CaptchaKrakenV1_Lora

A multimodal LoRA adapter for Qwen/Qwen3.5-9B that solves image captchas. It is the model behind CaptchaKraken โ€” a self-hosted captcha solver for browser automation (npm captcha-kraken-js, PyPI captchakraken).

This adapter supersedes the earlier CaptchaKraken_v1 and CaptchaKraken_v1.1 repositories, which have been withdrawn. It is the same trained adapter as v1.1, republished under the CaptchaKraken Source-Available License and under a stable name.

Coverage

The first release covered grid captchas only ("select all squares withโ€ฆ"). This adapter also handles the non-grid puzzle families โ€” drag-to-slot, click-the-object, line-tracing, tile-fitting, and the other hCaptcha interaction types โ€” while keeping the grid performance. It is trained with per-object content supervision (each click/drag target is labelled by what it is, not just where), which is what recovered the drag/click puzzles.

Details

  • Base model: Qwen/Qwen3.5-9B (natively multimodal), revision c202236235762e1c871ad0ccb60c8ee5ba337b9a โ€” the revision this adapter was trained against.
  • Adapter: PEFT LoRA, r=32, lora_alpha=64, applied to both the language model and the vision tower, excluding the vision merger. Serving the adapter therefore requires vLLM's --enable-tower-connector-lora.
  • Task: image captcha solving. Grid tile selection (reCAPTCHA 3ร—3 / 4ร—4, hCaptcha 3ร—3 image grids) plus non-grid puzzles (drag / click / line / fit). For grids it returns the cell numbers to click; for interaction puzzles it returns the action (click points or drag vectors).

Serving (vLLM)

vllm serve Qwen/Qwen3.5-9B \
  --reasoning-parser qwen3 \
  --enable-lora --enable-tower-connector-lora \
  --max-lora-rank 32 --max-model-len 8192 \
  --trust-remote-code --port 8000 \
  --lora-modules captcha=CaptchaKraken/CaptchaKrakenV1_Lora

--enable-tower-connector-lora is required โ€” without it the vision half of the adapter is dropped and grid accuracy collapses. On limited-VRAM GPUs, serve a quantized base (AWQ/FP8) instead of the bf16 base above, or use one of the pre-merged single-file models below.

The CaptchaKraken project wires this up hands-off: setup.sh downloads the weights and the server auto-starts on the first solve.

Pre-merged models

If you would rather not wire up an adapter, this adapter merged into the base is published as two standalone models โ€” no adapter flags, one download:

Model Precision Weights Min VRAM
CaptchaKraken/Sunlight-AWQ-4bit 4-bit (AWQ) ~6 GB 11 GB
CaptchaKraken/Twilight-FP8 8-bit (FP8) ~14 GB 22 GB

License

CaptchaKraken Source-Available License v1.0 โ€” see LICENSE.

You may use, modify, and distribute this adapter, including commercially, where captcha solving is an internal component of a product that delivers value beyond the solve itself โ€” scrapers, anti-detection browsers, automation frameworks, QA and accessibility tooling.

You may not sell the solve: no reselling or offering for a fee any captcha solving service or API whose primary value is solving captchas, no thin wrappers that just expose this model's solving capability, and no relaying this model's outputs through a paid or public captcha-solving API. Those uses require a separate written commercial agreement from the copyright holder.

Copyright (c) 2026 CaptchaKraken LLC. All rights reserved.

Framework versions

  • PEFT 0.18.1
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