GraySoft
Projects Models Compare Cloud benchmarks FAQ Download guIDE →
Model Intelligence Sheet

prithivMLmods/APUS-OpenJev-v1-9B-GGUF overview

APUS OpenJev v1 9B GGUF APUS OpenJev v1 9B is a Qwen3.5 9B based decision model from APUS AI LAB, designed for browser action selection, workflow routing, and …

transformersgguftext-generation-inferencellama-cppapus-openjevdecision-modelstructured-outputbf16text-generationenzhbase_model:apus-ailab/APUS-OpenJev-v1-9Bbase_model:quantized:apus-ailab/APUS-OpenJev-v1-9Blicense:apache-2.0endpoints_compatibleregion:usconversational

Runs locally from ~4.31 GB disk (8 GB VRAM class GPUs with llama.cpp / guIDE).

Downloads
0
Likes
2
Pipeline
text-generation

Repository Files & Downloads

8 GGUF files detected
Direct downloads for local inference
FileTypeQuantizationSizeLink
APUS-OpenJev-v1-9B.BF16.ggufGGUFGGUF16.69 GBDownload
APUS-OpenJev-v1-9B.Q3_K_L.ggufGGUFGGUF4.59 GBDownload
APUS-OpenJev-v1-9B.Q3_K_M.ggufGGUFGGUF4.31 GBDownload
APUS-OpenJev-v1-9B.Q4_K_M.ggufGGUFGGUF5.24 GBDownload
APUS-OpenJev-v1-9B.Q4_K_S.ggufGGUFGGUF4.98 GBDownload
APUS-OpenJev-v1-9B.Q5_K_M.ggufGGUFGGUF6.02 GBDownload
APUS-OpenJev-v1-9B.Q5_K_S.ggufGGUFGGUF5.87 GBDownload
APUS-OpenJev-v1-9B.Q6_K.ggufGGUFGGUF6.85 GBDownload

Model Details

Model IDprithivMLmods/APUS-OpenJev-v1-9B-GGUF
AuthorprithivMLmods
Pipelinetext-generation
Licenseapache-2.0
Base modelapus-ailab/APUS-OpenJev-v1-9B
Last modified2026-09-22T13:53:42.000Z

Model README

---

license: apache-2.0

base_model:

  • apus-ailab/APUS-OpenJev-v1-9B

tags:

  • text-generation-inference
  • llama-cpp
  • apus-openjev
  • decision-model
  • structured-output
  • bf16

language:

  • en
  • zh

pipeline_tag: text-generation

library_name: transformers

---

APUS-OpenJev-v1-9B-GGUF

> APUS-OpenJev-v1-9B is a Qwen3.5-9B-based decision model from APUS AI-LAB, designed for browser action selection, workflow routing, and natural-language principle judgments rather than open-ended text generation — this repository provides the 9B checkpoint-3000 merged BF16 weights, downloadable independently without a separate LoRA adapter. It scores dynamic candidates supplied per request and returns their preference distribution, reusing Qwen's language representations and vocabulary projection so application code can assemble decisions into structured workflow outputs; its native runtime supports two effort levels — low (16 layers) and high (32 layers, recommended for text generation). On the internal Frozen80 development panel (covering Browser, HelpSteer3, BoolQ, MNLI, and attribute-decision tasks), the merged model scores 68/80 (85.00%), though the authors note this is a reused engineering panel rather than an independent blind benchmark or end-to-end browser success rate, and that candidate probabilities express relative preference rather than calibrated correctness (with BF16 merging further shifting some probabilities). It's part of a three-size family (4B, 9B, 35B-A3B) hosted in separate repositories under a shared collection, with the 4B release instead selecting checkpoint-5949 (82.50% on the same panel), and is released under Apache 2.0 as a finetune of the Qwen3.5-9B base.

Model Files

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

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

| APUS-OpenJev-v1-9B.BF16.gguf | BF16 | 17.9 GB | Link | Full BF16 weights. Highest quality, largest file size. |

| APUS-OpenJev-v1-9B.Q3_K_L.gguf | Q3_K_L | 4.93 GB | Link | Lower quality but usable, good for low RAM availability. |

| APUS-OpenJev-v1-9B.Q3_K_M.gguf | Q3_K_M | 4.62 GB | Link | Low quality. |

| APUS-OpenJev-v1-9B.Q4_K_M.gguf | Q4_K_M | 5.63 GB | Link | Good quality, default size for most use cases, recommended. |

| APUS-OpenJev-v1-9B.Q4_K_S.gguf | Q4_K_S | 5.35 GB | Link | Slightly lower quality with more space savings, recommended. |

| APUS-OpenJev-v1-9B.Q5_K_M.gguf | Q5_K_M | 6.47 GB | Link | High quality, recommended. |

| APUS-OpenJev-v1-9B.Q5_K_S.gguf | Q5_K_S | 6.31 GB | Link | High quality, recommended. |

| APUS-OpenJev-v1-9B.Q6_K.gguf | Q6_K | 7.36 GB | Link | Very high quality, near perfect, recommended. |

llama.cpp

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

Run prithivMLmods/APUS-OpenJev-v1-9B-GGUF with guIDE

Download guIDE — the AI-native code editor with local LLM inference and 69 built-in tools.

Download guIDE → · Browse 524k+ models · Compare models

Source: Hugging Face · Compare models