Claude vs GPT vs Gemini for Security Research (2026)

Every serious security researcher in 2026 runs at least two frontier models. This is the working comparison — not benchmark theatre — for picking the right one per task.

Code review and vuln discovery

Claude (Sonnet 4.5 / Opus 4.1) consistently wins on whole-repo reasoning thanks to long-horizon coherence and accurate taint tracing. GPT-5 catches subtle logic bugs Claude misses and is more rigorous about preconditions. Gemini 3.1 Pro has the largest context window and is best for codebases >500k tokens.

Refusal behaviour for offensive prompts

Claude: stricter on novel offensive technique synthesis; cooperative on review/triage with clear scope.
GPT-5: more permissive on offensive payload generation; abrupt refusals on CBRN/persona prompts.
Gemini: most variable — same prompt may refuse one session, comply the next.

All three respond best to explicit scope ('this is my system, authorised test') and concrete deliverables (a payload, a report).

Agent execution (Claude Code vs Codex vs Jules)

Claude Code remains the strongest terminal agent for long-horizon tasks: it plans, recovers from failure, and respects permissions. OpenAI Codex is faster on small, well-scoped tasks. Google Jules is best when the workload is GCP-native.

Pricing reality for bug bounty wallets

A serious bug-bounty session burns $5–$30 in tokens. Claude prompt caching cuts repeat-context costs by 80–90%; GPT-5 batch mode halves cost when latency is flexible. Run cheap models (Sonnet, GPT-5-mini, Gemini Flash) for enumeration; promote to top-tier only for final review.

Quick picker

Whole-repo review: Claude.
Single-function rigorous review: GPT-5.
>500k-token context: Gemini.
Terminal agent in your repo: Claude Code.
Cheap enumeration: Sonnet or GPT-5-mini.

FAQ

Should I just use whichever is cheapest?

No. Use the cheap tier for breadth (enumeration, grep-style passes) and the top tier for depth (exploit synthesis, write-up).