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AI Model Selection Insights

Arm is exploring ways to help developers evaluate, compare, and select AI models.

This short survey asks about your experience with AI models, what influences model selection, and what would make Arm-curated model recommendations useful and trustworthy.

Estimated time: 3-5 minutes
1.Which best describes your role?(Required.)
2.Which industry or domain best describes your AI work?(Required.)
3.Which AI model types or tasks have you worked with hands-on?(Required.)
4.Which AI model providers or vendors have you worked with or evaluated?(Required.)
5.Where do you usually find or source AI models for evaluation or deployment?(Required.)
6.Which deployment targets have you evaluated or deployed AI models for?(Required.)
7.How important are these factors when selecting an AI model? As you answer, consider the tradeoffs you typically make between them.(Required.)
N/A
Not important
Slightly important
Moderately important
Very important
Essentail
Cost
Documentation / examples
Ease of deployment
Hardware compatibility
Latency
Licensing
Memory footprint
Model size
Please select 'N/A' to show you are paying attention
Power / energy efficiency
Quantization readiness
Reliability / stability
Runtime compatibility
Task accuracy
Throughput
8.What would make a model recommendation from Arm feel trustworthy?(Required.)
N/A
Not important
Slightly important
Moderately important
Very important
Essential
Arm-verified performance measurements
Clear explanation of why the model is recommended
Comparison with similar models
Known limitations or caveats
Licensing / compliance information
Quantization / optimization details
Reproducible tests, code, and methodology
Tested hardware and software configuration
9.Is there anything else you’d like to share about how you evaluate, compare, or select AI models?
10.If you’d like to to be contacted about future Arm user research opportunities and incentives, please leave your details below so that we can follow up.