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Now Supporting Meta Llama on Bedrock

Save up to 90% on LLM spend while maintaining the same quality

nOps AI Model Provider Recommendations give you side-by-side guidance on when to switch AI models — such as from OpenAI to Amazon Bedrock — to reduce costs significantly while maintaining the same performance. 

Starting today, recommendations now include the Meta Llama on Bedrock (Meta Llama 4 Maverick, Meta Llama 4 Scout, Meta Llama 3.3 70B). This allows you to cut costs — often by an order of magnitude — without sacrificing response quality.

In the example below, a conversational service running GPT-4.1 costs $11,181.15 per month. Our engine flagged that the same prompt mix fits Llama-4-Scout 17B on Bedrock just as well, bringing projected spend down to $1,125.98 — a savings of $10,055.17 (-89.93%). In another example, our engine suggested a switch from GPT-4o to Llama-4-Maverick to reduce cost by 95% with an increase of 8.16% in quality.

AI provider recommendations in the nOps UI

What's New

nOps automatically detects your OpenAI models and assesses latency, context-window and function-calling needs. It calculates token economics using the latest model provider pricing from Amazon, OpenAI, Claude and now Llama, to select and recommend the most cost-efficient Bedrock model tier that meets your requirements—no guesswork needed.

Each recommendation includes a clear explanation of the proposed model switch, including pricing, capabilities, and projected savings.

How to Get Started

To access the new recommendations, log in to nOps. Navigate from Cost Optimization to the AI Model Provider Recommendations dashboard. 

If you're already on nOps...

Have questions about AI Model Provider Recommendations? Need help getting started? Our dedicated support team is here for you. Simply reach out to your Customer Success Manager or visit our Help Center. If you’re not sure who your CSM is, send our Support Team an email.

If you’re new to nOps…

Ranked #1 on G2 for cloud cost management and trusted to optimise $5B+ in annual spend, nOps gives you automated GenAI savings with complete confidence. Book a demo to start saving on LLM cost without compromising on performance. 

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Published Date: July 21, 2025, Announcement

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