Google
Google
CybersecurityClosed Source - Restricted Access Verified Architecture & SpecsEnterprise Tier

Gemini 3.8 Flash Cyber

Google’s cybersecurity-focused Gemini 3.8 variant for defensive vulnerability discovery and automated patching. It is available only to trusted defenders through Google’s Fairwind Program; Google has not published a standalone public API ID or token rate card for this variant. Use it for defensive security research, vulnerability discovery, code analysis, and patch generation rather than treating it as a generally available consumer/developer model.

Technical Architecture & Execution Specifications
Architecture Overview

Gemini 3.8 Flash Cyber

Google’s cybersecurity-focused Gemini 3.8 variant for defensive vulnerability discovery and automated patching. It is available only to trusted defenders through Google’s Fairwind Program; Google has not published a standalone public API ID or token rate card for this variant. Use it for defensive security research, vulnerability discovery, code analysis, and patch generation rather than treating it as a generally available consumer/developer model.

Supported Modalities
text

Hardware & Execution ParametersCybersecurity

Total Parameter CountUndisclosed
Active Parameters (MoE)Undisclosed per token
Context Window CapacityStandard
Model Weights FootprintN/A
Distribution LicenseClosed Source - Restricted Access
Standard API Pricing (1M Tokens)$null in / $— out
Model Heritage & Evolutionary Lineage
Gemini v3.8

Genealogical Graph & Evolutionary Provenance

Tracing foundational base architecture ancestry, architectural successors, scale siblings, and reasoning distillation derivatives.

Ancestral Base / Predecessor
Active SelectionSep 2026
Gemini 3.8 Flash Cyber
UndisclosedCurrent Spec
Evolutionary Successor
Latest Generation Checkpoint
Sibling Scale Variants (1)
AI Model Architecture & Intelligence

Architecture Engineering & Capability Deep-Dive

An objective architectural evaluation of Gemini 3.8 Flash Cyber by Google, analyzing underlying compute dynamics, memory constraints, and deployment economics.

Topology & Attention Mechanics

A robust autoregressive transformer utilizing standard attention patterns for predictable and coherent token generation.

Architecture Type:Advanced Transformer

Evaluation Profile & Reasoning

Exhibits frontier-tier behavior in reasoning and coding.

Domain Specialty:Cybersecurity

LLM Hardware Sizing & Serving

Served via scalable API endpoints guaranteeing high tokens-per-second concurrency and enterprise SLAs.

KV Cache Mgmt: PagedAttention / FlashAttention-3
Hosting Type:Closed Source - Restricted Access

Inference Economics & Workflows

Well-suited for enterprise pipelines where capability is balanced against per-million token costs.

Enterprise Fit:Production Ready
Production Trade-Offs & Capability Balance

Architectural Strengths vs. Considerations

An objective balance sheet analyzing the operational advantages and production constraints of deploying Gemini 3.8 Flash Cyber.

Key Architectural Strengths

  • Ultra cost-effective inference at $null/1M input tokens enables high-frequency agent loops.
  • Demonstrated CyberGym evaluation score of 86.2% in verified benchmarks.

Operational Considerations

  • Non-deterministic reasoning chains require schema validation in safety-critical deployments.
LLM Hardware Sizing & Runtime Compatibility

Inference Runtimes & Hardware Sizing

Deployment targets, inference engines, and memory requirements for Gemini 3.8 Flash Cyber.

Recommended Hardware Profile:
Cloud Hosted API (Zero Local VRAM)
Supported Inference Engines
Vendor REST API

Primary managed cloud endpoint

Official
OpenRouter

Unified multi-provider gateway

Supported
Amazon Bedrock / GCP

Private cloud enterprise integration

Enterprise
OpenAI SDK

Standard chat completions client

Compatible
Precision & Quantization Formats
Cloud PrecisionManaged Serving

Vendor-optimized floating point precision (FP8/BF16)

Prompt CachingPrefix Cache

Up to 50–90% cost reduction on repeated system prompts

LLM Benchmark Database & Performance Metrics

3 Tested

Standardized evaluation results across reasoning, agentic coding, computer use, and alignment.

Flagship Headline MetricsIndustry SOTA Standard
Cybersecurity & Safety

CyberGym

86.2%pass@1
0%100%
General / Other

Internal 20-language vulnerability benchmark

71%success_rate
0%100%
Cybersecurity & Safety

CWE-Bench

47.2%pass@1
0%100%
CyberGym
pass@1
86.2%
CWE-Bench
pass@1
47.2%
Internal 20-language vulnerability benchmark
success_rate
71%
Commercial Rates & Inference Costs

API & Deployment Pricing

Standard API consumption rates per million tokens as indexed from official laboratory pricing documentation.

Usage TierRate / Unit
Prompt / Input Tokens$ / 1M tokens
Completion / Output Tokens$ / 1M tokens
Inference Cost & ROI Engine
Market Cloud Rate
Prompt / Input Volume:50M Tokens / mo
1M500M1,000M
Generated / Output Volume:10M Tokens / mo
1M250M500M
Estimated Monthly Spend
$125.00/ mo
Input (50M @ $1.50/1M):$75.00
Output (10M @ $5.00/1M):$50.00
Cloud GPU Breakeven Ratio
RunPod RTX 4090 ($316/mo)0.40x spend
Lambda 1x H100 ($1,800/mo)0.07x spend
Similar Frontier Models & Alternatives
Explore All Comparisons

Comparable Foundation Architectures

Alternative models in the Cybersecurity class with similar capabilities, context windows, or deployment profiles.

MetaAudio

Muse Voice Transcribe

Context:Standard ctx
Parameters:Undisclosed
Input Rate:Free / Self-Host
OpenAIAudio

GPT-Realtime-Translate

Context:16k ctx
Parameters:Proprietary
Input Rate:Free / Self-Host
OpenAIAudio

GPT-Live-Transcribe

Context:Standard ctx
Parameters:Proprietary
Input Rate:Free / Self-Host
Integration & Deployment
import os
from google import genai

client = genai.Client(api_key=os.environ.get("GOOGLE_KEY"))

response = client.models.generate_content(
    model="google-gemini-3-8-flash-cyber-20260902",
    contents="Explain quantum superposition in 2 sentences.",
)
print(response.text)
Frequently Asked Questions

Frequently Asked Questions about Gemini 3.8 Flash Cyber

Essential facts, architectural specs, hardware constraints, and pricing answers for Gemini 3.8 Flash Cyber.

Gemini 3.8 Flash Cyber is a proprietary API model and cannot be run locally. It requires no local VRAM.

Primary Sources & Access Repositories

All technical specifications, parameter distributions, context architectures, and benchmark evaluations for Gemini 3.8 Flash Cyber are audited against primary source release documentation, research whitepapers, and verified vendor API endpoints.

access:Fairwind Program