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Published model evaluations

o3: trading task evaluations

See how openai/o3 performed in 2 trading task evaluations, with exact version, measured results, dates and test inputs.

As of 2025-08-11

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TL;DR

o3 (openai/o3) appears in 2 published studies. 2025-07-11, Models generating financial SQL queries, July 2025: 0.900 for median score. 2025-08-11, Models turning plain-English trading rules into strategy configs: 0.900 for median score. Each result belongs to its own task, date and grading method.

Exact tested ID
openai/o3
Published studies
2
Provider
openai

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Step 1 of 3

Models generating financial SQL queries, July 2025

o3: source evidence dated 2025-08-11.

Median score
0.900
Avg score
0.635
Success rate
77.53%
Avg time
56,070 ms
Input cost
$2.00/M
Output cost
$8.00/M
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The displayed values belong to the identified model versions and this published task, with their original metric units.

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How did this version perform on the job I need?

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2025-07-11: Models generating financial SQL queries, July 2025
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Models generating financial SQL queries, July 2025

See the complete models generating financial sql queries, july 2025

o3 recorded 0.900 for median score in the 2025-07-11 publication. About 88 financial questions per the article text, 11 models.

Published metricValue
Median score0.900
Avg score0.635
Success rate77.53%
Avg time56,070 ms
Input cost$2.00/M
Output cost$8.00/M

Models generating financial SQL queries, July 2025: read these measurements

View task, sample and measurement units

About 88 financial questions per the article text, 11 models

Generate SQL queries that answer financial questions against a financial database.

  1. Scoring

    Three LLM judges assign a 0 to 1 quality score that is separate from whether the query executes. The article states the score measures query and answer assessment, not investment returns.

  2. Cost units

    List prices per million tokens, from $0.10/M input and $0.40/M output (Gemini 2.0 Flash) to $15.00/M input and $75.00/M output (Claude Opus 4). Total run spend was reported as over $200, with $171.88 on Requesty.

  3. Time units

    Average time in milliseconds, from 31,140 ms (Gemini 2.0 Flash) to 74,812 ms (Grok-4).

Models turning plain-English trading rules into strategy configs

Open every published row

o3 recorded 0.900 for median score in the 2025-08-11 publication. 14 models on one sample of strategy requests, this article does not state the count (the companion article of 2025-08-12 describes the same table as 12 financial questions).

Published metricValue
Median score0.900
Avg score0.824
Success rate100.0%
Avg time (ms)124,902
Input cost$2.00/M
Output cost$8.00/M

Models turning plain-English trading rules into strategy configs: read these measurements

View task, sample and measurement units

14 models on one sample of strategy requests, this article does not state the count (the companion article of 2025-08-12 describes the same table as 12 financial questions)

Convert a natural-language trading strategy request into a NexusTrade portfolio configuration of actions and conditions.

  1. Scoring

    LLM judges score each configuration from 0 to 1 using published guidelines (1.0 perfect match, 0.8 to 0.9 minor issues, 0.5 to 0.7 significant discrepancies, 0.2 to 0.4 major errors, 0.0 to 0.1 complete mismatch). Success rate is reported separately.

  2. Cost units

    The table lists each model's list price per million input and output tokens. It does not publish total run cost.

  3. Time units

    Average time per generation in milliseconds, as published in the table.

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