ThinkFlowLab / system1-agents

> [!NOTE]
> **Give your agents a System 1 decision model. Start from a prebuilt agent or build your own.**
>
> Describe the task. Claude Code or Codex runs a prebuilt agent or builds a new one, on Jev,
> Laya or Cua-S1 Nano.
> Browser use, computer use, robotics and games ship ready to run.
>
> **Up to 6× faster and 25× cheaper than a chat model, at the same score.**
Quickstart · From Claude Code or Codex · Benchmarks · Docs
| scenario | Jev | chat model | speedup | Jev cost | chat model cost | more expensive |
|---|---|---|---|---|---|---|
| Browser use (Allrecipes)† | 35.7 s | 138.7 s | 3.89× | $0.091356 | $1.494331 | 16.4× |
| Custom agent (ticket router, 30 tickets) | 12.7 s | 65.3 s | 5.14× | $0.000764 | $0.014800 | 19.4× |
| Computer use (Windows Calculator) | 17.2 s | 30.1 s | 1.75× | $0.000447 | $0.003002 | 6.7× |
| Robotics (ALFWorld) | 7.4 s | 25.7 s | 3.47× | $0.000221 | $0.002800\* | 12.7× |
| Games (2048, 20 moves) | 27.1 s | 68.5 s | 2.53× | $0.000447 | $0.006139 | 13.7× |
| Games (Millionaire) | 15.3 s | 21.6 s | 1.41× | $0.000168 | $0.000892 | 5.3× |
| Games (Blackjack) | 2.3 s | 14.7 s | 6.39× | $0.000021 | $0.000531 | 25.3× |
† The first Allrecipes task of the WebVoyager task set
(He et al., 2024, Apache-2.0, attribution in NOTICE): a vegetarian
lasagna with over 100 reviews, 4.5 stars or more, for 6. The chat model of that row is Claude Fable 5.1 through
OpenRouter; both models pay it for the typed search text and the answer. \* Estimated; the chat-model run recorded no
cost. Each replay below is the episode behind its row, Jev on the left and the chat model on the right, both on the
wall clock. The other Allrecipes runs, longer games and the Google Flights driver comparison with its rerun of
2026-09-23: docs/benchmarks.md.
 Browser use, WebVoyager's Allrecipes task 0 on the live site, replay at 8× speed 
 Computer use, the Windows Calculator, replay at 4× speed 
 Ticket router, 30 tickets to five queues, replay at 8× speed 
 ALFWorld, an embodied household task, replay at 2× speed 
 2048, 20 moves, replay at 8× speed 
 Millionaire, a 15-question quiz ladder, replay at 4× speed 
 Blackjack, one hand, replay at 2× speed 
### OmniJev: a decision model that reads the screen
OmniJev (Apache-2.0, Beijing Zhongguancun Academy, CASIA and Zevo) is a
System 1 decision model on Qwen3.5 vision-language backbones (0.8B, 2B, 4B): it answers the same typed questions as
Jev over a screenshot, a video or a robot camera. `--model omnijev` puts it in the slot of the browser agents, which
then send it a screenshot of the page at every step (docs/decision-models.md).
The clips below are OmniJev's own v1.1 demos with its 4B model: replays of recorded trajectories with the model's
probabilities, not s1a runs and not live control. They are shown from the OmniJev repository and keep their upstream
terms.
 Web: Mind2Web test tasks (OmniJev v1.1 replay) 
 Phone: AndroidControl tasks (OmniJev v1.1 replay) 
 Games: Enduro, Skiing and Pong (OmniJev v1.1 re