OpenAI’s Astra Model: Humanity’s Last Exam Debut?Polymarket historical data and price history
OpenAI’s Astra Model: Humanity’s Last Exam Debut: a standalone Polymarket other event with 3 markets and $53.5K in lifetime traded volume. All markets have resolved, each with its winning outcome stored. Marketlens records every market's order book at full depth, coverage running since September 9, 2026 through September 10, 2026.
Data as of 2026-10-05
Markets in this event
Query this event
from datetime import datetime, timedelta, timezone
from marketlens import MarketLens
client = MarketLens()
[event] = client.events.list(q="OpenAI’s Astra Model: Humanity’s Last Exam Debut", take=1)
for market in client.events.markets(event.id, take=5):
print(market.question, market.outcomes[0].last_price)
# the order book behind any market, at any past moment
# a free key reads markets open in the last 7 days
book = client.orderbook.get(market.id, at=datetime.now(timezone.utc) - timedelta(days=2))
print(book.midpoint, book.bid_depth, book.ask_depth)Common questions
What data does Marketlens have for "OpenAI’s Astra Model: Humanity’s Last Exam Debut"?
3 markets with full depth L2 order book history recorded since September 9, 2026, market metadata with lifetime traded volume, and the winning outcome for each market once it resolves.
How much has "OpenAI’s Astra Model: Humanity’s Last Exam Debut" traded on Polymarket?
$53.5K in cumulative traded volume across the event's markets. Per market volumes are listed in the table on this page.
How do I download "OpenAI’s Astra Model: Humanity’s Last Exam Debut" data?
Query it through the REST API or the Python SDK (pip install marketlens): search events for "OpenAI’s Astra Model: Humanity’s Last Exam Debut", list the event's markets, then pull each market's order book history. Bulk Parquet exports cover full markets for offline work; the free tier reads markets open in the last 7 days and Pro the full archive.
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The free tier includes 2M data rows and every market open in the last 7 days, no card required.
$ pip install marketlens