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Mistral Large (Bedrock) vs Nemotron Super 49B: API Cost Comparison

Compare the API pricing, context windows, features, and real-world cost projections for Mistral Large (Bedrock) (AWS Bedrock) 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

AWS BedrockMistral Large (Bedrock)Nvidia NIMNemotron Super 49B

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 Super 49B at $3.00/month.

Cheapest: Nemotron Super 49B at $3.00/mo — save 97.0% vs Mistral Large (Bedrock)
Alert
BestNemotron Super 49B
Nvidia NIM$3.00$0.000300$1.00$2.0097.0%Alerts coming soon
Mistral Large (Bedrock)
AWS Bedrock$100.00$0.010000$40.00$60.00Alerts 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 TypeMistral Large (Bedrock)Nemotron Super 49BCheaper
Input (standard)$4.00/M$0.10/MNemotron Super 49B
Output$12.00/M$0.40/MNemotron Super 49B

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.

VolumeMistral Large (Bedrock)MonthlyNemotron Super 49BMonthlyMistral Large (Bedrock)Per requestNemotron Super 49BPer request
1K requests/mo$10.00$0.30$0.010000$0.000300
10K requests/mo$100.00$3.00$0.010000$0.000300
100K requests/mo$1,000.00$30.00$0.010000$0.000300
1M requests/mo$10,000.00$300.00$0.010000$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 tokens

When to Choose Mistral Large (Bedrock)

by AWS Bedrock

  • Code generation
  • Content Creation
  • Summarization

Input / 1M tokens

$4.00/M

Output / 1M tokens

$12.00/M

Context window

128,000

Tier

premium

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.

CapabilityMistral Large (Bedrock)Nemotron Super 49B
Context window128,000 tokens128,000 tokens
Max output tokens8,192 tokens8,192 tokens
Performance tierPremiumBudget
Vision / image inputNoNo
Function callingYesYes
JSON modeYesYes
Prompt cachingNoNo
Batch API (50% discount)YesNo
Extended reasoningNoNo
Fine-tuningNoNo

Mistral Large (Bedrock) notes

Mistral Large via AWS Bedrock. Strong multilingual performance. Useful for enterprises already on AWS that need Mistral's capabilities with native AWS security.

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 Large (Bedrock) cheaper than Nemotron Super 49B?

At standard usage (1,000 input tokens, 500 output tokens, 100,000 requests/month), Nemotron Super 49B costs $30.00/month versus $1,000.00/month for Mistral Large (Bedrock) — a 97% 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 Large (Bedrock) or Nemotron Super 49B?

Both Mistral Large (Bedrock) and Nemotron Super 49B have the same context window: 128,000 tokens.

Do Mistral Large (Bedrock) and Nemotron Super 49B support the Batch API?

Mistral Large (Bedrock) 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 Mistral Large (Bedrock) with batch pricing could significantly cut costs versus Nemotron Super 49B's standard rate.

Which model offers better prompt caching?

Neither Mistral Large (Bedrock) 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 Large (Bedrock) vs Nemotron Super 49B?

Both models are well-suited for Content Creation, Summarization. Mistral Large (Bedrock) is particularly strong for Code generation. Nemotron Super 49B is favored for General chatbot. 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 Mistral Large (Bedrock) vs Nemotron Super 49B?

At 1,000 input tokens and 500 output tokens per request — a typical conversational workload — Mistral Large (Bedrock) costs $0.010000 per request and Nemotron Super 49B costs $0.000300 per request. At 100,000 requests/month, that translates to $1,000.00 and $30.00 respectively. Use the interactive calculator to adjust these parameters for your actual workload.

Mistral Large (Bedrock) vs Nemotron Super 49B: Summary

When comparing Mistral Large (Bedrock) and Nemotron Super 49B for API cost, the right choice depends on your workload's token profile, required features, and tolerance for latency. Nemotron Super 49B offers lower total cost at standard usage volumes (1,000 input + 500 output tokens per request at 100,000 requests/month) at $30.00/month, compared to $1,000.00/month for Mistral Large (Bedrock).

Both models are priced in USD per million tokens, the standard unit across all major AI API providers. Mistral Large (Bedrock) charges $4.00/M for input tokens and $12.00/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: 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 Mistral Large (Bedrock) or Nemotron Super 49B is recommended.