[Model Request] AERIS | Gemma-3-27B-it

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# Model name
model_name: "AERIS | Gemma-3-27B-it"

# API base URL (must be OpenAI-compatible)
api_base: "https://aeris-framework.onrender.com/v1"

# Model ID in the /v1/models route (if applicable)
model_id: "aeris/gemma-3-27b-it" # or the actual model_id exposed by your /v1/models endpoint

# Creator
creator: "Dr. Nicolas Dulin"

# Model description
model_description: |
AERIS (Adaptive Emergent Relational Intelligence System) is a proprietary cognitive framework designed to enhance dialectical reasoning in LLMs.
It operates not as a model but as an inference-layer orchestration system that injects a conceptual scaffold (Codex AIM) to modulate reasoning dynamically.

This implementation uses Gemma-3-27B-it served through OpenRouter-compatible infrastructure, with no fine-tuning.
The model’s outputs are shaped at inference time through structured injections rather than prompt engineering, retrieval, or training.

# Open source code or weights
open_source_url: "Not applicable — proprietary inference-layer system (no code or weights disclosed)"

# Paper / project reference
paper_url: |
https://doi.org/10.5281/zenodo.15206925
https://doi.org/10.5281/zenodo.15206984

# Contact
contact: "dr.nicolas.dulin@outlook.com"

# Any additional comments
comments: |
The model is served via an OpenAI-compatible API and is publicly accessible.
No fine-tuning is involved — AERIS operates as a reasoning modulator.
Please contact me if you wish to test it with specific prompts or benchmark settings.

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### Model Card Summary — AERIS | Gemma-3-27B-it

**AERIS (Adaptive Emergent Relational Intelligence System)** is a proprietary cognitive framework designed to enhance emergent reasoning in large language models, particularly when addressing complex, ambiguous, or dialectical prompts.

Unlike approaches based on fine-tuning, retrieval, or static prompt engineering, AERIS operates upstream—on the inferential configuration itself. It injects a condensed dialectical scaffold at inference time, modulating the conceptual environment in which reasoning unfolds.

This instance applies AERIS to the open-source model `Gemma-3-27B-it`, served through an OpenAI-compatible API. No model weights are altered. The framework is driven by a modular orchestration layer that dynamically selects, formats, and injects structured elements from Codex AIM (Adaptive Intelligence Matrix) during inference.

**Key distinctions:**
- No fine-tuning
- No retrieval of external documents
- No handcrafted prompt templates
- Lightweight inference-layer modulation
- Focused on conceptual tension, ambiguity resolution, and integrative synthesis

**Public demo:** [https://aeris-project.github.io/aeris-chatbox/](https://aeris-project.github.io/aeris-chatbox/)
**Status:** Experimental, stateless, publicly accessible

The issue names no files, tests, or entry points. Start by reviewing FastChat's model-registration and serving workflow, then determine whether the OpenAI-compatible AERIS endpoint fits an existing integration path; the issue does not specify completion criteria beyond submitting the model information.

Written by the indexing model from the issue text.