이 모델의 강점은 무엇인가요?

한 번의 응답에 100만 토큰 출력으로 장문 에이전트·기업 지식 작업에 적합 GPT-6.1 Sol과 같은 $2/$10 가격대면서 Text Arena 최상위권 능력 코딩·기업 지식·사이버 방어에 강하고 CWE-bench v1 68%(자율 취약점 처리) Fairwind Program 단계적 롤아웃은 최근 프론티어 출시 중 가장 규율 있는 안전 자세

이 모델의 약점은 무엇인가요?

접근이 게이트되어 일반 API는 추가 안전 심사와 미국 사전 심사 대기로 GA가 늦음 독립 검증 결과 Sol 대비 작업당 2배 이상 토큰을 소모하고 실용 코딩에서 뒤처짐 환각율 약 15%(독립 측정)는 Astra의 51%보다 낫지만 Opus 5.5의 66%에는 미달 13/19·Text Arena 1위 등 여러 벤치마크 주장은 발표 시점 Google 자체 보고치

어떤 용도에 가장 적합한가요?

장문 문서 요약·법무·컴플라이언스 일괄 처리 자율 에이전트·악성코드 분석·취약점 분류(CWE-bench 강점) 기업 지식 검색과 코드베이스 이해를 요하는 엔터프라이즈 RAG

Google DeepMind독점

Gemini 4 Argon

Name: Gemini 4 Argon
Author: Google DeepMind

이 모델 비교

Google DeepMind의 Gemini 4 Argon은 2026년 10월 5일 발표한 프론티어 기초 모델로, 한 번의 응답에서 100만 토큰을 출력하는 창과 GPT-6.1 Sol과 동일한 공격적 가격($2/$10 per 100만 토큰)이 특징이다. 접근은 Fairwind Program을 통해 게이트되며, 신뢰된 사이버 방어자에게 먼저 열리고 일반 API는 추가 안전 심사 후 개방된다. Google은 데뷔 시점 19개 벤치마크 중 13개에서 1위(Text Arena도 1위)라고 주장하나, 모두 벤더 자체 보고치로 독립 재검증을 기다리는 단계다.

공유:X Hatena LINE

파라미터

Not disclosed

컨텍스트

1M output tokens (input context undisclosed)

라이선스

Proprietary

출시일

2026-10-05

API 가격

입력 가격 (1M 토큰당)

출력 가격 (1M 토큰당)

$10

과금 모드: standard

강점

•한 번의 응답에 100만 토큰 출력으로 장문 에이전트·기업 지식 작업에 적합
•GPT-6.1 Sol과 같은 $2/$10 가격대면서 Text Arena 최상위권 능력
•코딩·기업 지식·사이버 방어에 강하고 CWE-bench v1 68%(자율 취약점 처리)
•Fairwind Program 단계적 롤아웃은 최근 프론티어 출시 중 가장 규율 있는 안전 자세

약점

•접근이 게이트되어 일반 API는 추가 안전 심사와 미국 사전 심사 대기로 GA가 늦음
•독립 검증 결과 Sol 대비 작업당 2배 이상 토큰을 소모하고 실용 코딩에서 뒤처짐
•환각율 약 15%(독립 측정)는 Astra의 51%보다 낫지만 Opus 5.5의 66%에는 미달
•13/19·Text Arena 1위 등 여러 벤치마크 주장은 발표 시점 Google 자체 보고치

활용 사례

•장문 문서 요약·법무·컴플라이언스 일괄 처리
•자율 에이전트·악성코드 분석·취약점 분류(CWE-bench 강점)
•기업 지식 검색과 코드베이스 이해를 요하는 엔터프라이즈 RAG

심층 분석

Max output tokens

1,000,000

Up to 1M-token output in a single response; input context undisclosed

Input / Output price

$2 / $10 per 1M

Matches GPT-6.1 Sol; aggressive for a frontier model

Benchmark lead

13 of 19

Per Google; 1st on Text Arena at debut

CWE-bench v1

68%

Autonomous vuln find/validate/fix

Access

Fairwind Program (gated)

Trusted cyber defenders first; broader access after safety review

Hallucination rate

~15%

Independent testing; trails Opus 5.5 (66%) but beats Astra (51%)

강점

・1M-token output in a single response is a real differentiator for long agentic and enterprise-knowledge jobs - few models ship that much output today.
・Priced like a mid-tier model ($2/$10) while landing at or near the top of Text Arena - Google is competing on price as well as capability, directly colliding with GPT-6.1 Sol.
・Strong on the work Google is aiming at: coding, enterprise knowledge and cyber defense, with 68% on CWE-bench v1 for autonomous vulnerability handling.
・Gated, staged rollout through the Fairwind Program reads as the most disciplined safety posture of the recent frontier launches - if you are a trusted defender, access is fast.

약점

・Access is gated: broader API access is held for further safety checks and a U.S. voluntary pre-release review, so general availability is slower than an un-gated launch.
・Independent testing says it burns over 2x the tokens per task versus GPT-6.1 Sol and trails it on some real-use coding, eroding the price advantage the $2/$10 tag implies.
・Hallucination rate ~15% (independent) is better than Astra's 51% but worse than Opus 5.5's stated 66% misread - verify on your own data before trusting long outputs.
・Several benchmark claims (13 of 19, Text Arena #1) are Google self-reported at launch; treat the composite as provisional until Artificial Analysis and others re-run them.

경쟁사 비교

Model	Arena	SWE	GPQA	Price
GPT-6.1 Sol	N/A	N/A	N/A	$2 / $10 per 1M
Claude Opus 5.5	N/A	N/A	N/A	Proprietary
Gemini 3.8 Flash	N/A	N/A	N/A	$0.30 / $1.20 per 1M

개요

Gemini 4 Argon is Google DeepMind's first frontier model in over seven months, launched in early October 2026 and aimed at complex, long-horizon coding, enterprise knowledge work and cyber defense. Its headline specs are serious: up to 1,000,000 output tokens in a single response, introductory API pricing of $2 per million input tokens and $10 per million output - identical to OpenAI's GPT-6.1 Sol - and a claimed lead on 13 of 19 credible benchmarks, debuting at or near the top of Text Arena. The launch shape matters as much as the specs. Argon reaches 'trusted cyber defenders' first through Google's Fairwind Program, with broader API access held for further safety checks and a U.S. voluntary pre-release review. That is the same gated choreography OpenAI and Anthropic have used - ship the capable model, bolt on the gate, call it safety. Argon is a genuine frontier release; the gating is the same control valve painted a different color, and the ~15% independent hallucination rate means long outputs still need verification.

벤치마크 및 성능

상세 비교

### Head-to-head with the models it actually competes with | Feature | Gemini 4 Argon | GPT-6.1 Sol | Claude Opus 5.5 | Gemini 3.8 Flash | | :--- | :--- | :--- | :--- | :--- | | **Role** | Frontier coding/cyber | Frontier coding/agent | Frontier reasoning | Efficient flash | | **Price (in/out per 1M)** | $2 / $10 | $2 / $10 | Proprietary | $0.30 / $1.20 | | **Max output** | 1,000,000 | 128K | 128K | ~1M (flash) | | **CWE-bench v1** | 68% | N/A | N/A | N/A | | **Access** | Fairwind (gated) | GA | GA | GA | | **Hallucination** | ~15% | N/A | ~66% misread | N/A | **The routing decision.** Argon wins on output capacity and cyber-defense framing, and its $2/$10 price matches Sol exactly - so if you need million-token outputs and can wait for Fairwind access, it is the stronger pick. If you need general availability now, Sol and Opus 5.5 are already GA. The ~2x token burn vs Sol means Sol may still be cheaper per real task despite identical list price.

커뮤니티 평가

Reaction at launch split between 'finally a real Google frontier' and 'another gated rollout.' The 1M output window drew the most enthusiasm - developers building long agentic and document pipelines called it the feature they had been waiting for. The Fairwind gating drew the usual skepticism: trusted cyber defenders get fast access while everyone else waits, which looks like a distribution gate more than a safety gate. * **What people liked.** The output ceiling and the $2/$10 price that directly challenges Sol; early cyber-defense feedback on CWE-bench-style tasks was positive. * **What people pushed back on.** The gated access and the self-reported 13-of-19 / Text Arena #1 claims; independent testing already showing ~2x token burn vs Sol cooled the price-story. * **The safety read.** Argon's staged, Fairwind-first rollout is the most disciplined of the recent frontier launches - but it is still a lab controlling its own distribution, which fits the broader 'gate as control valve' pattern rather than a neutral safety regime.

활용 사례

### Where Gemini 4 Argon earns its price **1. Long-horizon coding and repo-scale agents** * **Example:** An agent that reads an entire large codebase, plans a multi-file refactor, and writes patches across a 1M-token window in one response. * **Why:** The 1M output token ceiling is the standout - few frontiers ship that much output, and it removes the chunk-and-stitch overhead for big jobs. **2. Cyber defense (Fairwind)** * **Example:** A trusted defender using Argon to find, validate and fix critical vulnerabilities autonomously. * **Why:** 68% on CWE-bench v1 for autonomous vulnerability handling; this is the use case Google aimed the gated rollout at. **3. Enterprise knowledge synthesis** * **Example:** Summarizing a massive document set or audit trail into one coherent long output. * **Why:** 1M output plus enterprise-knowledge positioning fits regulatory, legal and finance report drafting - but verify the ~15% hallucination rate on your own corpus.