Cloudflare Workers AI vs Together AI
Detailed side-by-side comparison to help you choose the right tool
Cloudflare Workers AI
🔴DeveloperAI Model APIs
Run AI models on Cloudflare's global edge network with 50+ open-source models for serverless AI inference at scale.
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Starting Price
FreeTogether AI
🔴DeveloperAI Model Hosting & Inference
AI-native cloud for inference, fine-tuning, and dedicated GPU clusters, offering 200+ open-source and frontier-class models behind an OpenAI-compatible API plus reserved H100/H200/B200 capacity.
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Starting Price
$0.02/1M tokensFeature Comparison
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Cloudflare Workers AI - Pros & Cons
Pros
- ✓Globally distributed inference on Cloudflare's edge network reduces latency for end users compared to single-region API providers
- ✓Tight integration with Workers, Vectorize, R2, D1, and AI Gateway makes it easy to assemble full RAG and agent stacks without leaving the platform
- ✓Generous free tier (10,000 neurons/day) and unified neuron-based pricing across 50+ models simplifies cost forecasting versus per-token billing per model
- ✓Supports function calling, JSON mode, LoRA fine-tunes, and BYOM, giving production teams real customization options on open-weight models
- ✓Bindings from Workers eliminate API key management and cold starts when calling AI from edge functions
- ✓AI Gateway provides built-in caching, rate limiting, retries, and unified analytics that work for both Workers AI and third-party providers like OpenAI
Cons
- ✗Catalog is limited to open-source and Cloudflare-curated models — no GPT-4, Claude, or Gemini frontier models are available natively
- ✗Per-model availability and feature support (streaming, function calling, context window) is uneven and changes as models are deprecated or added
- ✗Larger models can have higher per-request latency or queueing under load compared to dedicated GPU providers like Together AI or Fireworks
- ✗Neuron-based pricing is opaque relative to standard input/output token pricing, making direct cost comparisons against OpenAI or Anthropic harder
- ✗Best value is realized only when you commit to the broader Cloudflare ecosystem; using Workers AI alone forfeits much of its differentiation
Together AI - Pros & Cons
Pros
- ✓Breadth of open-weight model catalog (200+) with one OpenAI-compatible API
- ✓One account spans serverless, dedicated endpoints, fine-tuning, and reserved GPU capacity
- ✓Transparent per-token pricing — easy to model unit economics against closed providers
- ✓InfiniBand-backed GPU Clusters are credible for real training, not just inference
Cons
- ✗Frontier-class reasoning still lags closed models on the hardest benchmarks
- ✗Fastest single-model latency is sometimes beaten by Groq or Cerebras
- ✗Many model variants means model selection itself becomes a project
- ✗Dedicated endpoint cost calculations require attention to GPU type and utilization
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