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dennisonb/gemma-4-26b-a4b-it-au-v5-gguf overview

Agent University Gemma 4 specialist v5 — skill focused debug + tools, no memorization Trained purely on skills: real error→diagnosis→fix traces, implementation…

ggufloragemma-4code-specialistagent-universitybase_model:google/gemma-4-26B-A4B-itbase_model:adapter:google/gemma-4-26B-A4B-itlicense:apache-2.0endpoints_compatibleregion:us

Runs locally from ~25.02 GB disk (32 GB+ VRAM class GPUs with llama.cpp / guIDE).

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Model Details

Model IDdennisonb/gemma-4-26b-a4b-it-au-v5-gguf
Authordennisonb
Pipeline
Licenseapache-2.0
Base modelgoogle/gemma-4-26B-A4B-it
Last modified2026-07-05T16:54:18.000Z

Model README

---

license: apache-2.0

base_model: google/gemma-4-26B-A4B-it

tags:

  • lora
  • gemma-4
  • code-specialist
  • agent-university

---

Agent University Gemma-4 specialist v5 — skill-focused (debug + tools, no memorization)

Trained purely on skills: real error→diagnosis→fix traces, implementation tasks, and tool-grounded answers — exact facts are delegated to retrieval by design.

Benchmark (40 app-building tasks and 210 knowledge questions the models never saw during training, scored against real, tested reference implementations): 53.2% knowledge retention via tool use; 47.1% on build tasks; tool calibration retained (95–98% / 7.5%). Claude Sonnet 5 scored 31.5% on the same build tasks.

  • Base: google/gemma-4-26B-A4B-it (Apache-2.0, subject to Gemma Terms)
  • Training: LoRA SFT on the Agent University corpus (~90 live-tested curricula for AI/agent libraries and dev tools)
  • Format: Merged Q8_0 GGUF — runs directly with llama.cpp / LM Studio / Ollama. Raw adapter in the companion -adapter repo.

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