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AI Tool Comparison
Langfuse vs Together AI
A side-by-side breakdown to help you pick the right tool for your workflow.
Langfuse
Trace and score LLM application runs so teams can debug agent behavior and track cost per user or session.
Developer Tools
freemium
Together AI
Run, fine-tune, and scale open-source models — start on cheap shared inference and graduate to dedicated GPUs (including on-demand B200s) as traffic grows.
Developer Tools
freemium
Bottom Line
Langfuse edges ahead on rating (4.7 vs 4.5), but the right pick still comes down to which workflow you're running.
Choose Langfuse if…
LLM Observability
Choose Together AI if…
Developer Tools
| Attribute | Langfuse | Together AI |
|---|---|---|
| Category | Developer Tools | Developer Tools |
| Pricing | freemium | freemium |
| Pricing Detail | Free (50K units) / $29/mo Core / $199/mo Pro | Pay-as-you-go from $1.04/M tokens / dedicated GPUs from $6.49/hr |
| Rating |
Key Features
Langfuse
- Full LLM call tracing
- Prompt version management
- User session tracking
- Cost and latency analytics
- Evaluation datasets
- Self-hostable
Together AI
- Inference for 200+ open models
- Fine-tuning and training
- OpenAI-compatible API
- Dedicated endpoints
Pros
Langfuse
- •One of the best open-source options in LLM observability
- •Works with any LLM provider
- •Eval framework helps catch quality regressions early
Together AI
- •Broad open-model catalog
- •Scales for production
- •Competitive pricing
Cons
Langfuse
- Setup requires SDK integration in your codebase
- Dashboard can feel complex for simple use cases
Together AI
- Usage costs add up
- Less consumer-facing