# OpenAI's GPT-6.1-sol outperforms Jev on paused tasks, but lags in real-time

Digest AI · Research · published 2026-10-16T04:00:00Z

Canonical: https://digestai.news/story/openai-s-gpt-6-1-sol-outperforms-jev-on-paused-tasks-but-lags-in-real

## Summary

The paper introduces **RealtimeBench**, a benchmark of 180 tasks spanning six game types that continue running while an agent generates its response. By keeping the environment live, the authors can measure how timing affects performance of large‑language‑model agents.

Paired tests show that the larger GPT‑6.1‑sol model beats the faster Jev model when the games are paused, but Jev overtakes GPT‑6.1‑sol when the games keep running. To address this gap, the authors propose **Two‑Timescale Offline Recursive Self‑Improvement (TORSI)**. A slow “teacher” analyses failures in paused games, writes reusable instructions, and a fast “student” applies them without further teacher calls during live play. After two TORSI rounds, Jev’s average test score rises from **13.51** to **24.19** on a 0‑100 scale, improving across all six game types, and the same instructions lift three other models without additional tuning.

These results suggest a path toward real‑time intelligence, where deliberation and action are coordinated across different timescales to keep agents effective in continuously changing environments.

## Key points

- RealtimeBench evaluates agents on 180 continuously running tasks across six game types
- GPT-6.1-sol beats Jev when games are paused, but Jev is faster when games keep running
- TORSI training lifts Jev’s average score from 13.51 to 24.19 and helps three other models improve

## Why it matters

Shows that timing constraints matter for agent effectiveness and offers a training framework that could make future AI assistants more reliable in dynamic, real‑world settings.

## Sources

1. [The World Won't Wait: Evaluating and Teaching Agents Under a Live Clock](https://arxiv.org/abs/2610.20665) (arXiv cs.AI, 2026-10-16, primary source)

Part of the developing story: [The Rise and Fall of Jev Decision Models](https://digestai.news/thread/typesafe-s-jev-decision-model-costs-0-042-per-million-tokens-matches-sonnet-5) (4 stories)

## Cite

Digest AI, "OpenAI's GPT-6.1-sol outperforms Jev on paused tasks, but lags in real-time", 16 October 2026, https://digestai.news/story/openai-s-gpt-6-1-sol-outperforms-jev-on-paused-tasks-but-lags-in-real

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