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PoYo에서 OpenAI Chat Completions 또는 Gemini 네이티브 포맷으로 Google DeepMind의 Gemini 4 Argon API를 사용하세요. 1M 통합 입출력 컨텍스트, Vals Index 및 DeepSWE v1.1(77.9%) 1위, 1M 토큰당 입력 $1.60 / 출력 $8.00 (공식 가격 대비 20% 할인).
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이 Playground는 데모용입니다. 데이터는 현재 창에서만 유효하며 새로고침하면 지워집니다.

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숨겨진 비용 없이 투명한 가격입니다. 사용한 만큼만 지불하세요.

Googlegemini-4-argon
Input
PoYo 가격
$1.60/1M tokens
320 크레딧
공식 가격
$2.00/1M tokens
Official
절약률
20%
Googlegemini-4-argon
Output
PoYo 가격
$8.00/1M tokens
1600 크레딧
공식 가격
$10.00/1M tokens
Official
절약률
20%
Googlegemini-4-argon
Cache Read
PoYo 가격
$0.160/1M tokens
32 크레딧
공식 가격
$0.200/1M tokens
Official
절약률
20%

* 실제 비용은 최종 출력을 기준으로 합니다.

추천 모델
GEMINI 4 ARGON · POYO에서 바로 사용 가능

장기 코딩, 엔터프라이즈 지식 작업 및 사이버 방어를 위한 100만 통합 입출력 토큰 윈도우를 갖춘 Google DeepMind의 프론티어 추론 모델

장기 소프트웨어 엔지니어링, 기업 워크플로 및 사이버 방어를 위한 Gemini 4 Argon API

Gemini 4 Argon은 Google DeepMind의 차세대 희소 전문가 혼합(MoE) 프론티어 추론 모델입니다. 복잡하고 긴 호흡의 워크플로에서 깊이 있는 추론을 유지하도록 설계된 Argon은 최대 출력 한도를 기존 64K에서 업계 최고 수준인 1,000,000(1M) 통합 입출력 토큰으로 대폭 확장하여 전체 리포지토리 리팩토링, 심층 금융·법률 분석, 자율 보안 취약점 패치를 한 번에 수행합니다.

PoYo에서 모델 ID gemini-4-argon을 사용하여 OpenAI 호환 POST /v1/chat/completions 또는 Gemini 네이티브 POST /v1beta/models/gemini-4-argon:generateContent(및 :streamGenerateContent)로 호출할 수 있습니다. PoYo 요금은 입력 $1.60 / 1M 토큰(320 크레딧), 출력 $8.00 / 1M 토큰(1,600 크레딧), 캐시 읽기 $0.16 / 1M 토큰(32 크레딧)으로 Google 공식 표준 요금($2.00 / $10.00 / $0.20)보다 20% 저렴합니다.

PoYo API 키 발급받기

Gemini 4 Argon API 핵심 기능

소프트웨어 엔지니어링, 기업 데이터 분석, 3D 공간 추론 및 방어적 사이버 보안 전반에 걸친 Google DeepMind 공식 벤치마크와 실제 적용 사례.

01

State-of-the-Art Long-Horizon Software Engineering (77.9% DeepSWE v1.1)

Gemini 4 Argon sets a new state of the art on DeepSWE v1.1 (77.9%) and Vibe Code Bench (91.9%), outperforming Claude Opus 5.5 (74.2%) and GPT-6 Astra (74.1%). With a 1M token output limit, Argon can untangle multi-million-line legacy codebases, migrate C/C++ libraries to safe Rust (achieving a 2.7x speedup in Google's libgav1 video decoder), and optimize vLLM GPU kernels end-to-end without mid-response truncation.

  • 77.9% on DeepSWE v1.1 and 91.9% on Vibe Code Bench
  • Up to 1,000,000 unified input and output tokens per trajectory
  • Multi-file architecture refactoring and C++ to Rust migrations
Official Google DeepMind DeepSWE v1.1 benchmark chart showing Gemini 4 Argon at 77.9% vs Claude Opus 5.5 and GPT-6 Astra

02

#1 on Economic Knowledge Work & Enterprise Automation

Argon ranks #1 on the Vals Index (68.9%)—weighted across finance, legal, tax, and coding by U.S. GDP contribution—and leads Vals Finance Agent v2 (65.4%), Harvey's Legal Agent Benchmark (19.6% vs 5.4% for Astra), and Zapier's AutomationBench (51.3%). Its GraphWalks 256K–1M long-context recall reaches 84.2% F1, over 17 percentage points ahead of competing frontier models.

  • 68.9% on Vals Index and 65.4% on Vals Finance Agent v2
  • 19.6% on Harvey's Legal Agent Benchmark (3x higher than peers)
  • 84.2% F1 on GraphWalks 256K–1M long-context reasoning
Official Google DeepMind Vals Index benchmark comparison showing Gemini 4 Argon leading at 68.9%

03

Multimodal Video, 3D Spatial & Scientific Synthesis

Natively trained across text, images, audio, video, and PDFs, Gemini 4 Argon achieves 91.7% on LVBench (long video understanding), 88.8% on LABBench 2, and 87% on Embodied Reasoning (ERQA). In official DeepMind demonstrations, Argon synthesizes 50 GB of Airborne LiDAR, GIS vectors, and archival CAD drawings into interactive 3D reconstructions, and drives multi-agent visual critique loops in Blender and Three.js.

  • 91.7% on LVBench long-video comprehension and 71.6% on Chartography
  • 88.8% on LABBench 2 and 76.0% on RiemannBench mathematical reasoning
  • Autonomous 3D scene generation and multimodal scientific synthesis

04

Defensive Cybersecurity & Prompt Injection Resilience

Built for cyber defenders in Google's Fairwind Program and Wiz's Scan for Good initiative, Argon ties for #1 on CWE-bench v1 (68.0%) for autonomous vulnerability remediation and discovers complex multi-language exposures across 20 programming languages. Adversarial training reduces indirect prompt injection success to just 0.7% across 15 adaptive attempts on the Gray Swan IPI benchmark.

  • 68.0% on CWE-bench v1 for automated security patching
  • 0.7% attack success rate on Gray Swan Indirect Prompt Injection (IPI)
  • Autonomous source-code auditing and proof-of-concept validation
Official Google DeepMind CWE-bench v1 cybersecurity vulnerability remediation benchmark chart for Gemini 4 Argon

Gemini 4 Argon API로 무엇을 구축할 수 있나요?

01

Full-Repository Refactoring & Language Migration

Leverage the 1M unified input-output token window to refactor monolithic modules, migrate C/C++ codebases to memory-safe Rust, and output complete multi-file patches in one trajectory.

02

Autonomous Enterprise & Operations Agents

Orchestrate end-to-end business workflows across APIs, databases, and document repositories with #1 AutomationBench (51.3%) reliability and transparent chain-of-thought monitoring.

03

Financial Modeling & Legal Due Diligence

Connect evidence across hundreds of SEC filings, contracts, and case precedents with leading accuracy on Vals Finance Agent v2 (65.4%) and Harvey's Legal Agent Benchmark (19.6%).

04

Automated Security Auditing & Patching

Scan multi-language repositories to surface subtle logic flaws, validate exploitability in sandboxed environments, and generate verified CWE remediation patches.

05

Long-Video & Multimodal Document Intelligence

Analyze hours-long video recordings, technical charts, audio streams, and dense PDFs with 91.7% LVBench accuracy and 84.2% recall across 256K–1M token contexts.

06

Scientific Computing & 3D Simulation

Accelerate quantum circuit optimization, molecular conformer search, formal proof verification in Lean, and browser-ready Three.js / WebGL scientific visualizations.

Gemini 4 Argon vs GPT-6 Astra vs Claude Opus 5.5 vs Claude Fable 5.1 비교

2026년 10월 Google DeepMind Gemini 4 Argon 모델 카드에 발표된 공식 벤치마크와 공식 및 PoYo API 요금 비교입니다.

Benchmark / MetricGemini 4 ArgonGPT-6 AstraClaude Opus 5.5Claude Fable 5.1
Vals Index (Knowledge Work)68.9% (#1)63.1%67.0%65.8%
AutomationBench (End-to-End Workflows)51.3% (#1)41.4%42.5%31.4%
Vals Finance Agent v265.4% (#1)53.5%58.6%58.9%
Harvey's Legal Agent Benchmark19.6% (#1)5.4%3.8%6.7%
DeepSWE v1.1 (Agentic Coding)77.9% (#1)74.1%74.2%67.4%
Vibe Code Bench91.9% (#1)89.6%90.3%90.3%
Terminal-Bench 4.057.4%58.2%66.4%57.9%
LABBench 2 / RiemannBench (Science & Math)88.8% / 76.0%85.4% / 72.0%73.1% / 69.6%68.6% / 65.6%
GraphWalks 256K–1M (Long Context F1)84.2% (#1)71.8%66.8%65.0%
LVBench (Long Video) / Chartography91.7% / 71.6%87.5% / 71.0%83.7% / 66.3%79.7% / 46.2%
CWE-bench v1 (Cybersecurity)68.0% (Tied #1)68.0%67.0%58.0%
Context Window / Max Output1M / 1M unified1.05M / 128K1M / 128K1M / 128K
Official Standard Price (Input / Output per 1M)$2.00 / $10.00$10.00 / $50.00$4.00 / $20.00$10.00 / $50.00
PoYo API Price (Input / Output / Cache Read per 1M)$1.60 / $8.00 / $0.16$8.00 / $40.00 / $0.80$3.20 / $16.00 / $0.16$8.00 / $40.00 / $0.20

Source: Google DeepMind Gemini 4 Argon Model Card (October 2026). PoYo pricing reflects a 20% discount off official standard rates (200 credits = $1.00 USD).

PoYo에서 Gemini 4 Argon API 호출 방법

1. API 키 생성: PoYo 대시보드에 로그인하여 API 키를 생성합니다.

2. 엔드포인트 프로토콜 선택: OpenAI SDK 호환을 위해 POST https://api.poyo.ai/v1/chat/completions를 사용하거나, Gemini 네이티브 기능을 위해 POST https://api.poyo.ai/v1beta/models/gemini-4-argon:generateContent(및 :streamGenerateContent)를 사용합니다.

3. 모델 ID 설정: "model": "gemini-4-argon"을 전달하여 스트리밍 및 일반 응답을 모두 사용할 수 있습니다.

Gemini 4 Argon API 자주 묻는 질문

What is Gemini 4 Argon?

Gemini 4 Argon is Google DeepMind's flagship sparse Mixture-of-Experts (MoE) frontier reasoning model announced in late September 2026 and released globally in October 2026. It is engineered for long-horizon software engineering, high-stakes enterprise knowledge work (finance, legal, tax), scientific discovery, and defensive cybersecurity.

How much does the Gemini 4 Argon API cost on PoYo vs Google Official?

Google's official standard introductory pricing is $2.00 per 1M input tokens, $10.00 per 1M output tokens, and $0.20 per 1M cached input tokens. On PoYo, you get a flat 20% discount: $1.60 / 1M input tokens (320 credits), $8.00 / 1M output tokens (1,600 credits), and $0.16 / 1M cache read tokens (32 credits), where 200 credits = $1.00 USD.

Which API endpoints does PoYo support for Gemini 4 Argon?

PoYo supports both the OpenAI-compatible Chat Completions endpoint (POST https://api.poyo.ai/v1/chat/completions) and the Google Gemini Native endpoints (POST https://api.poyo.ai/v1beta/models/gemini-4-argon:generateContent and :streamGenerateContent) using the model ID gemini-4-argon.

What is the context window and maximum output token limit of Gemini 4 Argon?

Gemini 4 Argon features a 1,000,000-token unified input-output context window and expands maximum output capacity to 1,000,000 tokens (up from 64K in previous Gemini models). This allows the model to sustain 100K+ token reasoning chains and generate full-repository code or exhaustive reports in a single trajectory.

How does Gemini 4 Argon compare to Claude Opus 5.5 and GPT-6 Astra?

On Google DeepMind's published evaluations, Gemini 4 Argon leads on DeepSWE v1.1 (77.9% vs 74.2% for Opus 5.5 and 74.1% for Astra), Vals Index (68.9% vs 67.0% and 63.1%), AutomationBench (51.3%), GraphWalks 256K–1M (84.2%), and LVBench (91.7%), while tying Astra on CWE-bench v1 (68.0%). Claude Opus 5.5 leads on Terminal-Bench 4.0 (66.4% vs 57.4%), and GPT-6 Astra leads on FrontierSWE v2 (65.5%) and Terminal-Bench Science 0.1 (68.1%).

What input modalities and knowledge cutoff does Gemini 4 Argon have?

According to the Gemini 4 Argon Model Card, the model natively accepts text, images, audio, video, and PDF documents as input and produces text output. Its knowledge cutoff is March 2026.

왜 PoYo API로 Gemini 4 Argon을 연동해야 할까요?

01

20% Lower Token Costs

Pay $1.60 input, $8.00 output, and $0.16 cache read per 1M tokens—saving 20% compared to official rates with flexible pay-as-you-go credits.

02

Dual OpenAI & Gemini Native Formats

Switch seamlessly between /v1/chat/completions for existing OpenAI SDKs and /v1beta/models/gemini-4-argon:generateContent for native Gemini features.

03

Benchmark Side-by-Side with Opus & Astra

Use one PoYo API key to route workloads across Gemini 4 Argon, Claude Opus 5.5, Claude Sonnet 5.5, GPT-6 Astra, and GPT-6.1 Sol.

04

Instant Global Access, No Tier Gating

Start calling gemini-4-argon immediately in production or testing in the web Playground without enterprise waitlists or regional quota bottlenecks.