Groq
4.4
Groq runs inference on its own hardware and sells the result as speed: the same open models, returning tokens faster than general-purpose GPU clouds. Where latency is the product — voice agents, interactive tools, anything a person waits for — that difference changes what is buildable.
- Commercial use OK
- Pricing
- 従量課金
- Free tier
- No
- Commercial use
- Permitted
- Japanese UI
- Not confirmed
- Enterprise contract
- Not confirmed
What it is good for
- Voice agents and other interactive latency-sensitive work
- Interfaces where the user watches the response appear
- High-volume classification where throughput is the constraint
- Prototyping an experience that feels instant
Strengths and trade-offs
Strengths
- Noticeably faster token generation than general-purpose clouds
- Usage-based pricing with no subscription
- OpenAI-compatible API, so integration is short
- Good fit for open models you already evaluated elsewhere
Trade-offs
- Model selection is narrower than general providers
- Frontier proprietary models are not available
- Capacity and rate limits need checking before you depend on it
Editors' review
Speed as the product, which matters more than it looks on a benchmark
Latency is usually treated as a nice-to-have, and in most applications it is. In a few — a phone agent, an interface the user watches — it is the entire experience, and the gap between fast and acceptable decides whether people use the thing.
Groq's position is narrow and clear: the same open models, served faster. That makes it a swap rather than a migration, since the API is OpenAI-compatible and the models are ones you can evaluate elsewhere first.
What it is not is a general provider. Frontier proprietary models are absent, and the catalogue is smaller. Use it where speed is the requirement and something else where capability is.
Verdict
The right choice when a human is waiting for the response. Not a general-purpose replacement.
Compiled from official documentation and public sources, with our own editorial judgement. We do not publish figures we cannot source.