Temperature=0 Doesn't Mean Deterministic. Your Batch Size Does.
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The problem A team I worked with had an eval suite that called their model at temperature=0 and diffed the output against a golden completion, on the theory that greedy decoding meant identical input in, identical output out — perfect for catching regressions. Most of the time it worked. A few times a week, a completion that had passed for months would suddenly diff as "failed," with no code change, no prompt change, no model version bump. They spent real engineering hours convinced their…
1Key Takeaways
- The problem A team I worked with had an eval suite that called their model at temperature=0 and diffed the output against a golden completion, on the theory that greedy decoding meant identical input in, identical output out — perfect for catching regressions.
- A few times a week, a completion that had passed for months would suddenly diff as "failed," with no code change, no prompt change, no model version bump.
- They spent real engineering hours convinced their….
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3Why it matters
Coding AI shifts how fast software ships and how much human review each change needs. DEV — ML reports that the problem A team I worked with had an eval suite that called their model at temperature=0 and diffed the output against a golden completion, on the theory that greedy decoding meant identical input in, identical output out — perfect for catching regressions.
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