tomvaillant/gemma4-12b-spotlight-orchestrator-v5-GGUF overview
Gemma 4 12B — Spotlight Orchestrator v5 GGUF Q4 K M Q4 K M quantization of the v5 Spotlight orchestrator — the servable artifact for the 12B local tier of Spot…
Runs locally from ~6.87 GB disk (8 GB VRAM class GPUs with llama.cpp / guIDE).
Repository Files & Downloads
| File | Type | Quantization | Size | Link |
|---|---|---|---|---|
| gemma-4-12b-spotlight-orchestrator-Q4_K_M.gguf | GGUF | Q4_K_M | 6.87 GB | Download |
Model Details
| Model ID | tomvaillant/gemma4-12b-spotlight-orchestrator-v5-GGUF |
|---|---|
| Author | tomvaillant |
| Pipeline | text-generation |
| License | gemma |
| Base model | unsloth/gemma-4-12b-it |
| Last modified | 2026-07-10T15:16:48.000Z |
Model README
---
base_model: unsloth/gemma-4-12b-it
pipeline_tag: text-generation
license: gemma
language:
- en
tags:
- gguf
- llama.cpp
- osint
- agent
- spotlight
---
Gemma-4 12B — Spotlight Orchestrator v5 (GGUF Q4_K_M)
Q4_K_M quantization of the v5 Spotlight orchestrator — the servable artifact
for the 12B local tier of
Spotlight. It is merged from the
with Unsloth's native merge path, coherence-checked, and converted with
llama.cpp.
Files
gemma-4-12b-spotlight-orchestrator-Q4_K_M.gguf— the single 7.381 GB,
text-only Q4_K_M deployment artifact. Vision weights are intentionally not
included.
Serving — the flags are load-bearing
llama-server -m gemma-4-12b-spotlight-orchestrator-Q4_K_M.gguf \
--port 8093 --host 127.0.0.1 \
--ctx-size 81920 --parallel 2 --no-cache-idle-slots \
--n-gpu-layers 999 --jinja --flash-attn on \
--cache-type-k q8_0 --cache-type-v q8_0 \
--reasoning-budget 400 \
--alias gemma-4-12b-spotlight-v5
These settings are part of the tested configuration:
--parallel 2 --ctx-size 81920gives each slot 40,960 tokens, matching the
tuning context and leaving enough room for a full investigation loop.
--no-cache-idle-slotsprevents slot save/restore failures during subagent
delegation.
--reasoning-budget 400prevents reasoning from consuming the response
budget before a tool call or gate presentation is emitted.
--jinjaenables tool calling; q8 KV and flash attention keep memory use
inside the local 48 GB target.
What it is trained to do
Drive Spotlight's brief → methodology → research → fact-check → report pipeline;
delegate constrained investigation and fact-check work; obey human gates; and
recover cleanly when deterministic validators reject structured inputs. The v5
dataset contains the report-execution recovery contexts that v4 fumbled, but the
production harness no longer asks any model to edit the 20 KB HTML template:
Spotlight renders all three report artifacts deterministically from validated
findings.json and fact-check.json.
Validation status
Released 2026-07-10 after the preserved v4 failure fixture passed the canonical
report finalizer: evidence-chain validation, deterministic Markdown/HTML/evidence
map rendering, report-gate validation, and byte-identical repeat rendering. The
same finalizer also passed the completed 26B case. A fresh full 12B E2E is the
post-release validation; report file construction is no longer part of that
model-capability bet.
Install
curl -fsSL https://spotlight.buriedsignals.com/install-spotlight.sh | bash
Direct GGUF download:
hf download tomvaillant/gemma4-12b-spotlight-orchestrator-v5-GGUF \
gemma-4-12b-spotlight-orchestrator-Q4_K_M.gguf
Limitations
The model does not replace source verification. Spotlight's deterministic
fact-check validator and report finalizer are required deployment components.
Tool use is tuned against Spotlight's harness schema and may not transfer to
other agent frameworks without adaptation. The Q4_K_M artifact is text-only;
use a separate vision-capable fact-check tier for scanned documents or imagery.
Run tomvaillant/gemma4-12b-spotlight-orchestrator-v5-GGUF with guIDE
Download guIDE — the AI-native code editor with local LLM inference and 69 built-in tools.
Source: Hugging Face · Compare models