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Together Inference
NewVerified
Fast, scalable AI inference platform for open-source models
Overview
Infrastructure platform enabling fast inference of various open-source LLMs with optimized performance and low latency
Pros
- Fast inference speeds
- Wide model selection
- Competitive pricing
- Good documentation
✕ Cons
- Requires technical setup
- Less prominent than major providers
Key Features
Multiple open-source model access
Batch processing
Real-time inference
Fine-tuning capabilities
Use Cases
Cost-effective deploymentOpen-source model testingHigh-volume inferenceCustom model fine-tuning
Best For
Machine Learning EngineersBackend DevelopersStartups & Indie HackersAI Application BuildersData Scientists
Frequently Asked Questions
What is the pricing model for Together Inference?▾
Together Inference uses pay-as-you-go pricing based on tokens consumed, with competitive rates compared to other inference providers. Pricing varies by model and inference type (real-time vs. batch).
How steep is the learning curve for getting started?▾
Setup is straightforward with good documentation and a simple API. Developers familiar with REST APIs or Python SDKs can integrate it within hours.
What integrations and APIs does Together Inference offer?▾
It provides REST APIs, Python and JavaScript SDKs, and supports integration with popular frameworks. The platform also offers batch processing APIs for large-scale inference jobs.
What are the main limitations of Together Inference?▾
The platform is limited to open-source models only, which may not include proprietary models like GPT-4. Custom model deployment options are more limited compared to full ML platforms.
What is Together Inference best used for?▾
It's ideal for projects requiring fast, cost-effective inference with open-source models, such as building applications with Llama, Mistral, or other community models, and handling batch processing workloads.
Pricing Plans
Serverless InferenceMost Popular
Custom
- Pay-per-use pricing for API calls
- High-performance inference as APIs
- Support for chat, vision, audio, and embeddings
- No upfront commitment required
Batch Inference
Custom
- 50% lower cost for most models
- Process billions of tokens
- Optimized for non-real-time workloads
- Cost-effective for large-scale processing
Dedicated Model Inference
Custom
- Custom hardware allocation
- Guaranteed performance at scale
- Dedicated endpoints
- Lower latency for production workloads
Enterprise
Custom
- GPU clusters at scale
- Custom infrastructure at frontier scale
- AI Factory for bespoke deployments
- Dedicated support and SLAs
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