Cisco just launched two cyber-focused small language models: Antares-350M and Antares-1B aim to supercharge codebase analysis – and they run at a “fraction of the compute expense” of popular frontier models

Cisco has unveiled a new range of cyber-capable small language models (SLMs) aimed at supercharging security operations.

The Antares range, which comes in two forms (Antares-350M and Antares-1B) will be made available as open-weight models via Hugging Face. According to Cisco, the aim here is to provide a codebase vulnerability tool that's far cheaper than general of frontier models.

While the Antares SLMs will operate as specialized models alongside frontier and generalized models, the company promised they will run at a "fraction of the compute expense."

"Benchmark testing shows that these models outperform many powerful closed- and open-weight models in this critical security task at a fraction of the cost," said Amin Karbasi, VP and chief scientist for Cisco Foundation AI.

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“And they’re compact enough to run locally, heading off the need to send sensitive codebases to the cloud.”

The move by Cisco comes amidst wider concerns about the rising costs of AI, exacerbated by changes to billing and pricing that have caused bills to shoot up across the industry.

Some companies, including Accenture, have told staff to cut back on AI use as a result of skyrocketing prices. Indeed, one report suggested AI could cost more than developer salaries within a few years.

At the same time, AI is making inroads into security – faster than some expected – with the rise of cyber-focused models such as Anthropic's Claude Mythos.

How Cisco’s Antares models work

Antares is designed to mimic how a human investigator would work their way through a code repository – though Cisco noted the aim wasn't to replace human judgement, but to make it easier to manage the work.

The models can help with locating files that relate to a vulnerability warning, trigger investigations based on advisories, support development workflows that use vulnerable files, and more.

Cisco noted that the decision to release the Antares range as open-weight models means they’re easier to work with and improve.

"We are releasing Antares as open-weight because the security community needs more accessible building blocks for practical, repository-level defense," said Karbasi.

"Cisco's efforts are connected by a common belief: AI in security has to move beyond impressive one-off demos and toward systems that practitioners can evaluate, govern, and improve."

Tackling complexity

Cisco said that Antares was built to address two concerns when it comes to code: the complexity of checking it for vulnerabilities and the costs of using AI for that task.

First, Karbasi said that it was difficult to apply vulnerability knowledge — advisories, vulnerability alerts and severities, and so on — to a company's internal code.

"That work is difficult because repositories are large, security signals are noisy, and the relevant evidence is rarely in one obvious place," he said.

"Analysts often need to search through unfamiliar code, follow naming conventions, inspect call paths, compare candidate files, and decide whether a weakness is actually present."

How cheap is Antares?

AI can help with that challenge, but the high costs of general or frontier models mean it often isn't practical, in particular for public sector organizations, universities, and smaller security teams.

"Compact models reduce inference costs, support local or on-premises operations, and help teams keep sensitive source code within their own environment," Karbasi said.

So just how cheap are the Antares models? Cisco said that running a 500-entry evaluation using Antares took 15 minutes on a single GPU at a cost of less than $1.

Cisco noted that this was 15-times cheaper than the best available open source model and a whopping 172-times cheaper than the top-end frontier model.

"The goal is to build toward a system where all security practitioners, regardless of on-prem or resource constraints, can effectively incorporate AI in everyday security operations," Karbasi added.

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