BEIJING, March 18 (Reuters) - A powerful artificial

intelligence model that appeared anonymously on a developer

platform last week has sparked speculation that Chinese startup

DeepSeek may be quietly testing its next-generation system ahead

of an official launch.

The free model, called Hunter Alpha, surfaced on the AI

gateway platform OpenRouter on March 11 without any developer

attribution and was later described by the platform as a

"stealth model."

During tests conducted by Reuters, the Hunter Alpha chatbot

described itself as "a Chinese AI model primarily trained in

Chinese" and said its training data extended to May 2025, the

same knowledge cutoff point reported by DeepSeek's own chatbot.

When asked about its creator, however, the system declined

to identify its developer.

"I only know my name, my parameter scale and my context

window length," the chatbot said.

Neither DeepSeek nor OpenRouter has identified the model's

creator and they did not respond to requests for comment.

Hunter Alpha's profile page describes it as a

1-trillion-parameter model, meaning it was trained using roughly

one trillion adjustable values that determine how the system

processes language and generates responses. Models with more

parameters generally require significantly more computing power

to operate.

The system also advertises a context window of up to one

million tokens, a measure of how much text an AI model can

process or remember during a single interaction. A token roughly

corresponds to a short piece of text, such as part of a word.

"The combination that stood out was Hunter Alpha's 1 million

token context paired with reasoning capability and free access,"

said Nabil Haouam, an engineer who builds AI agent systems.

"Most frontier models with that context window come with

real cost at scale," he added.

Those specifications resemble expectations in local media

for DeepSeek's next-generation V4 model, which Chinese outlets

have reported could launch as early as April. DeepSeek, like

many of its Chinese competitors, is well-funded, though it has

an unusual structure given its parent company is a quantitative

hedge fund rather than a tech conglomerate.

While the overlap does not establish a direct connection, it

has intensified speculation among developers that the anonymous

system could be an early test version of the upcoming release by

DeepSeek.

"The chain-of-thought pattern is probably the strongest

signal," said Daniel Dewhurst, an AI engineer who analysed the

model after its release, referring to how the AI model reasons.

"Reasoning style is hard to disguise and tends to reflect

how a model was trained."

Hunter Alpha's scale and memory capacity also match

specifications that have circulated for DeepSeek V4 since early

this year, he said.

Still, some developers cautioned that the evidence linking

the model to DeepSeek was inconclusive.

"My analysis suggests Hunter Alpha is likely not DeepSeek

V4," said Umur Ozkul, who runs independent AI benchmark tests,

citing differences in token-related behaviour and architectural

patterns when compared with DeepSeek's existing systems.

He said speculation connecting the model to DeepSeek was

understandable given the timing and capabilities advertised.

DEVELOPER TESTING

Anonymous model launches are not unusual, as platforms like

OpenRouter allow developers to send queries to dozens of AI

models through a single interface, making them a popular testing

ground for new systems.

An anonymous model called Pony Alpha appeared on OpenRouter

in February before Chinese firm Zhipu AI confirmed it was part

of its GLM-5 system five days later.

A notice on Hunter Alpha's profile page said all prompts and

completions for the model "are logged by the provider and may be

used to improve the model," underscoring the industry-wide

practice of using stealth model launches for unbiased feedback.

The model was adopted rapidly after appearing on the

platform and processed more than 160 billion tokens as of

Sunday, according to OpenRouter statistics.

Much of the activity came from software development tools

and AI agent frameworks like OpenClaw, which allow AI systems to

autonomously plan tasks and interact with external software.