ModelForge
Hire-facing control surface for SLMs, PEFT, CUDA vLLM, and LLMOps. Agents decide what to do — ModelForge decides which weights, where they run, and how we prove it.
30-second CAIO rebuttal
I am not agents-only. Agents are how work gets done; the model plane is how I decide buy vs RAG vs PEFT vs self-host. ModelForge is the control UI — DomainForge trains adapters, CUDA vLLM serves them, SLM bake-off proves when small models win, and the LLM gateway enforces + records.
Buy · RAG · PEFT · self-host
Buy API
Long-context reasoning, data class allows cloud, time-to-value beats unit cost.
RAG
Facts change often; citations required; PEFT would bake stale knowledge.
PEFT (QLoRA/DPO)
Stable schema/behavior; eval Δ justifies adapter ops (DomainForge → receipt).
Self-host SLM / vLLM
Privacy, latency, or $ at volume wins bake-off; CUDA metrics on Serve receipt.
Receipts
Published artifacts are clickable. Smoke ≠ GPU. Placeholders mean CUDA host still required (RunPod) — posture stays honest.
| Kind | Title | Status | Summary | Artifact |
|---|
CUDA receipts — operator unblock
This demo host has no NVIDIA GPU. Phases 2–3 flip to ready only after RunPod (or equivalent) produces peft_gpu.json + vllm_cuda.json with cuda=true. Do not mint those files on CPU.
export GPU_SKU="1x A100-40GB" HF_TOKEN=... bash scripts/one_shot_gpu_receipts.sh # → docs/receipts/peft_gpu.json + vllm_cuda.json # then: commit, push, vercel --prod
FinOps bridge
Model choice without metering is incomplete. Bake-off cost narrative lands in the SLM memo; shared budgets/breach signals live in agent-finops (ADR-028/029 gateway records tokens for attribution).