Records
Every run you saved, with the date on it
最后更新:
A score without a date is a rumour. Models get updated, providers swap the weights behind a name, and a result from March says nothing about July. So each saved run keeps the date, the model ids, the task set version and the score together.
Your runs
A single score vs a dated record: the second one can be compared, the first cannot.
What a record contains
| Field | Why it is kept |
|---|---|
| Date and time | Model behaviour changes; a score is only meaningful against a date |
| Model ids | The exact ids tested, including any auto/ route; a route can resolve differently later |
| Task set version | So a score from v1 is never compared against a v2 run |
| Score per model | The headline number |
| Per-task failures | More useful than the total: it says which kind of task broke |
| Total time | Makes cost visible: the same score at half the latency is a different answer |
Where these are stored
Runs saved from Compare are stored in this browser only. They are not uploaded, and they are not visible to anyone else — which also means they do not follow you to another machine.
A shared record — every run, by everyone, on one page — needs a server-side store that does not exist yet. Until it does, this page reads your local runs and says so, rather than showing an empty list and implying nobody has ever run a test.
How a record gets here
Records are not written on this page. They are written on Compare, when you decide a run is worth keeping, and this page reads them back.
- Step 1: run a test. Sign in on Compare, paste
an
sk-key, choose the model ids and the task groups, and pressRun the test. - Step 2: press save.
Save this runis the only thing that writes anything. A run you do not save leaves no trace at all. - Step 3: come back here. The saved run appears above with its date, the model ids, the task set version and the score for each model.
- Step 4: pin the id you tested. If a record covers a modality route
such as
auto/imagerather than a named model, the note field is the only thing that will tell you later what it resolved to. Name the model in your own notes if the result matters.
Why the id and the date travel together
A score is one half of a fact. The other half is what answered and when, because both move. A named model can be updated behind the same id, and a route resolves per request — six of the 199 listed ids are modality routes, 3% of the list, and the model one of them picks on Monday is not guaranteed to be the model it picks on Friday.
The task set is the third variable, which is why its version is stored. Twelve tasks with exact checkers do not change quietly, but a change to the set would still make two scores incomparable, so v1 runs are never mixed with another version in the same comparison.
One more limit worth knowing before you read anything into a score: the set is text only. Of the 199 ids, 23% are not chat models and cannot answer these tasks at all; the 153 chat entries are the whole pool this set can exercise. A high score here says a model follows instructions exactly. It does not say it is the right model for your agent loop.
How to verify a record
A record is only useful if you can reproduce the run from it. Pick one record, copy its id and date, then re-run the same prompt with the same model. If the output differs, the record still tells you which model served the original run; that is the first thing to check before blaming the prompt.
- Check the model field against what you requested.
- Check the date against the price page in force that day.
- Check the input size; a truncated input explains most output differences.
Records FAQ
Where are my saved runs stored?
Can I see other people's runs?
Why does a record keep failures instead of only the score?
Why is the total time recorded?
How old is too old for a record to mean anything?
Records and privacy
A record contains the run id, date, model, and a summary of the request; it does not need to contain the full document. Store the minimum needed to reproduce the decision, and set a retention period. If a record includes customer text, treat it with the same rules as the source document.
Next
Sources
Every third-party figure quoted on this site was read from the vendor documentation linked below, on the date stated. None of these links are affiliate links and none of these vendors paid to be listed. If a number here disagrees with the page it came from, the page is right — tell us and it gets corrected.
- OpenRouter — credit-purchase fees and free-model rate limits
- OpenRouter — rate-limit reference
- OpenRouter — public model list
- LiteLLM — licence, deployment options and supported models
- Cloudflare AI Gateway — features and pricing
- Vercel AI Gateway — features
- Portkey — plans
- Helicone — plans
- Model Context Protocol — specification
- OpenAI Python SDK — base_url and OPENAI_BASE_URL
- Anthropic Messages API — request format
Key numbers
- 6 个字段
- 1 个日期
- 3 个版本维度
- 6 fields kept per record: date, model ids, task-set version, score, per-task failures, total time.
- 1 date per run — a score without a date is not comparable.
- Task-set version separates runs: a v1 score is never compared with a v2 run.
How to use it, step by step
- Step 1. Run the model set against a fixed task set.
- Step 2. Save the run: the date, the exact model ids, the task-set version and the per-task results go in together.
- Step 3. Compare only runs with the same task-set version, and read per-task failures before the headline score.
One worked example
A record for a 3,000-token run stores the run id, date, model, token counts, and a short request summary — not the full document. That is enough to re-run and compare. Keeping full inputs turns the record store into a second copy of your data, with the same privacy obligations and a larger bill.
What a record does not prove
A record proves a run happened with a given model and date. It does not prove the output was correct, and it does not prove the input was complete. Treat it as a receipt, not a review.
Record checklist
- Run id and date are present and immutable.
- Model field matches what actually served the request.
- Token counts are stored per request.
- Retention period is defined and enforced.
A record that cannot answer "which model, when, how many tokens" is a log line, not a record.