Head-to-Head Model Comparison

GPT-4 Turbo vs Gemini 4 Argon

Benchmarks, API Token Pricing, Context Window & Speed Comparison

Vérifié par l’équipe de recherche de GetInfoUsDernière révision : October 2026Politique éditoriale
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Compare GPT-4 Turbo by OpenAI against Gemini 4 Argon by Google across real-world coding, reasoning, token economics, and latency.

Comparaison Face-à-Face (VS)

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GPT-4 Turbo

Bourreau de production 128K

Major architectural upgrade intégrant un 128K fenêtre de contexte, natif vision intégration, reproducible JSON mode, et significantly reduced API tarification.

Intelligence Index40 / 100
Input Token:

$10.00 / 1M

Output Token:

$30.00 / 1M

Context Window:

128K tokens

SWE-bench Verified:

27.5%

Google

Gemini 4 Argon

Roi multimodal avec sortie 1M

Google de DeepMind phare de pointe raisonnement moteur intégrant 1-millions-token sortie limits, autonome cybersecurity defense, et en temps réel audio/vision ingestion.

Intelligence Index97 / 100
Input Token:

$2.00 / 1M

Output Token:

$10.00 / 1M

Context Window:

1M tokens

SWE-bench Verified:

81.9%

Différences Clés en un Coup d’Œil

  • Gemini 4 Argon is 4.1x cheaper for API usage (input + output tokens combined).
  • Gemini 4 Argon has a larger context window (1M vs 128K tokens).
  • Gemini 4 Argon is faster at 115 tok/s vs 55 tok/s.
  • Gemini 4 Argon leads on SWE-bench coding (81.9% vs 27.5%).
Need definitions for token pricing, context, or benchmarks?Explore AI Glossary →
CaractéristiqueGPT-4 TurboGemini 4 Argon
Intelligence Index
Composite reasoning & knowledge score (0-100)
4097
Provider
OpenAIGoogle
Input Price
Cost per million input tokens
$10.00 / 1M$2.00 / 1M
Output Price
Cost per million output tokens
$30.00 / 1M$10.00 / 1M
Blended Price
Weighted 7:2:1 cache:input:output per 1M
$8.50 / 1M$1.47 / 1M
Context Window
Maximum input + output tokens
128K tokens~192 A4 pages of text1M tokens~1,500 A4 pages of text
Max Output Tokens
Per single request
4K1000K
Throughput Speed
Tokens generated per second
55 tok/s115 tok/s
SWE-bench Verified
Real-world software engineering
27.5%81.9%
GPQA Diamond
Graduate-level reasoning
48%81.5%
Cached Input Price
Prompt caching discount per 1M tokens
$5.00 / 1M$0.10 / 1M

Qui gagne où ?

At-a-glance decision framework
Code
Gemini 4 Argon
+54.4% SWE-bench lead
Coût
Gemini 4 Argon
4.1x cheaper monthly runtime
Vitesse
Gemini 4 Argon
+109% faster generation
Contexte
Gemini 4 Argon
1M tokens window

Scores de Benchmarks Vérifiés

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

GPT-4 TurboGemini 4 Argon
SWE-bench Verified (Autonomous Coding)

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

27.5%vs81.9%
GPQA Diamond (Doctorate-Level Science & Math)

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

48%vs81.5%
MMLU-Pro (Multi-task Language Understanding)

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

70.5%vs90.8%
LMSYS Chatbot Arena Elo

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

1248ptsvs1525pts
Humanity's Last Exam (Frontier Expert Knowledge)

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

N/Avs18.9%
Terminal-Bench (Agentic Coding & Terminal Use)

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

N/Avs57.4%
SciCode (Scientific Computing)

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

N/Avs56.4%
LiveCodeBench (Competitive Coding)

Contamination-free competitive programming problems collected continuously over time.

N/Avs80.5%
AIME (Advanced Math Competition)

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

N/Avs94.8%
Long-Context Reasoning

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

N/Avs96.4%
Generation Speed (Throughput)

Tokens emitted per second during active generation streaming.

55 tok/s vs115 tok/s

Latence et Temps de Réponse

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-4 Turbo0.65s
Gemini 4 Argon0.85s
Est. End-to-End Response (500 tokens)TTFT + generation time
GPT-4 Turbo9.74s
Gemini 4 Argon5.20s

Simulateur Interactif de Coût de Tokens

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-4 Turbo Monthly API Bill
$49.50 / month
$10/1M in · $30/1M out
Gemini 4 Argon Monthly API Bill
$12.15 / month
$2/1M in · $10/1M out
Gemini 4 Argon saves approximately $37.35 / month (75%) under this workload.4.1x Savings

GPT-4 Turbo · Strengths & Key Advantages

  • 128,000 token fenêtre de contexte capable d'ingesting entire books et documentation suites
  • Sharp 3x prix reduction d'original GPT-4
  • fiable JSON object mode et parallel appel d'outils
Considerations & Trade-offs
  • Max sortie capped à 4,096 tokens
  • Outpaced dans débit par subsequent GPT-4o omni releases

Gemini 4 Argon · Strengths & Key Advantages

  • Groundbreaking 1,000,000 token maximum sortie génération capacité via long Decode Continuation
  • 1M-token entrée window avec 99.7% GraphWalks recall (84.2% dans le 256K-1M range)
  • natif traitement de complet audio, vidéo streams, et visuel données (91.7% sur LVBench)
  • Half le token prix de d'Anthropic Opus 5.5 et #1 sur Chatbot Arena (1525 Elo)
Considerations & Trade-offs
  • massif token outputs peut incur élevé absolute coûts if unconstrained (~62K sortie tokens par index tâche)
  • $2/$10 tarification est un introductory 50% discount; standard rates revert à $4/$20 once le promotion ends

Token Use & Task Economics

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

MetricGPT-4 TurboGemini 4 Argon
Cost per Task
Estimated USD to finish one task
$0.20$2.45
Output Tokens / Task
Tokens generated per task
24K75K
Reasoning Tokens / Task
Thinking tokens burned per task
0K36K

Spécifications Techniques

Architecture, release timeline, capabilities, and modalities.

CaractéristiqueGPT-4 TurboGemini 4 Argon
Official API Model ID (SDK)gpt-4-turbomodels/gemini-4-argon
API ProtocolOpenAI Responses API & Chat Completions v1Google Gemini API (generateContent) + OpenAI-Compatible SDK
Release Date2023-112026-09
Knowledge CutoffDecember 2023June 2026
ArchitectureOptimized Sparse MoEPathways 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 ($10/1M in) across full 128K windowStandard rate up to 200K tokens; 2x input/output tier above 200K tokens
Prompt Cache Policy & TTLAutomatic prefix caching at $5/1M (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 CallingNative MCP Client/Server ready · Parallel function calling · 100% Strict JSON SchemaNative 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 Modalitiestexttext

GPT-4 Turbo vs Gemini 4 Argon: Réponses Rapides (FAQ)

Which is more intelligent, GPT-4 Turbo or Gemini 4 Argon?

Gemini 4 Argon is more intelligent. It scores 97 compared with 40 on the composite Intelligence Index.

Which model is faster?

Gemini 4 Argon is faster, generating 115 tokens per second compared with 55 tokens per second.

Which model is cheaper to run?

Gemini 4 Argon is cheaper at $1.47 per 1M tokens blended, compared with $8.50 (7:2:1 cache:input:output ratio).

Which model has lower latency?

GPT-4 Turbo has lower latency, with a time to first token of 0.65s compared with 0.85s.

Which model has a larger context window?

Gemini 4 Argon has a larger context window, supporting 1M tokens compared with 128K tokens.

Verdict

Choose GPT-4 Turbo for d'entreprise document revue, production agent orchestration, et au format long visuel analyse, or choose Gemini 4 Argon for whole-dépôt génération de code, complet-book synthèse, vidéo compréhension, et multi-hour audio traitement.

Questions fréquentes

Which is cheaper: GPT-4 Turbo or Gemini 4 Argon?+

GPT-4 Turbo costs $10/1M input and $30/1M output tokens, while Gemini 4 Argon costs $2/1M input and $10/1M output tokens.

Which model has a larger context window: GPT-4 Turbo or Gemini 4 Argon?+

GPT-4 Turbo supports 128K 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.

Les scores de benchmarks, tarifs par token et limites évoluent rapidement. Vérifiez toujours les spécifications actuelles sur la documentation officielle du fournisseur.

Sources: OpenAI & Google Official Documentation