Llama 3.1 8B (SambaNova) vs Nemotron 70B Instruct: API Cost Comparison
Compare the API pricing, context windows, features, and real-world cost projections for Llama 3.1 8B (SambaNova) (SambaNova) and Nemotron 70B Instruct (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 3.1 8B (SambaNova) at $2.00/month.
| Alert | |||||||
|---|---|---|---|---|---|---|---|
BestLlama 3.1 8B (SambaNova) | SambaNova | $2.00 | $0.000200 | $1.00 | $1.00 | 88.9% | Alerts coming soon |
Nemotron 70B Instruct | Nvidia NIM | $18.00 | $0.001800 | $12.00 | $6.00 | — | Alerts coming soon |
Monthly Cost Comparison
Price Comparison at a Glance
All prices are in USD per 1 million tokens ($/M tokens). Lower is cheaper.
| Pricing Type | Llama 3.1 8B (SambaNova) | Nemotron 70B Instruct | Cheaper |
|---|---|---|---|
| Input (standard) | $0.10/M | $1.20/M | Llama 3.1 8B (SambaNova) |
| Output | $0.20/M | $1.20/M | Llama 3.1 8B (SambaNova) |
Prices last verified: 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 3.1 8B (SambaNova)Monthly | Nemotron 70B InstructMonthly | Llama 3.1 8B (SambaNova)Per request | Nemotron 70B InstructPer request |
|---|---|---|---|---|
| 1K requests/mo | $0.20 | $1.80 | $0.000200 | $0.001800 |
| 10K requests/mo | $2.00 | $18.00 | $0.000200 | $0.001800 |
| 100K requests/mo | $20.00 | $180.00 | $0.000200 | $0.001800 |
| 1M requests/mo | $200.00 | $1,800.00 | $0.000200 | $0.001800 |
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 3.1 8B (SambaNova)
by SambaNova
- Text classification
- Data extraction
- Customer support
Input / 1M tokens
$0.10/M
Output / 1M tokens
$0.20/M
Context window
128,000
Tier
budget
When to Choose Nemotron 70B Instruct
by Nvidia NIM
- General chatbot
- Code generation
- Data extraction
Input / 1M tokens
$1.20/M
Output / 1M tokens
$1.20/M
Context window
128,000
Tier
mid
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 3.1 8B (SambaNova) | Nemotron 70B Instruct |
|---|---|---|
| Context window | 128,000 tokens | 128,000 tokens |
| Max output tokens | 8,192 tokens | 8,192 tokens |
| Performance tier | Budget | Mid |
| 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 | No | No |
Llama 3.1 8B (SambaNova) notes
Llama 3.1 8B on SambaNova. Best-in-class throughput for budget workloads. Ideal for high-volume, low-latency inference tasks.
Nemotron 70B Instruct notes
Nemotron 70B Instruct on NVIDIA NIM. NVIDIA's flagship instruction-tuned model delivering strong reasoning and alignment at mid-tier pricing.
Frequently Asked Questions
Is Llama 3.1 8B (SambaNova) cheaper than Nemotron 70B Instruct?
At standard usage (1,000 input tokens, 500 output tokens, 100,000 requests/month), Llama 3.1 8B (SambaNova) costs $20.00/month versus $180.00/month for Nemotron 70B Instruct — a 89% 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, Llama 3.1 8B (SambaNova) or Nemotron 70B Instruct?
Both Llama 3.1 8B (SambaNova) and Nemotron 70B Instruct have the same context window: 128,000 tokens.
Do Llama 3.1 8B (SambaNova) and Nemotron 70B Instruct support the Batch API?
Neither Llama 3.1 8B (SambaNova) nor Nemotron 70B Instruct 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 Llama 3.1 8B (SambaNova) nor Nemotron 70B Instruct 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 Llama 3.1 8B (SambaNova) vs Nemotron 70B Instruct?
Both models are well-suited for Data extraction. Llama 3.1 8B (SambaNova) is particularly strong for Text classification, Customer support. Nemotron 70B Instruct is favored for General chatbot, Code generation. 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 3.1 8B (SambaNova) vs Nemotron 70B Instruct?
At 1,000 input tokens and 500 output tokens per request — a typical conversational workload — Llama 3.1 8B (SambaNova) costs $0.000200 per request and Nemotron 70B Instruct costs $0.001800 per request. At 100,000 requests/month, that translates to $20.00 and $180.00 respectively. Use the interactive calculator to adjust these parameters for your actual workload.
Llama 3.1 8B (SambaNova) vs Nemotron 70B Instruct: Summary
When comparing Llama 3.1 8B (SambaNova) and Nemotron 70B Instruct for API cost, the right choice depends on your workload's token profile, required features, and tolerance for latency. Llama 3.1 8B (SambaNova) offers lower total cost at standard usage volumes (1,000 input + 500 output tokens per request at 100,000 requests/month) at $20.00/month, compared to $180.00/month for Nemotron 70B Instruct.
Both models are priced in USD per million tokens, the standard unit across all major AI API providers. Llama 3.1 8B (SambaNova) charges $0.10/M for input tokens and $0.20/M for output tokens. Nemotron 70B Instruct charges $1.20/M input and $1.20/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
See cost recommendations for workloads where Llama 3.1 8B (SambaNova) or Nemotron 70B Instruct is recommended.