🔒Cisco Unveils Antares-350M and Antares-1B for Code Security
New models find bugs faster, cheaper than the big boys
TL;DR
Cisco has released Antares-350M and Antares-1B, open-source security models that outperform larger rivals like Google's Gemini. They're faster, cheaper, and work locally without leaving proprietary code.
Cisco just dropped two new security models, Antares-350M and Antares-1B, designed to find bugs in existing codebases. These small but mighty models are available on Hugging Face but only for vetted users. They outperform larger rivals like Google's Gemini and Z.ai's GLM-5.2, scanning 500 repos for less than a buck. If you're dealing with strict privacy or compliance requirements, these could be your new best friend.
Key Points
Antares-350M and Antares-1B are available to vetted users on Hugging Face, specializing in code security analysis.
Both models outperform larger rivals like Google's Gemini 3 Pro and Z.ai's GLM-5.2 in identifying security flaws.
It costs less than $1 to scan 500 repositories with Antares, compared to over $100 for frontier models.
Antares scans codebases faster and at a fraction of the cost, ideal for environments with strict privacy or compliance needs.
Cisco's future model, Antares-3B, promises better performance than GLM-5.2 and OpenAI's GPT-5.5 in finding vulnerabilities.
Why It Matters
If you're scanning proprietary codebases for security flaws, Cisco's new Antares models could be a game-changer. They outperform larger rivals while costing less and running locally without leaving your organization’s machines. But vetted users only can access them on Hugging Face.
Frequently Asked Questions
Why does this matter?
If you're scanning proprietary codebases for security flaws, Cisco's new Antares models could be a game-changer. They outperform larger rivals while costing less and running locally without leaving your organization’s machines. But vetted users only can access them on Hugging Face.
What happened?
Cisco has released Antares-350M and Antares-1B, open-source security models that outperform larger rivals like Google's Gemini. They're faster, cheaper, and work locally without leaving proprietary code.
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