Category
AI Infrastructure
Serve models fast, without owning GPUs.
23 tools·16 with free plan·12 with free trial
Read the editor's roundup →Run and serve AI models — inference APIs, GPU hosting, and model deployment platforms.
23 tools reviewed16 with a free plan12 with a free trial22 with an API8 self-hostable4 paid-only
Top picks
01
Very fast LLM inference on custom LPU hardware.
Groq is the go-to when raw inference speed matters: agents, voice, and interactive chat feel noticeably snappier on its LPU hardware, and per-token prices are competitive. The trade-off is scope. You serve models from Groq's supported catalog rather than arbitrary custom weights, and the exact model lineup shifts over time. Corporate turbulence around the 2026 Nvidia deal and a down round is worth noting for those making long-term platform bets, though day-to-day service has stayed reliable. A strong default for latency-sensitive apps on popular open models.
freemium·$0.05 per 1M input tokens (Llama 3.1 8B)
02
Inference, fine-tuning, and GPU clusters for open models.
Together AI is a strong middle-ground AI cloud: cheaper than closed frontier APIs, broader than a pure inference endpoint, and able to scale from a serverless token call to reserved GPU clusters. It suits teams committed to open models that want both flexibility and the option to fine-tune and own weights. The caveats are a wide pricing surface (per-token vs per-GPU-hour vs fine-tuning) and the usual open-model reality that you are responsible for evaluating quality and safety. Good default for cost-conscious teams building on open models.
freemium·Per-token from ~$0.10 per 1M tokens; GPU clusters usage-based
03
Fast, production inference for open and custom models.
Fireworks AI targets teams past the prototype stage that need fast, reliable inference on open or custom models without running their own GPUs. Its strengths are optimized latency, custom model deployment, and production features like function calling and structured output. The catalog and OpenAI-compatible API make migration easy. The main caveat is that it is tuned for production usage and enterprise buyers, so hobbyists may prefer simpler free tiers, and per-model pricing varies enough that you should model costs for your specific workload before committing.
freemium·Per-token, varies by model; dedicated GPU usage-based
All AI Infrastructure
One API for hundreds of AI models across providers.
#llm-api#model-routing#aggregator#multi-provider 9 views
Serverless GPU runtime for AI inference, training, and sandboxes
#serverless-gpu#inference#model-training#open-source 1 views
Open-access AI cloud and decentralized GPU marketplace
#gpu-cloud#inference#open-models#decentralized
Small specialised on-device models for speech, text, and vision, one per task
#on-device models#edge ai#speech recognition#privacy
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Frequently asked questions
- What's the best ai infrastructure tool?
- Groq currently leads in community votes. Groq is the go-to when raw inference speed matters: agents, voice, and interactive chat feel noticeably snappier on its LPU hardware, and per-token prices are competitive. The trade-off is scope. You serve models from Groq's supported catalog rather than arbitrary custom weights, and the exact model lineup shifts over time. Corporate turbulence around the 2026 Nvidia deal and a down round is worth noting for those making long-term platform bets, though day-to-day service has stayed reliable. A strong default for latency-sensitive apps on popular open models.
- Are there free options?
- 16 tools in this category offer a free plan. Another 12 have a free trial.
- How do you rank these tools?
- Tools are ranked by a combination of community upvotes, editorial review, and feature breadth. Our editors review pricing and capabilities quarterly.
- Can I suggest a tool we're missing?
- Yes — submit it here. Our team reviews submissions weekly.