Choosing the wrong AI model can burn budgets fast. Enter ArchitectGBT, promising 60-second model picks with cost breakdowns [1]. And any-LLM-gateway acts as a gatekeeper for spend and access [2].
Spend visibility isn’t optional in 2025. Direct API costs run 40–60% of total model expenses—the rest comes from infrastructure, optimization, error handling, and human review [3].
Performance, Cost of Ownership, Integration, Strategy—the Four-Dimension Evaluation Matrix asks teams to test across all four axes.
Dimension 1: Performance Testing on Actual Tasks - Benchmarks like MMLU and HumanEval tell you nothing about production work; test on real tasks instead [3]. - Task replication: complete five representative tasks from your workflow with documented completion rates. [3] - Edge case handling: feed three scenarios that previously broke implementations. [3] - Consistency verification: run prompts ten times; look for output variance. [3]
In one case, three models were tested for customer support; the leader on benchmarks hallucinated on edge cases, while the runner-up was consistently good and cut errors by 43% [3].
Dimension 2: Cost of Ownership - API pricing is only part of the bill; input token volume, output generation costs, and error handling overhead drive totals [3].
Dimensions 3 and 4: Integration and Strategy cover how well a model plugs into your stack and how decisions align with business goals [3].
Takeaway: pair structured evaluation with spend controls to turn model selection into a repeatable, money-saving practice [2][3].
References
How many of you have lost money due to choosing the wrong AI model?
User asks about losses from selecting AI models and tests a tool to help pick best models with cost insights.
View sourceControl LLM Spend and Access with any-LLM-gateway
Proposes an any-LLM gateway to manage costs and regulate access to LLM services.
View source[D] We built a 4-dimension framework for LLM evaluation after watching 3 companies fail at model selection
Proposes a four-dimension framework to evaluate LLMs across performance, cost, integration, and strategy, with protocols and examples.
View source