Google launches Gemini 3.8 Flash with enhanced reasoning and coding capabilities

Google has released Gemini 3.8 Flash and Gemini 3.8 Flash Cyber, its latest artificial intelligence models that deliver what the company describes as next-generation intelligence for agentic workflows and cybersecurity applications. The launch marks the third Flash release in only six weeks, following the Gemini 3.7 Flash model introduced three weeks earlier.

Enhanced Reasoning and Coding Capabilities

Gemini 3.8 represents Google's best reasoning and coding model yet, offered at the same speed and low cost as its predecessor, the 3.7 version. The new release introduces two variants tailored for different deployment environments, though both are powered by the same foundational intelligence. These models have been further accelerated by long-running agentic loops designed to recursively evaluate and refine the underlying technology.

The significant coding and reasoning improvements across this shared core were driven by multiple innovations, including rigorous training in the highly demanding domain of cybersecurity. According to Google, 3.8 Flash delivers substantial gains over 3.7 Flash, often approaching the performance of higher-cost frontier models.

On DeepSWE v1.1, a benchmark for long-horizon software engineering, 3.8 Flash outperforms most larger frontier models in autonomously solving complex engineering problems end to end, at only a fraction of the cost. The model also exhibits the dependability required for critical enterprise autonomy across specialized knowledge domains.

Performance Across Professional Fields

In quantitative and professional fields that require advanced analysis and reporting, 3.8 Flash outperforms both 3.7 Flash and other frontier models in benchmarks including Vals Finance Agent V2 and Harvey's Legal Agent Benchmark. The model achieves a 54.9 percent score on HLE-Verified, demonstrating its ability to handle multi-step reasoning across STEM, humanities, and professional fields.

These performance gains stem from a core design choice: 3.8 Flash works harder. On complex tasks, it exhibits greater diligence, executing extra reasoning steps and calling tools iteratively. At times, the model might use more tokens to maximize performance, especially at higher effort levels. For applications where compute efficiency is the primary constraint, developers can utilize lower effort levels to minimize token overhead or continue to rely on Gemini 3.7 Flash, which remains fully supported for efficiency-first workloads.

Cybersecurity Breakthrough

Gemini 3.8 Flash Cyber, available to a set of trusted defenders via the Fairwind Program, provides what Google characterizes as a decisive advantage in today's complex cybersecurity landscape, with the Flash speed and cost that enables quick iteration. On CyberGym, the standard industry benchmark for finding vulnerabilities, Gemini 3.8 Flash Cyber demonstrates frontier-level performance in autonomous vulnerability discovery, surpassing both 3.5 Flash Cyber and significantly larger frontier models.

To better capture real-world defensive needs beyond just C/C++ codebases like those in CyberGym, Google evaluated Gemini 3.8 Flash Cyber against a comprehensive internal benchmark in which the model must discover a wide range of vulnerabilities across complex codebases spanning 20 programming languages. The model showcases an impressive leap over previous models and reaches a success rate exceeding 70 percent.

With Gemini 3.8 Flash Cyber, Google focused specifically on equipping defenders with expert capabilities that give them an advantage over attackers, investing in vulnerability fixing from the start and prioritizing it over offensive capabilities like exploitation. On CWE-Bench, a challenging external benchmark for patching capabilities run by Collinear, Gemini 3.8 Flash Cyber is on the Pareto frontier: with a pass@1 of 47.2 percent compared to a leading frontier model at 47.8 percent, yet offered at a significantly lower cost.

Google is already using Gemini 3.8 Flash Cyber to secure code across its own operations. The 3.8 Flash ships with safeguards against misuse in the domains of Chemical, Biological, Radiological, and Nuclear (CBRN) and cyber offense, while enabling beneficial use cases, as per Google's Frontier Safety Framework. The 3.8 Flash Cyber ships with a more permissive set of mitigations for cybersecurity, and as such, is only available to trusted defenders who require a more comprehensive set of cyber capabilities.

Gemini 3.8 models have also made a significant leap in prompt injection robustness as measured by Gray Swan, protecting Gemini model users from prompt-injection related malicious attacks.