# engy

engy sells inference on Liquid Inference. A buyer names one of its models as engy/\<model\>, or names the model and pays the lowest offer that meets the buyer's rules.

## Facts

- Handle: engy
- Website: https://engy.ai/
- On the exchange since: 2026-10-01
- Models: 9
- Offers: 9
- Regions: asia
- Precisions (declared): fp4, fp8
- Lowest price on: 3 of 9 models

## Reliability, last 3 days

- Probes answered: 98.02%
- Hours with an answer: 98.6%
- Median response time: 2.8s

## Checked by the exchange

3 of 9 offers match the fingerprint of the model. 0 have a finished evaluation.

The exchange sends fixed prompts to each offer and compares the answers with a baseline for the model. It also runs benchmarks against the offers and keeps the results.

## Data handling

The provider states nothing about how it keeps data.

## Models

- [DeepSeek V4 Flash](https://liquidinference.ai/models/deepseek-v4-flash.md): declared precision fp8, asia, $0.050 input and $0.0050 output per million tokens, $0.010 cache read per million tokens, 920.6K tokens of context
- [DeepSeek V4.1 Flash](https://liquidinference.ai/models/deepseek-v4.1-flash.md): declared precision fp8, asia, $0.028 input and $0.090 output per million tokens, $0.010 cache read per million tokens, 262.1K tokens of context
- [GLM 5.2](https://liquidinference.ai/models/glm-5.2.md): declared precision fp4, asia, $0.155 input and $0.035 output per million tokens, $0.100 cache read per million tokens, 229.4K tokens of context
- [GLM 5.3](https://liquidinference.ai/models/glm-5.3.md): declared precision fp4, asia, $0.150 input and $0.035 output per million tokens, $0.050 cache read per million tokens, 294.9K tokens of context
- [GLM 5.3 Flash](https://liquidinference.ai/models/glm-5.3-flash.md): declared precision fp8, asia, $0.046 input and $0.140 output per million tokens, $0.020 cache read per million tokens, 229.4K tokens of context
- [Kimi K3](https://liquidinference.ai/models/kimi-k3.md): declared precision fp8, asia, $1.200 input and $3.000 output per million tokens, $0.120 cache read per million tokens, 1M tokens of context
- [Kimi K3.1 Pro](https://liquidinference.ai/models/kimi-k3.1-pro.md): declared precision fp4, asia, $1.790 input and $8.900 output per million tokens, $0.180 cache read per million tokens, 1M tokens of context
- [Qwen 3.6 35B a3b](https://liquidinference.ai/models/qwen3.6-35b-a3b.md): declared precision fp8, asia, $0.045 input and $0.300 output per million tokens, $0.015 cache read per million tokens, 131.1K tokens of context
- [Qwen 3.8 27B](https://liquidinference.ai/models/qwen3.8-27b.md): declared precision fp4, asia, $0.045 input and $0.320 output per million tokens, $0.015 cache read per million tokens, 131.1K tokens of context

## Related pages

- [This page in a browser](https://liquidinference.ai/providers/dfb60c1c-bf13-4aed-aedf-d80cc249ba87)
- [All providers](https://liquidinference.ai/providers.md)
- [All models](https://liquidinference.ai/models)
- [Discover the best model for your budget](https://liquidinference.ai/discover)
- [Quickstart](https://liquidinference.ai/docs/quickstart.md)
- [llms.txt: the index of every page, as Markdown](https://liquidinference.ai/llms.txt)
- [llms-full.txt: every page in one file](https://liquidinference.ai/llms-full.txt)