Supported self-hosted models and hardware requirements
DETAILS: Tier: Ultimate with GitLab Duo Enterprise - Start a trial Offering: Self-managed Status: Beta
- Introduced in GitLab 17.1 with a flag named
ai_custom_model. Disabled by default.- Enabled on self-managed in GitLab 17.6.
- Changed to require GitLab Duo add-on in GitLab 17.6 and later.
The following table shows the supported models along with their specific features and hardware requirements to help you select the model that best fits your infrastructure needs for optimal performance.
Approved LLMs
Install one of the following GitLab-approved LLM models:
| Model family | Model | Code completion | Code generation | GitLab Duo Chat |
|---|---|---|---|---|
| Mistral Codestral | Codestral 22B | {check-circle} Yes | {check-circle} Yes | {dotted-circle} No |
| Mistral | Mistral 7B | {check-circle} Yes | {dotted-circle} No | {dotted-circle} No |
| Mistral | Mistral 7B-it | {check-circle} Yes | {check-circle} Yes | {check-circle} Yes |
| Mistral | Mixtral 8x7B-it | {check-circle} Yes | {check-circle} Yes | {check-circle} Yes |
| Mistral | Mixtral 8x22B-it | {check-circle} Yes | {check-circle} Yes | {check-circle} Yes |
| Claude 3 | Claude 3.5 Sonnet | {check-circle} Yes | {check-circle} Yes | {check-circle} Yes |
| GPT | GPT-3.5-Turbo | {check-circle} Yes | {check-circle} Yes | {dotted-circle} No |
| GPT | GPT-4 Turbo | {check-circle} Yes | {check-circle} Yes | {dotted-circle} No |
| GPT | GPT-4o | {check-circle} Yes | {check-circle} Yes | {dotted-circle} No |
| GPT | GPT-4o-mini | {check-circle} Yes | {check-circle} Yes | {dotted-circle} No |
The following models are under evaluation, and support is limited:
| Model family | Model | Code completion | Code generation | GitLab Duo Chat |
|---|---|---|---|---|
| CodeGemma | CodeGemma 2b | {check-circle} Yes | {dotted-circle} No | {dotted-circle} No |
| CodeGemma | CodeGemma 7b-it | {dotted-circle} No | {check-circle} Yes | {dotted-circle} No |
| CodeGemma | CodeGemma 7b-code | {check-circle} Yes | {dotted-circle} No | {dotted-circle} No |
| Code Llama | Code-Llama 13b-code | {check-circle} Yes | {dotted-circle} No | {dotted-circle} No |
| Code Llama | Code-Llama 13b | {dotted-circle} No | {check-circle} Yes | {dotted-circle} No |
| DeepSeek Coder | DeepSeek Coder 33b Instruct | {check-circle} Yes | {check-circle} Yes | {dotted-circle} No |
| DeepSeek Coder | DeepSeek Coder 33b Base | {check-circle} Yes | {dotted-circle} No | {dotted-circle} No |
Hardware Requirements
For optimal performance, the following hardware specifications are recommended as baselines for hosting these models. Hosting requirements may vary depending model to model, so we recommend checking model vendor documentation as well:
- CPU: Minimum 8 cores (16 threads recommended).
- RAM: At least 32 GB (64 GB or more recommended for larger models).
-
GPU:
- Minimum: 2x NVIDIA A100 or equivalent for optimal inference performance.
- Note: For running Mixtral 8x22B and Mixtral 8x22B-it, it is recommended to use 8x NVIDIA A100 GPUs.
- Storage: SSD with sufficient space for model weights and data.