LLM Provider Ecosystem¶
Claif Knollm supports 40+ LLM providers, giving you unprecedented choice and flexibility in your AI applications. This comprehensive guide covers everything from premium services to free alternatives.
Provider Categories¶
-
:material-crown:{ .lg .middle } Premium Providers
High-quality, cutting-edge models from industry leaders like OpenAI, Anthropic, and Google.
-
:material-flash:{ .lg .middle } Fast & Affordable
Ultra-fast inference at budget-friendly prices from Groq, Cerebras, and DeepSeek.
-
:material-open-source-initiative:{ .lg .middle } Open Source
Community-driven models and free hosting from Hugging Face, Together AI, and Replicate.
-
:material-tools:{ .lg .middle } Specialized
Domain-specific providers for enterprise, research, and niche applications.
Provider Overview¶
Premium Tier (Enterprise-Grade)¶
The highest quality models with the best capabilities:
Provider | Models | Specialty | Avg Cost/1K | Context |
---|---|---|---|---|
OpenAI | 25+ | GPT-4, o1, DALL-E | $0.015 | 128K |
Anthropic | 12+ | Claude 3.5, Constitutional AI | $0.015 | 200K |
15+ | Gemini 1.5, Gemma | $0.001 | 2M | |
Mistral | 12+ | European AI, Code | $0.007 | 32K |
Fast & Budget Tier¶
Optimized for speed and cost efficiency:
Provider | Models | Specialty | Avg Cost/1K | Speed |
---|---|---|---|---|
Groq | 20+ | Ultra-fast inference | $0.0002 | 500+ tok/s |
Cerebras | 8+ | High-speed processing | $0.0006 | 300+ tok/s |
DeepSeek | 15+ | Code generation | $0.0014 | 200+ tok/s |
Together AI | 50+ | Open model hosting | $0.0008 | 150+ tok/s |
Open Source & Free Tier¶
Community models and free access:
Provider | Models | Specialty | Cost | Access |
---|---|---|---|---|
Hugging Face | 100+ | Open models | Free* | API + Transformers |
Replicate | 80+ | Community models | Pay-per-use | Web + API |
Ollama | 50+ | Local inference | Free | Local only |
HuggingChat | 20+ | Chat interface | Free | Web + API |
*Free tier with limits, paid plans available.
Key Provider Features¶
Universal Coverage¶
Knollm provides unified access to providers offering:
- Text Generation - All providers
- Chat Completion - 38 providers
- Function Calling - 25 providers
- Vision/Multimodal - 18 providers
- Code Generation - 30 providers
- Embeddings - 22 providers
- Image Generation - 12 providers
Intelligent Routing¶
Automatic provider selection based on:
graph TD
A[Request] --> B{Routing Strategy}
B -->|Cost Optimized| C[Find Cheapest]
B -->|Quality Optimized| D[Find Best Model]
B -->|Speed Optimized| E[Find Fastest]
B -->|Balanced| F[Optimize All Factors]
C --> G[Provider Selection]
D --> G
E --> G
F --> G
G --> H{Primary Available?}
H -->|Yes| I[Use Primary]
H -->|No| J[Try Fallback]
J --> K{Fallback Available?}
K -->|Yes| I
K -->|No| L[Return Error]
Real-Time Failover¶
Built-in redundancy ensures reliability:
- Health Monitoring - Continuous provider health checks
- Automatic Failover - Seamless switching to backup providers
- Load Balancing - Distribute requests across healthy providers
- Circuit Breakers - Temporary exclusion of failing providers
Provider Selection Guide¶
Choose by Use Case¶
Recommended: Groq, DeepSeek, Hugging Face
from claif_knollm import KnollmClient, RoutingStrategy
client = KnollmClient(
routing_strategy=RoutingStrategy.COST_OPTIMIZED,
fallback_providers=["groq", "deepseek", "huggingface"]
)
Why: Minimal costs, fast iteration, good for experimentation.
Recommended: OpenAI, Anthropic, Google
client = KnollmClient(
routing_strategy=RoutingStrategy.QUALITY_OPTIMIZED,
fallback_providers=["openai", "anthropic", "google"]
)
Why: Highest quality, reliable service, comprehensive capabilities.
Recommended: Groq, Cerebras, Together AI
client = KnollmClient(
routing_strategy=RoutingStrategy.SPEED_OPTIMIZED,
fallback_providers=["groq", "cerebras", "together"]
)
Why: Ultra-fast processing, cost-effective at scale.
Code: DeepSeek, CodeLlama models Vision: GPT-4 Vision, Claude 3.5 Sonnet Reasoning: o1 models, Claude 3.5 Sonnet Long Context: Google Gemini (2M tokens), Claude (200K tokens)
Choose by Budget¶
Budget Level | Recommended Providers | Average Cost/1K Tokens |
---|---|---|
Free | Hugging Face, Ollama | $0.0000 |
Budget (\(0-\)10/month) | Groq, DeepSeek, Together | \(0.0002-\)0.0008 |
Standard (\(10-\)100/month) | Mistral, Cohere, AI21 | \(0.001-\)0.007 |
Premium ($100+/month) | OpenAI, Anthropic, Google | \(0.003-\)0.015 |
Getting Started with Providers¶
1. Set Up API Keys¶
Configure the providers you want to use:
# Premium providers
export OPENAI_API_KEY="your-openai-key"
export ANTHROPIC_API_KEY="your-anthropic-key"
export GOOGLE_API_KEY="your-google-key"
# Budget providers
export GROQ_API_KEY="your-groq-key"
export DEEPSEEK_API_KEY="your-deepseek-key"
export TOGETHER_API_KEY="your-together-key"
2. Test Provider Connectivity¶
# Test all configured providers
knollm providers test
# Test specific providers
knollm providers test openai anthropic groq
# Check provider status
knollm providers status
3. Choose Your Strategy¶
from claif_knollm import KnollmClient, RoutingStrategy
# Let Knollm choose the best provider automatically
client = KnollmClient(
routing_strategy=RoutingStrategy.BALANCED,
fallback_providers=["openai", "groq", "deepseek"]
)
# Make a request - provider chosen automatically
response = await client.create_completion(
messages=[{"role": "user", "content": "Hello!"}]
)
print(f"Response from: {response.provider}")
Provider Comparison Tools¶
Use Knollm's built-in tools to compare providers:
CLI Comparison¶
# Compare providers by capability
knollm providers compare openai anthropic google --capability vision
# Compare by cost
knollm providers compare groq deepseek together --sort-by cost
# Detailed comparison table
knollm providers list --format detailed --tier premium
Programmatic Comparison¶
from claif_knollm import ProviderRegistry
registry = ProviderRegistry()
# Get providers by tier
premium_providers = registry.get_providers_by_tier("premium")
budget_providers = registry.get_providers_by_tier("budget")
# Compare specific providers
comparison = registry.compare_providers(
["openai", "anthropic", "groq"],
criteria=["cost", "speed", "quality"]
)
for provider, scores in comparison.items():
print(f"{provider}: {scores}")
What's Next?¶
Dive deeper into the provider ecosystem:
- Provider Catalog → - Detailed information on all providers
- Provider Comparison → - Side-by-side feature comparison
- Integration Guide → - How to integrate specific providers
- Cost Optimization → - Minimize your provider costs
💡 Pro Tips
- Start with 2-3 providers from different tiers for redundancy
- Use cost-optimized routing for development, quality-optimized for production
- Monitor provider performance with
knollm providers stats
- Set budget limits to avoid unexpected costs from premium providers