Google Vertex AI
Status: ✅ Supported
Google Cloud Vertex AI provides access to Gemini models.
Supported Models
| Model ID | Name | Context |
|---|---|---|
deepseek-ai/deepseek-v3.1-maas | DeepSeek V3.1 | 163K |
deepseek-ai/deepseek-v3.2-maas | DeepSeek V3.2 | 163K |
zai-org/glm-4.7-maas | GLM-4.7 | 200K |
zai-org/glm-5-maas | GLM-5 | 202K |
openai/gpt-oss-120b-maas | GPT OSS 120B | 131K |
openai/gpt-oss-20b-maas | GPT OSS 20B | 131K |
gemini-2.0-flash | Gemini 2.0 Flash | 1M |
gemini-2.0-flash-lite | Gemini 2.0 Flash Lite | 1M |
gemini-2.5-flash | Gemini 2.5 Flash | 1M |
gemini-2.5-flash-lite | Gemini 2.5 Flash Lite | 1M |
gemini-2.5-flash-lite-preview-06-17 | Gemini 2.5 Flash Lite Preview 06-17 | 65K |
gemini-2.5-flash-lite-preview-09-2025 | Gemini 2.5 Flash Lite Preview 09-25 | 1M |
gemini-2.5-flash-preview-04-17 | Gemini 2.5 Flash Preview 04-17 | 1M |
gemini-2.5-flash-preview-05-20 | Gemini 2.5 Flash Preview 05-20 | 1M |
gemini-2.5-flash-preview-09-2025 | Gemini 2.5 Flash Preview 09-25 | 1M |
gemini-2.5-pro | Gemini 2.5 Pro | 1M |
gemini-2.5-pro-preview-05-06 | Gemini 2.5 Pro Preview 05-06 | 1M |
gemini-2.5-pro-preview-06-05 | Gemini 2.5 Pro Preview 06-05 | 1M |
gemini-3-flash-preview | Gemini 3 Flash Preview | 1M |
gemini-3-pro-preview | Gemini 3 Pro Preview | 1M |
gemini-3.1-pro-preview | Gemini 3.1 Pro Preview | 1M |
gemini-3.1-pro-preview-customtools | Gemini 3.1 Pro Preview Custom Tools | 1M |
gemini-embedding-001 | Gemini Embedding 001 | 2K |
gemini-flash-latest | Gemini Flash Latest | 1M |
gemini-flash-lite-latest | Gemini Flash-Lite Latest | 1M |
moonshotai/kimi-k2-thinking-maas | Kimi K2 Thinking | 262K |
meta/llama-3.3-70b-instruct-maas | Llama 3.3 70B Instruct | 128K |
meta/llama-4-maverick-17b-128e-instruct-maas | Llama 4 Maverick 17B 128E Instruct | 524K |
qwen/qwen3-235b-a22b-instruct-2507-maas | Qwen3 235B A22B Instruct | 262K |
Setup
1. Google Cloud Setup
- Create or select a Google Cloud project
- Enable the Vertex AI API:
gcloud services enable aiplatform.googleapis.com - Ensure billing is enabled
2. Authentication
Clawrium uses Application Default Credentials (ADC). Set up authentication:
# Install gcloud CLI if not already installed
# https://cloud.google.com/sdk/docs/install
# Authenticate
gcloud auth application-default login
Or use a service account:
# Create service account
gcloud iam service-accounts create clawrium-provider \
--display-name="Clawrium Provider"
# Grant Vertex AI User role
gcloud projects add-iam-policy-binding PROJECT_ID \
--member="serviceAccount:clawrium-provider@PROJECT_ID.iam.gserviceaccount.com" \
--role="roles/aiplatform.user"
# Create and download key
gcloud iam service-accounts keys create key.json \
--iam-account=clawrium-provider@PROJECT_ID.iam.gserviceaccount.com
# Set environment variable
export GOOGLE_APPLICATION_CREDENTIALS=/path/to/key.json
3. Add to Clawrium
clm provider add my-vertex --type vertex
Note: Vertex AI uses Google Cloud authentication, not an API key.
4. Select Model
Choose a default model during setup:
gemini-2.5-pro(best quality)gemini-2.5-flash(recommended balance)
Configuration
# View provider details
clm provider list
# Change default model
clm provider edit my-vertex --model gemini-2.5-flash
# Remove provider
clm provider remove my-vertex
Pricing
Vertex AI uses pay-per-use pricing. Check Vertex AI pricing for current rates.
Approximate costs:
- Gemini 2.5 Pro: ~$1.25/1M input tokens, ~$10/1M output tokens
- Gemini 2.5 Flash: ~$0.15/1M input tokens, ~$0.60/1M output tokens
Benefits
- Google Cloud integration: Works with GCP services
- Enterprise features: Fine-tuning, batch prediction
- Global infrastructure: Low latency worldwide
- Gemini models: Google's most capable models
Usage in Agents
During agent onboarding:
clm agent configure my-agent
# Select my-vertex when prompted for provider
Troubleshooting
"Permission denied"
- Verify Vertex AI API is enabled
- Check IAM permissions (needs
aiplatform.user) - Ensure billing is enabled
"Authentication failed"
- Run
gcloud auth application-default login - Check
GOOGLE_APPLICATION_CREDENTIALSis set correctly - Verify service account has proper roles
"Model not found"
- Check your region supports the model
- Verify the model name is correct
- Some models may be in preview/limited availability