LLMs in Artemis
Artemis supports a set of built-in LLM providers out of the box. You can also bring your own LLM by configuring a custom provider profile — see Adding a custom LLM below.
OpenAI
| LLM | Description | Cloud Provider |
|---|---|---|
| GPT-5.6 Sol | High-capability GPT-5.6 variant optimized for reasoning tasks. | OpenAI |
| GPT-5.6 Terra | GPT-5.6 variant with broad knowledge and strong code generation. | OpenAI |
| GPT-5.6 Luna | Lightweight GPT-5.6 variant balancing speed and quality. | OpenAI |
| GPT-5.5 | Flagship GPT-5.5 model with advanced reasoning and creativity. | OpenAI |
| GPT-5.4 Mini | Compact GPT-5.4 variant optimized for speed and cost-efficiency. | OpenAI |
| GPT-5.4 Nano | Ultra-lightweight GPT-5.4 variant for fast, low-cost inference. | OpenAI |
Anthropic (Claude)
| LLM | Description | Cloud Provider |
|---|---|---|
| Claude Sonnet 5 | Mid-tier Claude 5 model with balanced speed and intelligence. | Anthropic |
| Claude Opus 4.8 | High-performance Claude model with strong reasoning capabilities. | Anthropic |
Google (Gemini)
| LLM | Description | Cloud Provider |
|---|---|---|
| Gemini 3.1 Pro Preview | Google's latest high-end multimodal model, preview release. | Google Vertex AI |
Z.ai
| LLM | Description | Cloud Provider |
|---|---|---|
| GLM 5.2 | High-performance model from Z.ai with strong multilingual support. | Z.ai |
Adding a custom LLM
Artemis supports bringing your own LLM provider. Configuration is done in the Artemis UI under Settings → Models → Profiles — no deployment config changes are needed.
Step 1 — Create a provider profile
Go to Settings → Models → Profiles and create a new profile for your LLM provider. You will need the provider's API endpoint and credentials (API key or equivalent).
Step 2 — Add models to the profile
Within the profile, add the specific models you want to make available. Each model entry maps a name to the provider's model identifier.
Step 3 — Set token costs
For each model, fill in the input and output token costs. This is required for per-user cost tracking to work correctly — profiles with missing costs will not report accurate usage.
Step 4 — Select models under Presets
Go to Settings → Models → Presets and select which models from your profile should be active. Presets control which models are available for each task type (chat, coding, scoring, etc.) across the platform.
As of v3.0.0, LLM configuration has moved entirely to the UI. It is no longer part of the deployment config file.