Head-to-Head Model Comparison

GPT Image 1 vs Gemini 4 Argon

Benchmarks, API Token Pricing, Context Window & Speed Comparison

تمت المراجعة بواسطة فريق أبحاث GetInfoUsآخر مراجعة: October 2026السياسة التحريرية
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Compare GPT Image 1 by OpenAI against Gemini 4 Argon by Google across real-world coding, reasoning, token economics, and latency.

مقارنة مباشرة (VS)

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OpenAI

GPT Image 1

نموذج رائد متقدم

نموذج GPT Image 1 المقدم من OpenAI يوفر نافذة سياق تصل إلى 4K رمز، بتكلفة $5 لكل مليون رمز إدخال و$40 لكل مليون رمز إخراج، ومصمم للبرمجة والاستدلال وتطبيقات الأعمال.

Intelligence Index41 / 100
Input Token:

$5.00 / 1M

Output Token:

$40.00 / 1M

Context Window:

4.1K tokens

SWE-bench Verified:

38.8%

Google

Gemini 4 Argon

نموذج استدلال عميق

نموذج Gemini 4 Argon المقدم من Google يوفر نافذة سياق تصل إلى 1M رمز، بتكلفة $2 لكل مليون رمز إدخال و$10 لكل مليون رمز إخراج، ومصمم للبرمجة والاستدلال وتطبيقات الأعمال.

Intelligence Index97 / 100
Input Token:

$2.00 / 1M

Output Token:

$10.00 / 1M

Context Window:

1M tokens

SWE-bench Verified:

81.9%

أهم الفروقات في لمحة

  • Gemini 4 Argon is 3.6x cheaper for API usage (input + output tokens combined).
  • Gemini 4 Argon has a larger context window (1M vs 4K tokens).
  • Gemini 4 Argon is faster at 115 tok/s vs 14 tok/s.
  • Gemini 4 Argon leads on SWE-bench coding (81.9% vs 38.8%).
Need definitions for token pricing, context, or benchmarks?Explore AI Glossary →
FeatureGPT Image 1Gemini 4 Argon
Intelligence Index
Composite reasoning & knowledge score (0-100)
4197
Provider
OpenAIGoogle
Input Price
Cost per million input tokens
$5.00 / 1M$2.00 / 1M
Output Price
Cost per million output tokens
$40.00 / 1M$10.00 / 1M
Blended Price
Weighted 7:2:1 cache:input:output per 1M
$5.00 / 1M$1.47 / 1M
Context Window
Maximum input + output tokens
4.1K tokens~6 A4 pages of text1M tokens~1,500 A4 pages of text
Max Output Tokens
Per single request
4K1000K
Throughput Speed
Tokens generated per second
14 tok/s115 tok/s
SWE-bench Verified
Real-world software engineering
38.8%81.9%
GPQA Diamond
Graduate-level reasoning
53.6%81.5%
Cached Input Price
Prompt caching discount per 1M tokens
$0.00 / 1M$0.10 / 1M

من يتفوق في كل مجال؟

At-a-glance decision framework
Coding
Gemini 4 Argon
+43.1% SWE-bench lead
Cost
Gemini 4 Argon
3.6x cheaper monthly runtime
Speed
Gemini 4 Argon
+721% faster generation
Context
Gemini 4 Argon
1M tokens window

نتائج الاختبارات المعيارية الموثقة

Official evaluation metrics verified by independent third-party research labs.

GPT Image 1Gemini 4 Argon
SWE-bench Verified (Autonomous Coding)

Industry benchmark evaluating real-world GitHub issue resolution and multi-file debugging.

38.8%vs81.9%
GPQA Diamond (Doctorate-Level Science & Math)

Challenging questions created by domain experts to test complex PhD-level reasoning.

53.6%vs81.5%
MMLU-Pro (Multi-task Language Understanding)

Hardened reasoning and academic knowledge benchmark with reduced lucky-guess probability.

72.6%vs90.8%
LMSYS Chatbot Arena Elo

Crowdsourced human preference evaluation based on blind, head-to-head model battles.

1286ptsvs1525pts
Humanity's Last Exam (Frontier Expert Knowledge)

Extremely difficult, closed-ended questions spanning the frontier of human expert knowledge.

4.1%vs18.9%
Terminal-Bench (Agentic Coding & Terminal Use)

Autonomous multi-step tasks executed inside a real command-line terminal environment.

18.5%vs57.4%
SciCode (Scientific Computing)

Research-grade coding problems drawn from real scientific and numerical workloads.

27.3%vs56.4%
LiveCodeBench (Competitive Coding)

Contamination-free competitive programming problems collected continuously over time.

43.9%vs80.5%
AIME (Advanced Math Competition)

American Invitational Mathematics Examination — multi-step Olympiad-level reasoning.

29.7%vs94.8%
Long-Context Reasoning

Accuracy when reasoning over very large inputs that fill the model context window.

58.2%vs96.4%
Generation Speed (Throughput)

Tokens emitted per second during active generation streaming.

14 tok/s vs115 tok/s

زمن الاستجابة والسرعة

Time to first token (TTFT) and estimated end-to-end response time for a typical 500-token response.

Time to First Token (TTFT)Lower is better
GPT Image 18.20s
Gemini 4 Argon0.85s
Est. End-to-End Response (500 tokens)TTFT + generation time
GPT Image 143.91s
Gemini 4 Argon5.20s

محاكي تكلفة الرموز التفاعلي

Adjust sliders to calculate projected monthly cloud API spending with prompt caching discounts.

100K / day
10K500K1M
30K / day
5K150K300K
50% cached
0% (Cold)50%90% (Warm)
GPT Image 1 Monthly API Bill
$43.50 / month
$5/1M in · $40/1M out
Gemini 4 Argon Monthly API Bill
$12.15 / month
$2/1M in · $10/1M out
Gemini 4 Argon saves approximately $31.35 / month (72%) under this workload.3.6x Savings

GPT Image 1 · Strengths & Key Advantages

  • بنية Native multimodal image generation transformer متطورة من OpenAI مع سعة سياق تبلغ 4K رمز
  • كفاءة عالية في التكلفة ($5/1M إدخال و$40/1M إخراج) وسرعة استجابة ممتازة
  • أداء قوي في اختبارات البرمجة، الاستدلال المنطقي، ودعم اللغات المتعددة
Considerations & Trade-offs
  • يتطلب إدارة دقيقة لاستهلاك الرموز عند استخدام نافذة السياق الكاملة
  • قد يحتاج إلى ضبط دقيق للتعليمات (Prompt Engineering) في المهام التخصصية المعقدة

Gemini 4 Argon · Strengths & Key Advantages

  • بنية Pathways Multimodal Sparse Mixture-of-Experts متطورة من Google مع سعة سياق تبلغ 1M رمز
  • كفاءة عالية في التكلفة ($2/1M إدخال و$10/1M إخراج) وسرعة استجابة ممتازة
  • أداء قوي في اختبارات البرمجة، الاستدلال المنطقي، ودعم اللغات المتعددة
Considerations & Trade-offs
  • يتطلب إدارة دقيقة لاستهلاك الرموز عند استخدام نافذة السياق الكاملة
  • قد يحتاج إلى ضبط دقيق للتعليمات (Prompt Engineering) في المهام التخصصية المعقدة

Token Use & Task Economics

Estimated cost and token consumption to complete one representative agentic task.

MetricGPT Image 1Gemini 4 Argon
Cost per Task
Estimated USD to finish one task
$0.32$2.45
Output Tokens / Task
Tokens generated per task
8K75K
Reasoning Tokens / Task
Thinking tokens burned per task
0K36K

المواصفات التقنية

Architecture, release timeline, capabilities, and modalities.

FeatureGPT Image 1Gemini 4 Argon
Official API Model ID (SDK)gpt-image-1models/gemini-4-argon
API ProtocolOpenAI Responses API & Chat Completions v1Google Gemini API (generateContent) + OpenAI-Compatible SDK
Release Date2025-042026-09
Knowledge CutoffApril 2025June 2026
ArchitectureNative multimodal image generation transformerPathways Multimodal Sparse Mixture-of-Experts
ParametersConfidentialConfidential
Enterprise Rate Limits (RPM / TPM)10,000 – 30,000 RPM (Tier 5 Enterprise) · 800,000 – 2,000,000 TPM10,000 – 30,000 RPM (Tier 5 Enterprise) · 4,000,000 – 10,000,000 TPM
Long-Context Tier (>128K/200K)Flat rate ($5/1M in) across full 4K windowStandard rate up to 200K tokens; 2x input/output tier above 200K tokens
Prompt Cache Policy & TTLAutomatic prefix caching at $0/1M (no extra cache-write fee)Implicit + Explicit Context Caching at $0.1/1M with configurable TTL
Computer Use / GUI AgentSupported (Screen coordinate grounding, browser & desktop GUI action loops)Supported (Screen coordinate grounding, browser & desktop GUI action loops)
MCP & Parallel Tool CallingPrompt-based JSON extraction onlyNative MCP Client/Server ready · Parallel function calling · 100% Strict JSON Schema
Web Search Grounding & SandboxNative Web Search tool + Hosted Code Interpreter & File Search RAGBuilt-in Google Search Grounding + Managed Python Code Execution Sandbox
Official Fine-Tuning SupportSupervised Fine-Tuning (SFT), Direct Preference (DPO) & Reinforcement Fine-Tuning (RFT)Vertex AI Supervised Adapter Tuning & Context Distillation
Multimodal Token BillingText BPE (~4 chars/token) · Vision (~258–765 tokens per image tile)Text BPE (~4 chars/token) · Vision (~258–765 tokens per image tile) · Audio (~25–32 tokens/sec) · Video (~258–300 tokens/sec)
Quantization & Min GPU VRAMCloud-Hosted Proprietary (FP8 / BF16 Tensor Core Cluster) · Zero Local VRAM Required (100% Serverless Cloud API)Cloud-Hosted Proprietary (FP8 / BF16 Tensor Core Cluster) · Zero Local VRAM Required (100% Serverless Cloud API)
Safety & Frontier ClassificationOpenAI Preparedness Framework Audited & System Card PublishedGoogle DeepMind Frontier Safety Framework Verified
Enterprise Compliance (ZDR/HIPAA/SOC2)SOC2 Type II · GDPR · Zero Data Retention (ZDR) & HIPAA BAA Available on Enterprise TierSOC2 Type II · GDPR · Zero Data Retention (ZDR) & HIPAA BAA Available on Enterprise Tier
Input Modalitiestext, visiontext, vision, audio, video
Output Modalitiesimagetext

GPT Image 1 vs Gemini 4 Argon: إجابات سريعة (FAQ)

Which is more intelligent, GPT Image 1 or Gemini 4 Argon?

Gemini 4 Argon is more intelligent. It scores 97 compared with 41 on the composite Intelligence Index.

Which model is faster?

Gemini 4 Argon is faster, generating 115 tokens per second compared with 14 tokens per second.

Which model is cheaper to run?

Gemini 4 Argon is cheaper at $1.47 per 1M tokens blended, compared with $5.00 (7:2:1 cache:input:output ratio).

Which model has lower latency?

Gemini 4 Argon has lower latency, with a time to first token of 0.85s compared with 8.20s.

Which model has a larger context window?

Gemini 4 Argon has a larger context window, supporting 1M tokens compared with 4.1K tokens.

الحكم النهائي

Choose GPT Image 1 for أتمتة الأعمال، تطوير البرمجيات، الوكلاء الأذكياء (ai agents)، وتطبيقات openai الإنتاجية, or choose Gemini 4 Argon for أتمتة الأعمال، تطوير البرمجيات، الوكلاء الأذكياء (ai agents)، وتطبيقات google الإنتاجية.

الأسئلة الشائعة (FAQ)

Which is cheaper: GPT Image 1 or Gemini 4 Argon?+

GPT Image 1 costs $5/1M input and $40/1M output tokens, while Gemini 4 Argon costs $2/1M input and $10/1M output tokens.

Which model has a larger context window: GPT Image 1 or Gemini 4 Argon?+

GPT Image 1 supports 4K tokens whereas Gemini 4 Argon supports 1M tokens.

AI Terminology & Guide
Explore Glossary →

Understand key metrics like context window, token pricing, reasoning mode, and SWE-bench scores in our comprehensive AI glossary.

Benchmark scores, token prices, and rate limits evolve rapidly as AI labs release model updates. Always verify current specifications and pricing on the official provider documentation.

المصادر الرسمية: OpenAI & Google Official Documentation