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prithivMLmods/Supertron3-0.8B-GGUF overview

Supertron3 0.8B GGUF Supertron3 0.8B https://huggingface.co/Surpem/Supertron3 0.8B is a compact vision language model from Suprem Org, fine tuned from Qwen3.5 …

transformersgguftext-generation-inferencellama-cppqwen3_5multimodalactionagentpytorchcomputer usegui agentstool-callingedgeimage-text-to-textenbase_model:Surpem/Supertron3-0.8Bbase_model:quantized:Surpem/Supertron3-0.8Blicense:apache-2.0endpoints_compatibleregion:usconversational

Runs locally from ~197.7 MB disk (4 GB VRAM class GPUs with llama.cpp / guIDE).

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Pipeline
image-text-to-text

Repository Files & Downloads

11 GGUF files detected
Direct downloads for local inference
FileTypeQuantizationSizeLink
Supertron3-0.8B.BF16.ggufGGUFGGUF1.41 GBDownload
Supertron3-0.8B.Q3_K_L.ggufGGUFGGUF468.6 MBDownload
Supertron3-0.8B.Q3_K_M.ggufGGUFGGUF444.6 MBDownload
Supertron3-0.8B.Q3_K_S.ggufGGUFGGUF415.2 MBDownload
Supertron3-0.8B.Q4_0.ggufGGUFGGUF478.2 MBDownload
Supertron3-0.8B.Q4_K_M.ggufGGUFGGUF504.8 MBDownload
Supertron3-0.8B.Q4_K_S.ggufGGUFGGUF481.8 MBDownload
Supertron3-0.8B.Q5_0.ggufGGUFGGUF537.5 MBDownload
Supertron3-0.8B.Q5_K_M.ggufGGUFGGUF551.2 MBDownload
Supertron3-0.8B.Q5_K_S.ggufGGUFGGUF537.5 MBDownload
Supertron3-0.8B.mmproj-bf16.ggufGGUFBF16197.7 MBDownload

Model Details

Model IDprithivMLmods/Supertron3-0.8B-GGUF
AuthorprithivMLmods
Pipelineimage-text-to-text
Licenseapache-2.0
Base modelSurpem/Supertron3-0.8B
Last modified2026-09-08T04:59:07.000Z

Model README

---

base_model:

  • Surpem/Supertron3-0.8B

tags:

  • text-generation-inference
  • llama-cpp
  • qwen3_5
  • multimodal
  • action
  • agent
  • pytorch
  • computer use
  • gui agents
  • tool-calling
  • edge

license: apache-2.0

language:

  • en

pipeline_tag: image-text-to-text

library_name: transformers

---

Supertron3-0.8B-GGUF

> Supertron3-0.8B is a compact vision-language model from Suprem Org, fine-tuned from Qwen3.5-0.8B, purpose-built for GUI agents and agentic tool calling at the edge — interpreting visual interfaces across web, desktop, and CLI environments to emit precise pyautogui-style computer-use actions or valid JSON function calls. Its hybrid architecture interleaves Gated DeltaNet and Attention layers (24 layers, 1024 hidden dimension) with a vision encoder, retains a 262K native context window, and fits in a 1.7GB footprint suited for low-latency, on-device deployment. Despite being the smallest model in its evaluation set, Supertron3-0.8B ranks first on BFCL-style function calling (82% vs. 56% for its own Qwen3.5-0.8B base and 69% for the larger Qwen3.5-4B) and is the only model in the comparison that can reliably execute computer-use tasks at all — scoring 100% on Computer Use versus 0% for the unmodified base model — though it trails slightly on Mind2Web step accuracy (77% vs. 80% for the base), reflecting that the fine-tune specifically taught the base model to act rather than just converse. It's deployable via Transformers, vLLM, or SGLang, with known limitations around long-horizon multi-turn workflows and ScreenSpot-Pro-class grounding precision, which the authors attribute to the constraints of an 0.8B-parameter vision encoder; it's released under the Apache 2.0 license.

Model Files

File Name | Quant Type | File Size | File Link |

|-----------|------------|-----------|-----------|

| Supertron3-0.8B.BF16.gguf | BF16 | 1.52 GB | Download |

| Supertron3-0.8B.Q3_K_L.gguf | Q3_K_L | 491 MB | Download |

| Supertron3-0.8B.Q3_K_M.gguf | Q3_K_M | 466 MB | Download |

| Supertron3-0.8B.Q3_K_S.gguf | Q3_K_S | 435 MB | Download |

| Supertron3-0.8B.Q4_0.gguf | Q4_0 | 501 MB | Download |

| Supertron3-0.8B.Q4_K_M.gguf | Q4_K_M | 529 MB | Download |

| Supertron3-0.8B.Q4_K_S.gguf | Q4_K_S | 505 MB | Download |

| Supertron3-0.8B.Q5_0.gguf | Q5_0 | 564 MB | Download |

| Supertron3-0.8B.Q5_K_M.gguf | Q5_K_M | 578 MB | Download |

| Supertron3-0.8B.Q5_K_S.gguf | Q5_K_S | 564 MB | Download |

| Supertron3-0.8B.mmproj-bf16.gguf | mmproj-bf16 | 207 MB | Download |

llama.cpp

LLM inference in C/C++ — https://github.com/ggml-org/llama.cpp

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