Explore more topics
Published model evaluations

GPT-5 Nano: trading task evaluations

See how openai/gpt-5-nano performed in 1 trading task evaluation, with exact version, measured results, dates and test inputs.

As of 2025-08-10

Jump to a section

TL;DR

GPT-5 Nano (openai/gpt-5-nano) appears in 1 published study. 2025-08-10, GPT-5 family and peers generating financial SQL queries: 0.467 for median score. Each result belongs to its own task, date and grading method.

Exact tested ID
openai/gpt-5-nano
Published studies
1
Provider
openai

Inspect this exact model

Step 1 of 3

GPT-5 family and peers generating financial SQL queries

GPT-5 Nano: source evidence dated 2025-08-10.

Median score
0.467
Avg score
0.465
Success rate
62.92%
Avg time
54,926 ms
Input cost
$0.05/M
Output cost
$0.40/M
What you should see

The displayed values belong to the identified model versions and this published task, with their original metric units.

Step 2 of 3

How did this version perform on the job I need?

The first measured row below belongs to this model, not its provider's other models. Open that study to see the other arms and tested input.

2025-08-10: GPT-5 family and peers generating financial SQL queries
What you should see

Select a model for the specific tested task. A profile with one study does not establish performance on other jobs.

Step 3 of 3

Test a strategy with Aurora

Select a model for the specific tested task. A profile with one study does not establish performance on other jobs.

Test a strategy with Aurora
What you should see

Keep reporting dates and units beside the answer, and inspect its original citations.

GPT-5 family and peers generating financial SQL queries

See the complete gpt-5 family and peers generating financial sql queries

GPT-5 Nano recorded 0.467 for median score in the 2025-08-10 publication. EvaluateGPT financial question set (count not restated in this article), 8 models.

Published metricValue
Median score0.467
Avg score0.465
Success rate62.92%
Avg time54,926 ms
Input cost$0.05/M
Output cost$0.40/M

GPT-5 family and peers generating financial SQL queries: read these measurements

View task, sample and measurement units

EvaluateGPT financial question set (count not restated in this article), 8 models

Generate syntactically and semantically valid SQL queries for real-world financial questions.

  1. Scoring

    LLM-judge scores from 0 to 1 as described in the linked GPT-oss article (Claude Sonnet 4, Gemini 2.5 Pro and GPT-4.1 judges in that article). This article does not restate the judges.

  2. Cost units

    List prices per million tokens, from $0.05/M input and $0.40/M output (GPT-5 Nano) to $1.25/M input and $10.00/M output (Gemini 2.5 Pro, GPT-5, GPT-5 Chat). Total spend was reported as around $200.

  3. Time units

    Average time in milliseconds, from 40,236 ms (Gemini 2.5 Flash) to 113,743 ms (GPT-5).

Continue exploring

Discussion

Sign in or create a free account to join the discussion.

No comments yet.

Aurora · AI research assistant

Try this in Aurora

Edit the request, then open it in Aurora. You choose when to send it.