Glossary
Terms & definitions
Plain-language definitions for the metrics and categories used across the directory.
Metrics & concepts
- Inference
- Running a trained model to produce output (tokens) from a prompt. Inference providers sell access to this compute, usually priced per token or per GPU-second.
- Token
- The unit a model reads and writes — roughly 0.75 words in English. Pricing and throughput are quoted per token or per million tokens (1M).
- Blended $/1M
- A single comparison price: the mean of input and output cost per million tokens for a provider's reference model. A rough anchor, not a bill estimate.
- Input vs. output price
- Most providers charge separately for prompt (input) tokens and generated (output) tokens; output is usually more expensive.
- TTFT (time-to-first-token)
- Milliseconds from sending a request to receiving the first output token — the felt "responsiveness." Lower is better.
- Throughput (tok/s)
- Sustained output tokens generated per second once streaming begins. Higher means faster completions. Independent of TTFT.
- Uptime %
- Share of time the API is available. Reference figures here are indicative, not contractual SLA numbers.
- OpenAI-compatible API
- The provider implements the OpenAI Chat Completions request/response shape, so code written for the OpenAI SDK works by changing the base URL and key.
- Open weights
- Models whose parameters are publicly downloadable (e.g. Llama, Mistral, Qwen). Many providers host these; some also let you self-host.
- Proprietary model
- A closed model available only through its owner's API (e.g. GPT, Claude, Gemini). No self-hosting path.
- Reputation index
- Tokenmeter's editorial 0–100 composite of public signals about a provider. Not a first-party metric and not audited — see Methodology.
- Confidence level
- How much to trust a figure: high (confirmed against public docs on the review date), medium (public but not re-confirmed), or seed (illustrative, pending verification).
Provider categories
- Frontier lab
- A company training its own frontier models and serving them through a first-party API (e.g. OpenAI, Anthropic, Mistral).
- Hyperscaler
- A major cloud platform offering inference alongside the rest of its cloud stack, with broad compliance and global regions.
- Aggregator
- A platform hosting many open models behind one API, competing on catalog breadth and per-token price.
- Router
- A service that forwards each request to an upstream provider, giving one API and one bill across many providers and models.
- Specialist hardware
- Providers running custom silicon (LPUs, wafer-scale engines, RDUs) to push throughput and latency well beyond commodity GPUs.
- GPU cloud
- Infrastructure-first platforms offering dedicated GPUs and serverless runtimes; you often deploy or manage the serving layer yourself.
- Specialist app
- An API tuned for a specific job (e.g. search-grounded answers) rather than general-purpose token serving.
Categories in the current dataset: Aggregator · Frontier lab · GPU cloud · Hyperscaler · Router · Specialist app · Specialist hardware · Subscription (flat-rate).