CaptchaKraken-Lora-v1.2

LoRA adapter for Qwen/Qwen3.5-9B, trained on CaptchaKraken's synthetic puzzle generators. First CaptchaKraken model with animated ("video") challenge support, and the first trained against prompt generation 2.

Training run 20260812-005302. Verdict: ready-to-deploy — passed all three gates uncapped.

Requires captchakraken >= 2.5.0

This adapter answers generation-2 prompts. Every previously published CaptchaKraken model is generation 1, and sending this model a generation-1 prompt does not error — it silently degrades on every puzzle.

Client releases before 2.5.0 hardcode generation-1 prompt text and have no way to know otherwise, so do not point an older client at these weights. From 2.5.0 the client ships a model registry that maps this repo to generation 2 and serves the matching templates automatically; prompts.json here carries the exact text the weights were trained on, for anyone building their own client.

pip install "captchakraken>=2.5.0"      # or: npm install captchakraken@^2.5.0

Usage

Serve the adapter on top of the base model and disable thinking, or the reasoning parser routes the answer into reasoning and leaves content empty:

chat_template_kwargs = {"enable_thinking": false}

Coordinates are on a normalized 0–1000 scale (top-left (0,0), bottom-right (1000,1000)). Send the template matching the detected puzzle type as the text part of the user turn, image first. Animated puzzles are sent as one multi-image prompt of keyframes; the answer names the keyframe it acted on. See prompts.json → selection_rule.

Pixel budget matters as much as the prompt: this adapter was trained with MIN_PIXELS=200704 (448²) and MAX_PIXELS=518400 (720²). Qwen clamps each image's area into that band, so serving it under a different one shows the model a puzzle at a scale it never learned to read.

Training

Base	Qwen/Qwen3.5-9B
Method	LoRA, r=64, alpha=128, dropout 0.05
Targets	language model + visual tower (merger excluded)
Epochs	3
LR	1e-4
Batch / grad accum	1 / 8
Max pixels	518,400
Train entries	58,500 (1,548 val)
Data	synthetic generator output only

Real captured puzzles are deliberately excluded from training and kept for evaluation — that separation is what reveals when a generator stops matching the real puzzle.

Evaluation

All three gates run against this adapter, prompt-pinned to generation 2.

Tier	What it measures	Result
1	Hermetic pytest + prompt parity	pass
2	Graded solve rate vs. real, held-out static captchas	pass — overall 0.6155 (baseline 0.5535, tolerance 0)
3	Driving live HTML fixtures to completion, both ports	pass

Tier 2 is a graded score over real captures the model never trained on, not a pass/fail solve rate; treat it as a regression signal, not a marketing number.

License

CaptchaKraken Source-Available License v1.1 — see LICENSE.

You may use this commercially inside a product that delivers value beyond captcha solving itself: scrapers, data pipelines, your own browser automation, QA and accessibility tooling. Running it alongside a stealth or antidetect browser to automate your own work is explicitly permitted (§2(c)).

You may not, without a separate commercial agreement:

• sell, resell, or offer for a fee any captcha-solving service or API whose primary value is solving captchas (§3(a));
• distribute thin wrappers whose primary purpose is captcha solving (§3(b));
• proxy or relay this model's outputs through a paid or public API as a captcha-solving service (§3(c));
• ship it as a built-in captcha feature of a stealth / antidetect browser, profile manager, or automation platform you distribute to third parties (§3(d)) — note this restricts shipping it to others, not using it.

In short: you may build with this, but you may not sell the solve.

Commercial licensing: https://captchakraken.com