Together AI and Cohere serve fundamentally different segments of the AI platform market. Together AI excels as an open-source model marketplace with cost-effective serverless inference, while Cohere delivers purpose-built enterprise NLP with native retrieval and compliance features.
| Feature | Together AI | Cohere |
|---|---|---|
| Best For | Teams needing access to diverse open-source models with flexible serverless inference and dedicated GPU options | Enterprises requiring production-grade NLP with built-in retrieval, classification, and data privacy controls |
| Pricing Model | Serverless inference: from $0.10/M tokens (small models) to $2.50/M tokens (large models). Dedicated endpoints: from $0.80/GPU/hour (A100). Fine-tuning: from $3/M tokens. Free tier: $5 in credits. Pay-as-you-go with no minimum. | Free tier: rate-limited API access for prototyping. Production: Command R models from $0.15/M input tokens, $0.60/M output tokens. Embed models from $0.10/M tokens. Rerank from $1/1000 searches. Enterprise: custom pricing with data residency, fine-tuning, private deployment. |
| Model Selection | Extensive open-source model catalog including Llama, Mistral, and community fine-tunes with rapid new model additions | Proprietary Command R family optimized for enterprise tasks including generation, embeddings, and reranking |
| Deployment Options | Serverless inference endpoints and dedicated GPU clusters starting at $0.80/hour per A100 GPU | Cloud API, private cloud deployment, and on-premises options with data residency guarantees for compliance |
| Enterprise Features | Custom fine-tuning from $3/M tokens, dedicated GPU clusters for isolation, and pay-as-you-go billing | SOC 2 compliance, data residency controls, private deployments, custom fine-tuning, and dedicated support |
| Developer Experience | Simple REST API with OpenAI-compatible endpoints, Python SDK, and $5 free credits to start building | Well-documented API with specialized endpoints for RAG, classification, and embeddings plus Coral chat interface |
| Feature | Together AI | Cohere |
|---|---|---|
| Model Access & Inference | ||
| Language Model Inference | Serverless access to 100+ open-source models including Llama 3, Mistral, and Qwen families from $0.10/M tokens | Proprietary Command R and Command R+ models optimized for enterprise RAG and generation from $0.15/M input tokens |
| Embedding Models | Open-source embedding models available via serverless inference with support for multiple embedding architectures | Purpose-built Embed v3 models with multilingual support in 100+ languages at $0.10/M tokens |
| Model Fine-Tuning | Fine-tuning for open-source models starting at $3/M tokens with support for LoRA and full parameter tuning | Enterprise fine-tuning for Command R models with custom training data and private model deployment options |
| Retrieval & Search | ||
| Semantic Search | Embedding-based search supported through open-source models; users build their own retrieval pipeline | Native Embed + Rerank pipeline providing end-to-end semantic search at $1 per 1,000 rerank searches |
| RAG Support | RAG workflows built by combining open-source LLMs with external vector databases and retrieval frameworks | Built-in RAG with grounded generation, inline citations, and automatic document connector integrations |
| Reranking | Community reranking models available through the model catalog for custom reranking implementations | Dedicated Rerank endpoint returning relevance scores for search results at $1 per 1,000 searches |
| Infrastructure & Deployment | ||
| Serverless Inference | Auto-scaling serverless endpoints with pay-per-token pricing and no minimum commitment required | Managed API endpoints with rate-limited free tier and production pay-as-you-go access |
| Dedicated Compute | Dedicated GPU clusters with A100 GPUs from $0.80/hour providing guaranteed capacity and isolation | Private cloud deployments with dedicated infrastructure available under enterprise agreements |
| On-Premises Deployment | Not currently offered; platform operates as a cloud-only managed inference service | On-premises deployment available for enterprise customers requiring full data control and air-gapped environments |
| Developer Tools & Integration | ||
| API Compatibility | OpenAI-compatible API format allowing easy migration from OpenAI with minimal code changes | Proprietary REST API with Python, TypeScript, Java, and Go SDKs plus LangChain and LlamaIndex integrations |
| Playground & Testing | Interactive playground for testing 100+ models side-by-side with parameter tuning and prompt iteration | Coral chat playground and API dashboard for testing generation, embeddings, and classification endpoints |
| Monitoring & Observability | Usage dashboard with token consumption tracking and cost monitoring across all deployed models | Production dashboard with usage analytics, latency monitoring, and API key management controls |
| Enterprise & Compliance | ||
| Data Privacy | Standard cloud data processing with no training on customer data and secure API communication | Enterprise-grade data privacy with data residency controls, SOC 2 Type II certification, and GDPR compliance |
| Access Controls | API key-based authentication with team management features for organizing access across projects | Role-based access controls, SSO integration, and audit logging for enterprise governance requirements |
| SLA & Support | Community support and documentation with enterprise support available for dedicated GPU customers | Enterprise SLAs with dedicated support engineers, custom onboarding, and priority issue resolution |
Language Model Inference
Embedding Models
Model Fine-Tuning
Semantic Search
RAG Support
Reranking
Serverless Inference
Dedicated Compute
On-Premises Deployment
API Compatibility
Playground & Testing
Monitoring & Observability
Data Privacy
Access Controls
SLA & Support
Together AI and Cohere serve fundamentally different segments of the AI platform market. Together AI excels as an open-source model marketplace with cost-effective serverless inference, while Cohere delivers purpose-built enterprise NLP with native retrieval and compliance features.
Choose Together AI if:
Choose Together AI if your team prioritizes access to a broad range of open-source models and wants flexibility in model selection. Together AI's serverless inference starting at $0.10 per million tokens makes it highly cost-effective for experimentation and production workloads that benefit from the latest open-source innovations like Llama 3, Mistral, and community fine-tunes. The OpenAI-compatible API format simplifies migration, and dedicated GPU clusters at $0.80 per hour provide guaranteed capacity when you need consistent performance.
Choose Cohere if:
Choose Cohere if your organization needs production-grade enterprise NLP with built-in retrieval augmented generation, data privacy guarantees, and compliance certifications. Cohere's proprietary Command R models are specifically optimized for enterprise use cases like RAG with grounded citations, semantic search with reranking at $1 per 1,000 searches, and text classification. The platform's on-premises deployment options, SOC 2 compliance, and data residency controls make it suitable for regulated industries requiring strict data governance.
This verdict is based on general use cases. Your specific requirements, existing tech stack, and team expertise should guide your final decision.
Together AI's serverless inference ranges from $0.10 per million tokens for smaller models to $2.50 per million tokens for large models like Llama 3 70B. Cohere's Command R models cost $0.15 per million input tokens and $0.60 per million output tokens. For high-volume workloads using smaller models, Together AI can be significantly cheaper. However, Cohere's pricing includes built-in optimizations for enterprise features like grounded generation and citations that would require additional infrastructure on Together AI.
Cohere focuses exclusively on its proprietary Command R model family and does not host open-source models. Together AI specializes in open-source models and does not offer proprietary alternatives. If you need access to specific open-source architectures like Llama 3 or Mistral, Together AI is the clear choice. If you want Cohere's enterprise-optimized models with built-in RAG and classification, those are only available through the Cohere platform. Some teams use both platforms for different use cases.
Cohere offers a more integrated RAG experience with its built-in Embed models at $0.10 per million tokens, Rerank endpoint at $1 per 1,000 searches, and Command R's grounded generation that automatically produces inline citations. Together AI supports RAG workflows but requires combining separate components: an open-source LLM for generation, an embedding model for indexing, and external vector databases like Pinecone or Weaviate. Cohere's approach reduces development complexity, while Together AI provides more flexibility in choosing individual components.
Cohere is purpose-built for enterprise deployment with SOC 2 Type II certification, GDPR compliance, data residency controls allowing you to specify where your data is processed, and on-premises deployment options for air-gapped environments. Together AI provides standard cloud security practices and does not train on customer data, but currently lacks on-premises deployment and formal compliance certifications comparable to Cohere. For regulated industries like healthcare and finance that demand zero risk tolerance on data handling, Cohere's enterprise features provide significantly stronger governance capabilities.