Model Discovery

Umwelten provides comprehensive model discovery features to help you find and compare models across all supported providers (Google, Ollama, OpenRouter, LM Studio, GitHub Models).

Listing Models

Basic Model List

# List all available models
umwelten models 

# List with JSON output for programmatic use
umwelten models  --json

Filter by Provider

# Filter by specific provider
umwelten models --provider openrouter      # requires OPENROUTER_API_KEY
umwelten models  --provider ollama
umwelten models  --provider google         # GOOGLE_GENERATIVE_AI_API_KEY
umwelten models  --provider lmstudio
umwelten models  --provider github-models  # GITHUB_TOKEN

Filter by Cost

# Show only free models
umwelten models --free

# Sort by cost (ascending by default)
umwelten models --sort cost

Search Models

# Search for specific models
umwelten models --search "gpt-4"
umwelten models --search "gemini"
umwelten models --search "llama"

Sorting Options

# Sort by different fields
umwelten models --sort addedDate --desc
umwelten models --sort contextLength
umwelten models --sort cost
umwelten models --sort name

Model Information

Detailed Model Info

Get comprehensive information about a specific model:

# Basic model info (finds first match across all providers)
umwelten models --view info --id <model-id>

# Examples
umwelten models --view info --id openai/gpt-4o
umwelten models --view info --id gemini-2.0-flash
umwelten models --view info --id gemma3:12b

# Get info for a specific provider's version of a model
umwelten models --provider github-models --view info --id openai/gpt-4.1
umwelten models --provider openrouter --view info --id openai/gpt-4o
umwelten models --provider google --view info --id gemini-2.0-flash

Cost Analysis

View cost breakdown across all models:

# View all model costs
umwelten models costs

# Sort by different cost metrics
umwelten models costs --sort-by prompt
umwelten models costs --sort-by completion
umwelten models costs --sort-by total

The costs command shows:

• Model: Model identifier
• Provider: Which service hosts the model (ollama, openrouter, google, github-models, lmstudio)
• Prompt: Cost per 1M input tokens
• Completion: Cost per 1M output tokens
• Total: Combined cost per 1M tokens

Models are sorted by the specified metric (default: total cost).

Understanding the Output

Model List Table

Found 150+ models

┌───────────────────┬────────────┬─────────┬───────────────┬────────────────┬────────┐
│ ID                │ Provider   │ Context │ Input Cost/1M │ Output Cost/1M │ Added  │
├───────────────────┼────────────┼─────────┼───────────────┼────────────────┼────────┤
│ openai/gpt-4o     │ openrouter │ 128K    │ $2.5000       │ $10.0000       │ 5/12/24│
│ openai/gpt-4o-mini│ openrouter │ 128K    │ $0.1500       │ $0.6000        │ 7/17/24│
│ gemini-2.0-flash  │ google     │ 1M      │ $0.0750       │ $0.3000        │ 12/11/24│
│ gemma3:12b        │ ollama     │ 8K      │ Free          │ Free           │ 7/15/25│
└───────────────────┴────────────┴─────────┴───────────────┴────────────────┴────────┘

Key Information

• ID: Model identifier used in commands
• Provider: Which service hosts the model
• Context: Maximum context window (8K, 128K, 1M, etc.)
• Input/Output Cost: Cost per 1 million tokens
• Added: When the model was added to our database

Model Selection Tips

For Development & Testing

• Free models: Ollama models (gemma3:12b, llama3.2:latest)
• Fast & cheap: Google Gemini 2.0 Flash, OpenAI GPT-4o-mini

For Production

• High quality: OpenAI GPT-4o, Google Gemini 2.5 Pro
• Cost-effective: Google Gemini 2.0 Flash, OpenAI GPT-4o-mini

For Specialized Tasks

• Vision: Google Gemini 2.0 Flash, Ollama qwen2.5vl:latest
• Code: Ollama codestral:latest, OpenAI GPT-4o
• Long context: Google Gemini models (up to 2M tokens)

Provider-Specific Notes

Ollama

• Requires local Ollama server running
• Models must be pulled locally first: ollama pull model-name
• Free to use (only compute costs)
• Best for privacy and local development

Google Gemini

• Excellent vision capabilities
• Very large context windows (up to 2M tokens)
• Competitive pricing
• Fast inference

OpenRouter

• Access to many different model providers
• Pay-per-use pricing
• Wide variety of models and capabilities
• Good for testing different providers

LM Studio

• Local model hosting
• No API key required
• Models must be downloaded and loaded in LM Studio
• Full privacy and control

GitHub Models

• Free access during preview period
• Requires GitHub Personal Access Token with models scope
• Access to models from OpenAI, Meta, DeepSeek, and other providers
• OpenAI-compatible API interface

Next Steps

Once you've discovered suitable models:

• Run basic prompts to test functionality
• Start interactive chat for extended conversations
• Start model evaluation for systematic comparison
• Use cost analysis to optimize spending