Cisco bets its small open cybersecurity models can outperform GPT-5.5 at vulnerability detection for a fraction of the cost
Quick Answer
Cisco has launched two small open AI models, Antares-350M and Antares-1B, for cybersecurity vulnerability detection, claiming they detect 150 times more vulnerabilities per dollar than larger models like GPT-5.5.
Quick Take
In tests, Antares scanned 500 code repositories in 15 minutes for under a dollar, while GPT-5.5 took five hours and cost over $100.
Key Points
- Antares models trained on 72% security data and 15% code search histories.
- Both models run locally, ensuring sensitive code remains within the company.
- Cisco retains a larger 3-billion-parameter model for its own products.
- The larger model reportedly rivals GPT-5.5 and outperforms open models significantly.
- Cisco is exploring an industry consortium for open AI security tools.
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~1 min read
Jul 22, 2026
Cisco has released two small, open AI models for cybersecurity. Antares-350M and Antares-1B spot vulnerabilities in software code. Cisco's pitch is bang for the buck. Developer Aman Priyanshu claims on X that the smallest model catches about 150 times more vulnerabilities per dollar than large AI agents like Cognition's Devin Security Swarm. In Cisco's own tests, according to Axios, Antares scanned 500 code repos in about 15 minutes for under a dollar. GPT-5.5 took five hours and cost over $100 for the same job.
Both models run locally, so sensitive code never leaves the company. The technical report says the models were trained on roughly 72 percent security-concept data and 15 percent code search histories.
Cisco is keeping a larger three-billion-parameter version for its own products. That version reportedly performs close to GPT-5.5 and beats open models up to 200 times its size. The company is also exploring an industry consortium for open AI security tools.
— Originally published at the-decoder.com
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