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- Introducing AI Recommendations: Use Case Benchmarks
Introducing AI Recommendations: Use Case Benchmarks
Instantly see which AI model recommendation is right for your use case
Modern FinOps and platform teams don’t just want the cheapest model—they want the right model for the job. But comparing quality across use cases can be tedious and fragmented.
That’s why we built Use Case Benchmarks. Now, on the AI Recommendations page, you get a dynamic column that shows the percentage change in benchmark score between your current (source) model and the recommended model—for the specific use case you care about.
What's New
Use Case Benchmarks in nOps is designed to help your team evaluate cost–quality trade-offs with confidence. Starting today, you’ll find it in Inform → Cost Saving Recommendations → AI Model Provider Optimization.
Use Case Dropdown (Benchmarks from ProLLM)
Choose the benchmark that aligns to your workflow: Coding Assistant, QA Assistant, Summarization, Image Understanding, LLM as Judge.
Scores are sourced from ProLLM and refreshed daily, so your decisions stay current.
Dynamic Use Case Column
A new column appears in the AI Recommendations table that dynamically switches based on your selected Use Case. It shows the % change in benchmark score between the source and the recommended model (e.g., +12.3% or −7.9%).
Now you can quantify your specific use case impact at a glance before you commit to a switch.
- Positive values indicate a higher benchmark score for the recommended model; negative values indicate a potential quality decrease.
- If a score is unavailable for either model, change is not shown.
- Hover tooltips reveal the current vs. suggested raw scores.
Who Benefits Most
FinOps Leaders | AI/ML Platform & MLOps Engineers | Engineering Managers / Data Science |
Validate that savings do not compromise critical use-case quality; communicate trade-offs clearly to stakeholders | Compare providers/ models with objective benchmarks; standardize migrations with less back-and-forth testing | Align model choices with team workflows (coding assistance, QA, summarization, etc.) and set guardrails for acceptable quality deltas |
Who Benefits Most
ProLLM, like many other benchmarking platforms, regularly performs benchmark tests on common AI model providers. Integrating your AI model usage with nOps will give you immediate access to Use Case Benchmarks, which are used to enrich your AI Recommendations. nOps currently supports direct integrations with OpenAI, Anthropic, Gemini, and Amazon Bedrock.
How to Get Started
To start using Use Case Benchmarks, navigate to Inform → Cost Saving Recommendations → AI Model Provider Optimization.
- Use the Use Case dropdown to select a benchmark (e.g., Coding Assistant).
- The Use Case Benchmarks column updates to show the % change between the source and recommended model for that benchmark.
- Hover any cell to see the Current and Suggested raw scores.
- Sort results by ascending or descending change percentage.
If you're already on nOps...
Have questions about AI Use Case Benchmarks? 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 a message.
If you’re new to nOps…
nOps was recently ranked #1 with five stars in G2’s cloud cost management category, and we optimize $2+ billion in cloud spend for our customers.
Join our customers using nOps to understand your cloud costs and leverage automation with complete confidence by booking a demo with one of our AWS experts.
