's calculator to compare total monthly spend at your volume.
What is the cost per request for Llama 4 Scout (Fireworks) vs Nemotron Super 49B?
At 1,000 input tokens and 500 output tokens per request — a typical conversational workload — Llama 4 Scout (Fireworks) costs $0.000300 per request and Nemotron Super 49B costs $0.000300 per request. At 100,000 requests/month, that translates to $30.00 and $30.00 respectively. Use the interactive calculator to adjust these parameters for your actual workload.
Llama 4 Scout (Fireworks) vs Nemotron Super 49B: Summary
When comparing Llama 4 Scout (Fireworks) and Nemotron Super 49B for API cost, the right choice depends on your workload's token profile, required features, and tolerance for latency. Both models cost the same at standard usage volumes (1,000 input + 500 output tokens per request at 100,000 requests/month) at $30.00/month.
Both models are priced in USD per million tokens, the standard unit across all major AI API providers. Llama 4 Scout (Fireworks) charges $0.20/M for input tokens and $0.20/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.
Prompt caching is supported by Llama 4 Scout (Fireworks) but not Nemotron Super 49B. 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: Llama 4 Scout (Fireworks) supports up to 10,000,000 tokens in a single request, versus 128,000 tokens for Nemotron Super 49B. 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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