Can You Trust a Free AI Stack? Five Verification Myths, Tested

说明与用途

针对免费 AI 堆栈的自动化验证流程：使用 probe.py 脚本和声明账本，系统测量延迟、令牌使用和稳定性，揭示免费层的限制。

问题

Developers often assume free AI tiers provide reliable performance, reproducibility, and deployment guarantees, leading to unexpected failures and misaligned expectations.

结果

The author demonstrates that systematic, repeatable probes reveal hidden limitations of free AI tiers, enabling teams to make informed decisions about concurrency, staging, reproducibility, token budgeting, and deployment verification.

工作流

• 1. Identify the myth to test (e.g., concurrency limits, staging reliability, reproducibility, token allowance, deployment verification).
• 2. Design a probe: decide on request pattern (sequential vs parallel), number of calls, prompt, and metrics to capture (status, latency, retry count, usage).
• 3. Implement the probe script (e.g., probe.py) that logs each call’s metadata and aggregates results.
• 4. Run the probe against the free endpoint, capturing a fingerprint (Python version, OS, endpoint URL, prompt hash, timestamp).
• 5. Store the evidence in a JSON claim ledger with fields: claim, method, evidence, verdict, recorded, expires.
• 6. Review the ledger to confirm the claim holds today; schedule re‑runs to detect drift.
• 7. Adjust expectations or move to a paid tier if the free tier does not meet the required guarantees.

证据

Send 20 sequential requests, then 20 in parallel. Log status code, latency, and retry count for each.

来源

record a fingerprint before every run.

来源

The rule is simple. No expiry, no claim.

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