Which model should handle the expensive path?
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Model Recommendation Console
A decision console that maps use-case constraints to a model shortlist across quality, latency, price, context, privacy, and deployment surface.
Live Studio demo
Model recommendation console
Turn buyer constraints into a model route: primary model, fallback route, risk flag, and the benchmark evidence still needed before production.
Primary route
Fast mid-tier model
Fallback route
Small routing model
Risk flag
Good fit
Fit ranking
Support automation
Fast mid-tier model77
Best first route for support, extraction, CRM updates, and common workflow automation.
Frontier reasoning model70
Best for ambiguous work where one accepted answer avoids expensive downstream review.
Open-weight local model68
Useful when data locality and control matter more than maximum reasoning quality.
Small routing model68
Cheap and fast for routing; unsafe as the final model for complex answers.
RouteQualitySpeedCostPrivacy
Default production workhorse82867666
Hard cases and final review94584262
Private or offline baseline64627095
Triage, labels, and fallbacks48949670
Next benchmark to run: compare fast mid-tier model against small routing model on a private sample for support automation, then publish fit score, failure modes, and cost per accepted output.
How it works
Each Studio surface is designed as a practical operating loop: capture the buyer problem, run measured evidence, and return a decision artifact that can be acted on.
Current demo state
Preview decision console; next release should connect to live provider pricing and benchmark run imports.
1
Enter workload shape, latency target, context size, privacy boundary, accuracy risk, and monthly volume.
2
Map requirements against benchmark tracks, pricing levers, deployment constraints, and provider strengths.
3
Compare primary, cheaper fallback, and local/open-weight options with clear tradeoffs.
4
Export a recommendation memo with tests to run before production.
Buyer questions
These are the questions the product needs to answer before someone deploys, buys, or scales the system.
Where can a cheaper router or fallback be used?
What latency and privacy constraints change the answer?
What benchmark evidence is still missing?
Deliverables
What a buyer gets
Model shortlist
Fallback map
Monthly cost envelope
Pre-production test plan
Connected evidence
Read the benchmark trail
Studio packet
Buyer-ready demo packet.
This generated packet gives Sanjay and Saujas a consistent follow-up artifact for demos, consulting calls, and product conversations.
Next build step
Turn this Studio surface from a populated product brief into a live demo by wiring real run data, screenshots, and client-approved examples into the same page.