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Llama 3.1 70B (Bedrock) vs Nemotron 70B Instruct: API Cost Comparison

Compare the API pricing, context windows, features, and real-world cost projections for Llama 3.1 70B (Bedrock) (AWS Bedrock) 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

AWS BedrockLlama 3.1 70B (Bedrock)Nvidia NIMNemotron 70B Instruct

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: Nemotron 70B Instruct at $18.00/month.

Cheapest: Nemotron 70B Instruct at $18.00/mo — save 44.3% vs Llama 3.1 70B (Bedrock)
Alert
BestNemotron 70B Instruct
Nvidia NIM$18.00$0.001800$12.00$6.0044.3%Alerts coming soon
Llama 3.1 70B (Bedrock)
AWS Bedrock$32.30$0.003230$19.50$12.80Alerts 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 TypeLlama 3.1 70B (Bedrock)Nemotron 70B InstructCheaper
Input (standard)$1.95/M$1.20/MNemotron 70B Instruct
Output$2.56/M$1.20/MNemotron 70B Instruct

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.

VolumeLlama 3.1 70B (Bedrock)MonthlyNemotron 70B InstructMonthlyLlama 3.1 70B (Bedrock)Per requestNemotron 70B InstructPer request
1K requests/mo$3.23$1.80$0.003230$0.001800
10K requests/mo$32.30$18.00$0.003230$0.001800
100K requests/mo$323.00$180.00$0.003230$0.001800
1M requests/mo$3,230.00$1,800.00$0.003230$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 tokens

When to Choose Llama 3.1 70B (Bedrock)

by AWS Bedrock

  • General chatbot
  • Summarization
  • Rag Retrieval

Input / 1M tokens

$1.95/M

Output / 1M tokens

$2.56/M

Context window

128,000

Tier

mid

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.

CapabilityLlama 3.1 70B (Bedrock)Nemotron 70B Instruct
Context window128,000 tokens128,000 tokens
Max output tokens4,096 tokens8,192 tokens
Performance tierMidMid
Vision / image inputNoNo
Function callingYesYes
JSON modeYesYes
Prompt cachingNoNo
Batch API (50% discount)YesNo
Extended reasoningNoNo
Fine-tuningNoNo

Llama 3.1 70B (Bedrock) notes

Meta Llama 3.1 70B via AWS Bedrock. Good balance of capability and cost for enterprise workloads requiring open-weight model governance.

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 70B (Bedrock) cheaper than Nemotron 70B Instruct?

At standard usage (1,000 input tokens, 500 output tokens, 100,000 requests/month), Nemotron 70B Instruct costs $180.00/month versus $323.00/month for Llama 3.1 70B (Bedrock) — a 44% 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 70B (Bedrock) or Nemotron 70B Instruct?

Both Llama 3.1 70B (Bedrock) and Nemotron 70B Instruct have the same context window: 128,000 tokens.

Do Llama 3.1 70B (Bedrock) and Nemotron 70B Instruct support the Batch API?

Llama 3.1 70B (Bedrock) supports the Batch API (50% discount for async processing), while Nemotron 70B Instruct does not. If your workload tolerates up to 24-hour latency, routing to Llama 3.1 70B (Bedrock) with batch pricing could significantly cut costs versus Nemotron 70B Instruct's standard rate.

Which model offers better prompt caching?

Neither Llama 3.1 70B (Bedrock) 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 70B (Bedrock) vs Nemotron 70B Instruct?

Both models are well-suited for General chatbot. Llama 3.1 70B (Bedrock) is particularly strong for Summarization, Rag Retrieval. Nemotron 70B Instruct is favored for Code generation, Data extraction. 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 70B (Bedrock) vs Nemotron 70B Instruct?

At 1,000 input tokens and 500 output tokens per request — a typical conversational workload — Llama 3.1 70B (Bedrock) costs $0.003230 per request and Nemotron 70B Instruct costs $0.001800 per request. At 100,000 requests/month, that translates to $323.00 and $180.00 respectively. Use the interactive calculator to adjust these parameters for your actual workload.

Llama 3.1 70B (Bedrock) vs Nemotron 70B Instruct: Summary

When comparing Llama 3.1 70B (Bedrock) and Nemotron 70B Instruct for API cost, the right choice depends on your workload's token profile, required features, and tolerance for latency. Nemotron 70B Instruct offers lower total cost at standard usage volumes (1,000 input + 500 output tokens per request at 100,000 requests/month) at $180.00/month, compared to $323.00/month for Llama 3.1 70B (Bedrock).

Both models are priced in USD per million tokens, the standard unit across all major AI API providers. Llama 3.1 70B (Bedrock) charges $1.95/M for input tokens and $2.56/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.

Explore other model comparisons from the same providers or performance tiers.

Related Provider Pages

View complete pricing tables and model lineups for the providers behind these models.

Relevant Use Cases

See cost recommendations for workloads where Llama 3.1 70B (Bedrock) or Nemotron 70B Instruct is recommended.