Prefix cachingHigh fit
Test reuse of stable system instructions, policies, and repeated context to reduce duplicate prefill work.
Free workload assessment · No account needed
Yamify Workload Profiler
Understand your AI traffic. Find the optimizations worth testing for your workload, latency target, and budget.
01 Describe02 Analyze03 Measure & improve
01
Tell us about your workload
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02
Workload analysis
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WORKLOAD PROFILE
Agents / tools
1K–8Kinput / request
Under 200output / request
Steady 24/7traffic pattern
Fast responsebusiness priority
LIKELY FOCUS
Repeated prompt work may be consuming prefill capacity.
This is a workload-fit assessment, not a measured benchmark. Results depend on model, serving engine, hardware, context length, concurrency, and quality targets.
OPTIMIZATIONS TO INVESTIGATE
Continuous batchingHigh fit
Measure whether combining concurrent requests improves aggregate throughput at your latency target.
Decode and time-to-first-token tuningMeasure
Measure prefill and token-generation latency separately; shorter context or output limits may help when product quality allows.
Reduce avoidable contextReview
Review duplicated tool results, retrieved passages, and repeated instructions across the full request chain.
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Get a portable report to take to your team.
We’ll create a PDF with your workload answers and optimization priorities. A copy goes to your email and Yamify so our team can help you validate the opportunity.
Sharing is optional. Yamify receives the workload answers and the email address you provide.A useful optimization loop
Training, fine-tuning, and media workloads use different units and need separate sizing. This tool does not estimate their GPU requirements.