THE COMPARISON / A CLOSER LOOK
Cloudflare Workers AI vs Together AI
Compare the listed plans, useful capabilities, and practical tradeoffs.
Prices and features reflect editorial records. Check vendor terms before you buy; documentary checks do not imply hands-on testing.
Cloudflare Workers AI
AI Model APIs
Cloudflare Workers AI runs 50+ open-source models (Llama 3.1/3.2, Mistral, Whisper, embeddings, vision) on serverless GPUs at the edge for $0.011 per 1,000…
SOURCE-CHECK COVERAGE
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Starting Price
FreeTogether AI
🔴DeveloperLLM Infrastructure
GPU cloud and inference platform for open-source LLMs — fast, low-cost APIs for Llama, DeepSeek, Qwen, Mistral, plus fine-tuning and dedicated endpoints.
SOURCE-CHECK COVERAGE
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Starting Price
$0.02/1M tokensFeature Comparison
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Cloudflare Workers AI - Pros & Cons
Pros
- ✓Among the cheapest paths to production Llama inference at $0.011 per 1K Neurons with 10K free per day
- ✓Co-locates with Workers, Pages, and Vectorize for single-digit-millisecond RAG round trips on the edge
- ✓OpenAI-compatible endpoints mean existing OpenAI SDK code drops in with one URL change
Cons
- ✗Catalog is open-source-only — no GPT-5 or Claude (use AI Gateway or OpenRouter for those)
- ✗Throughput trails Groq on tokens-per-second for the largest Llama models
- ✗Vision and image generation model coverage is narrower than Replicate
Together AI - Pros & Cons
Pros
- ✓Cheaper per token than closed-model APIs for equivalent tasks — Llama 3.3 70B at ~$0.88/M is a real cost delta
- ✓Broad catalog covers most open models teams actually consider (Llama, DeepSeek, Qwen, Mistral, Kimi)
- ✓Three deployment tiers (serverless, dedicated, cluster) let you graduate without moving off the platform
- ✓Full-parameter and LoRA fine-tuning available with your dataset — a rare combination at this price
- ✓HIPAA-eligible and SOC 2 Type II environments make enterprise deals possible
Cons
- ✗Frontier reasoning still lags Claude, GPT, and Gemini for the hardest tasks; open models close but rarely lead
- ✗Serverless cold starts and shared-tenant latency vary — high-QPS production usually needs dedicated endpoints
- ✗Pricing per model shifts frequently as new SKUs launch; long-term budgeting requires occasional re-costing
- ✗Dedicated endpoints and clusters require some capacity planning — not fire-and-forget like serverless
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