Celeris releases its Celeris-1 Magnus AI model
This hybrid diffusion model features native reasoning for multi-step tool use and code execution. It outperforms competing agents on banking benchmarks while maintaining low latency.
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AI research lab developing ultra-low-latency language models
celeris.aiLast updated
In short: Celeris launched Celeris-1, a hybrid diffusion AI model that achieved record-breaking token throughput and real-time processing speeds.
This hybrid diffusion model features native reasoning for multi-step tool use and code execution. It outperforms competing agents on banking benchmarks while maintaining low latency.
It uses diffusion inference for near-GPT-5 intelligence at 15x faster speeds
Celeris-1 delivers 1,596 tok/s, 8% faster than Cerebras and 3.5x faster than Groq in end-to-end benchmarks.
On a standardized workload, it generated 1,664 tokens per second, 5.1 times faster than the next fastest API.
Celeris, an artificial intelligence research lab focused on advancing frontier intelligence through building ultra-fast LLMs, announced Celeris-1, the lab's flagship language model. Built from the...
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