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CaptchaKraken/CaptchaKrakenV1_Lora
CaptchaKrakenV1_Lora is a image-text-to-text model from CaptchaKraken. Use it for the image-text-to-text task on the model card, and read the license before you ship it in a product. It is set up for peft. The card lists the license as other.
A multimodal LoRA adapter for Qwen/Qwen3.5-9B that solves image captchas. It is the model behind CaptchaKraken — a self-hosted captcha solver for browser automation (npm captcha-kraken-js, PyPI captchakraken).
Downloads · 30 days
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From the Hugging Face model README
A multimodal LoRA adapter for Qwen/Qwen3.5-9B that solves image captchas.
It is the model behind CaptchaKraken
— 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repositories, which have been withdrawn.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.
The first release covered grid captchas only ("select all squares with…"). This adapter also handles the non-grid puzzle families — drag-to-slot, click-the-object, line-tracing, tile-fitting, and the other interaction types — 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.
Qwen/Qwen3.5-9B (natively multimodal), revision
c202236235762e1c871ad0ccb60c8ee5ba337b9a — the revision this adapter was
trained against.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.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 — 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.
If you would rather not wire up an adapter, this adapter merged into the base is published as two standalone models — 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 |
CaptchaKraken Source-Available License v1.0 — 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 — 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.