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Org card: ThinCtx-Qwen3.5-4B released, thinctx 0.2.0; the GPU context memory grows 30 to 40 times more slowly
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Download README.md from thinletter/README: direct link, hf CLI and curl.
- Browser
- Download file 1.85 kB
-
https://huggingface.co/spaces/thinletter/README/resolve/main/README.md
- Command line
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hf download hf://spaces/thinletter/README/README.md
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curl -L -o README.md https://huggingface.co/spaces/thinletter/README/resolve/main/README.md
1.85 kB
metadata
title: thinletter
emoji: 馃
colorFrom: pink
colorTo: yellow
sdk: static
pinned: false
thinletter is a small research group. We make existing models lighter to run and measure them against the originals. thinletter.io 路 info@thinletter.io
ThinCtx
Qwen3.5 models converted so that the GPU memory for the context stays small: it grows 30 to 40 times more slowly than the original's cache, with accuracy on par with the original model. The full context is kept in system memory, so long documents and long agent sessions fit on one consumer GPU.
- ThinCtx-Qwen3.5-4B
- ThinCtx-Qwen3.5-2B
- ThinCtx-Qwen3.5-0.8B (not recommended for tool calling)
- Runtime:
pip install thinctx路 results: thinletter.io/thinctx
ThinEmbed
The query side of an embedding model, compressed into a small file that runs in the browser on WebGPU, against your unchanged document index. Open source, Apache-2.0.
- harrier-0.6b (English): WebGPU clients 路 GGUF clients
- Qwen3-Embedding-0.6B (Czech): WebGPU client 路 GGUF client
- bge-m3 (Czech, multilingual): GGUF clients
- Demo 路 code 路 results: thinletter.io/query-encoders