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Proving Ground · Rank 7 of 9

Laguna XS 2.1

poolside's 33B coding-agent model — 3B parameters active at a time — compressed to NVFP4 on one desktop-sized AI computer.

90.2%
496 of 550 graded answers correct
550 tasks × 3 passes

Setup and speed

Model
Laguna XS 2.1
poolside's 33B coding-agent model — 3B parameters active at a time — compressed to NVFP4 on one desktop-sized AI computer.
Architecture
MoE · 33B total / 3B active
Mixture-of-experts — only the active slice runs per token; totals and active counts are from the official card.
Speculative decoding
DFlash
What this published run actually used for speculation — not every method the checkpoint supports.
Quantization
NVFP4 (poolside)
Compressed so it fits the hardware below — a higher or lower bit-width version would score differently
Deployment
1× DGX Spark (dgx-spark-x1)
Served by vLLM 0.25.1 + DFlash-NVFP4 drafter (Mia Laguna-S recipe, XS weights). One desktop-sized AI computer runs the whole model.
Source
poolside · Mia
Model, NVFP4 weights and DFlash drafter by poolside; Spark serving recipe by Mia (vLLM 0.25.1, FlashInfer, 7 speculative tokens), swapped onto Laguna XS 2.1 after vLLM 0.29 failed DFlash graph capture, run at 91% memory and a 131K context.
First token
0.00s
starts responding almost instantly
Writing speed
74.6 w/s
the pace of the prose once it starts
Tokens per second
97
the raw generation rate behind that
Visible answer starts
~23.17s
with thinking on, it reasons before it writes
Typical task
15.8s
half finish faster than this
Slow tasks
38.0s
9 in 10 finish inside this

Full results

Score by task difficulty
easy
93.9%
One clear step — read the request, produce the answer.
573 graded answers
medium
90.6%
Several steps or a judgment call: reconcile records, pick a queue, pull a field.
714 graded answers
hard
81.5%
Multi-step work with a trap: a policy to apply, a dataset to analyze, a budget to stay inside.
363 graded answers
Score by kind of work
Inbox triage and reply
96%
96/100 correcttypical 12.1s
Document extraction
96%
96/100 correcttypical 17.2s
Spreadsheet analysis
91%
91/100 correcttypical 22.5s
Formulas and SQL
78%
78/100 correcttypical 2.9s
Business writing
87%
87/100 correcttypical 18.8s
Classification and routing
96%
48/50 correcttypical 9.6s
Where it missed
  • —Each task is run three times; the score counts all 1,650 attempts, not 550 tasks.
  • —Beats Laguna S 2.1 on the same task set (496 vs 466) despite being the smaller sibling — strongest on Inbox triage and Document extraction (both 96) and Classification (48/50). Softest on Formulas & SQL at 78, which falls to 57 on hard tasks, and Spreadsheet analysis hard at 65 with step-limit failures.
  • —428 of 550 tasks were correct on all three passes. Nothing was cut off by the output limit — every miss was a wrong answer or a format/step budget issue.
  • —Files round: workbook and social posts passed the machine checks (quality 1.75 and 2.75). The annual report was produced but failed length (about 3.4 pages vs an eight-to-twelve-page brief, quality 2.0). The investor deck never wrote a file before the task ended.
  • —Speed probe (thinking on): first visible token median 23.2s, decode about 97 tok/s (~75 words/s). TTFT not separated from first visible content on this stack.

With thinking on, the first token arrives at 0.00s but the visible answer does not start until roughly 23.17s while the model reasons. The 15.8s typical task time is that reasoning plus the answer.

Files it produced

Four real documents from one fact sheet, produced once. Passed is machine-checked against the fact sheet and the brief; quality is a separate 1–5 score from a published rubric and never changes whether a file passed. How files are graded →

Passed 2/4Quality 2.17 / 5
Annual reportquality 2.00

An 8–12 page annual report with six required sections: shareholder letter, financial review, category performance, customer and geographic performance, risk factors, and outlook.

Download DOCX
Supporting workbookquality 1.75

A two-sheet workbook: a Summary comparing FY2025 to FY2024, and a Monthly sheet with all twelve months.

Download XLSX
Investor deck

A ten-slide investor presentation following a fixed outline, with the brand palette applied and at least one real chart object.

Not produced — the model never wrote this file
Social announcementsquality 2.75

An X post of 280 characters or fewer and a LinkedIn post, both announcing the results, text only.

Download MD

Every artifact below is the file the model actually produced, published unedited so you can open it yourself. These are AI-generated documents about a fictional company — read them as samples of the model's work, not as advice or a real annual report. The workbook's formula cells hold real formulas — a viewer that does not recalculate may show them blank until Excel opens the file.