Pinecone diagnosis: upsert 400s on large batches

TL;DR: Symptom: big upsert batches fail with 400 Invalid Argument while small ones work. The request exceeds the size cap; split into smaller batches. Confirm it 1. Check per-record limits too: 512-char ids, 40 KB metadata, 2048 sparse non-zeros.

The fix

Diagnosis

Symptom

Upserting thousands of vectors in one call returns 400; the same vectors succeed in smaller batches.

Likely cause

Single upsert requests are capped at about 2 MB. Large batches with rich metadata exceed it. The 400 is deterministic for the same payload.

Confirm it

1. Halve the batch until it succeeds; the threshold you find is your effective cap for that vector shape.
2. Estimate: dimension times 4 bytes per vector plus metadata; keep batches comfortably under 2 MB.
3. Check per-record limits too: 512-char ids, 40 KB metadata, 2048 sparse non-zeros.

Fix

Batch by byte size, not just count: accumulate vectors until near the cap, then send. Parallelize across batches for throughput, with backoff on 429.

Verify the fix

Ingest the full dataset with the new batcher and assert describe_index_stats totals equal the source count.

When to use this

• This covers exactly what the title says: Pinecone diagnosis.
• You are setting this up for the first time, or auditing an existing setup.
• You want the key gotchas in one place before you start.

When not to use this

• You are doing a different workflow with Pinecone; these steps are specific to the title above.
• You need the full reference docs; this is the short path, not the manual.

Compatibility

• Not pinned to a specific version; follows current Pinecone behavior.

Pinecone's upsert guide documents the request size cap; the error-handling guide defines 400 and forbids retrying it. Limits reference: 512-char ids, 40 KB metadata. Verified against live docs 2026-09-26.