Bigger Isn't Always Better: Gemma 31B vs Ministral 14B on a Pivot Table

More parameters doesn't automatically mean better extraction. 

Same insurance pivot table as the last video, same generic "*" query, no schema, but this time run through Sparrow's Advanced mode, backed by Gemma 4 31B Dense, instead of Standard mode Ministral 14B.

Result: Gemma 4 31B, despite being over twice the size, was less accurate on this pivot table than Ministral 14B was. It hallucinated on column values — assigning null to cells that had real values, then shifting the actual value into the next column instead. A column-alignment failure Ministral 14B didn't have.

The takeaway: model size isn't a proxy for fit. Structured extraction on dense tabular layouts seems to favor whatever model was better tuned for structure-following, not the model with more parameters. Worth testing both tiers against your actual documents before assuming "Advanced" means "more accurate."

Can an LLM Read a Pivot Table? Sparrow + Ministral 14B

Pivot tables are a genuinely hard case for LLM-based extraction — row/column headers, merged cells, and aggregated values instead of a flat list. In this video I test whether Ministral 14B, running in Sparrow's Standard tier, can handle one.

The document: an insurance pivot table. The query: a generic "*", no predefined schema. Sparrow's UI (sparrow.katanaml.io/process) sends it to Ministral 14B running locally via MLX-VLM, which has to infer the structure itself and return clean, structured JSON.

No schema tuning, no hints file — just upload and extract.

Built with Sparrow — open-source document intelligence platform.

Gemma 4 12B vs Ministral 14B: Who Wins at Structured Table Extraction?

Head-to-head test: Gemma 4 12B vs Ministral 14B on structured table extraction.

In this video, I run a head-to-head test: Gemma 4 12B (8-bit and bf16) vs Ministral 14B (8-bit), extracting data from a 5-row table — two columns, JSON schema, array output.

Results:

• Gemma 4 12B (both quantizations): fails to return a proper JSON array
• Ministral 14B 8-bit: extracts all rows correctly