Head-to-Head Model Comparison

GPT-5 vs Claude Opus 5.5

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-5 by OpenAI against Claude Opus 5.5 by Anthropic across real-world coding, reasoning, token economics, and latency.

Comparaison Face-à-Face (VS)

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OpenAI

GPT-5

Moteur de Raisonnement Profond

GPT-5 de OpenAI est un modèle d’IA conçu pour le raisonnement logique profond, les mathématiques formelles et l’analyse scientifique, offrant une fenêtre de contexte de 400K, une vitesse de 135 tokens/s, un indice d’intelligence de 58/100 e

Intelligence Index58 / 100
Input Token:

$1.25 / 1M

Output Token:

$10.00 / 1M

Context Window:

400K tokens

SWE-bench Verified:

74.9%

Anthropic

Claude Opus 5.5

Modèle Phare de Pointe

Claude Opus 5.5 de Anthropic est un modèle d’IA conçu pour le raisonnement d’entreprise de pointe, l’ingénierie logicielle et la production IA, offrant une fenêtre de contexte de 1M, une vitesse de 78 tokens/s, un indice d’intelligence de 9

Intelligence Index94 / 100
Input Token:

$4.00 / 1M

Output Token:

$20.00 / 1M

Context Window:

1M tokens

SWE-bench Verified:

84.6%

Différences Clés en un Coup d’Œil

  • GPT-5 is 2.2x cheaper for API usage (input + output tokens combined).
  • Claude Opus 5.5 has a larger context window (1M vs 400K tokens).
  • GPT-5 is faster at 135 tok/s vs 78 tok/s.
  • Claude Opus 5.5 leads on SWE-bench coding (84.6% vs 74.9%).
Need definitions for token pricing, context, or benchmarks?Explore AI Glossary →
CaractéristiqueGPT-5Claude Opus 5.5
Intelligence Index
Composite reasoning & knowledge score (0-100)
5894
Provider
OpenAIAnthropic
Input Price
Cost per million input tokens
$1.25 / 1M$4.00 / 1M
Output Price
Cost per million output tokens
$10.00 / 1M$20.00 / 1M
Blended Price
Weighted 7:2:1 cache:input:output per 1M
$1.34 / 1M$3.08 / 1M
Context Window
Maximum input + output tokens
400K tokens~600 A4 pages of text1M tokens~1,500 A4 pages of text
Max Output Tokens
Per single request
128K128K
Throughput Speed
Tokens generated per second
135 tok/s78 tok/s
SWE-bench Verified
Real-world software engineering
74.9%84.6%
GPQA Diamond
Graduate-level reasoning
85.7%82.3%
Cached Input Price
Prompt caching discount per 1M tokens
$0.13 / 1M$0.40 / 1M

Qui gagne où ?

At-a-glance decision framework
Code
Claude Opus 5.5
+9.7% SWE-bench lead
Coût
GPT-5
2.2x cheaper monthly runtime
Vitesse
GPT-5
+73% faster generation
Contexte
Claude Opus 5.5
1M tokens window

Scores de Benchmarks Vérifiés

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

GPT-5Claude Opus 5.5
SWE-bench Verified (Autonomous Coding)

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

74.9%vs84.6%
GPQA Diamond (Doctorate-Level Science & Math)

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

85.7%vs82.3%
MMLU-Pro (Multi-task Language Understanding)

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

86.5%vs91.5%
LMSYS Chatbot Arena Elo

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

1366ptsvs1507pts
Humanity's Last Exam (Frontier Expert Knowledge)

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

12.5%vs19.8%
Terminal-Bench (Agentic Coding & Terminal Use)

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

45%vs66.4%
SciCode (Scientific Computing)

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

42.8%vs58.7%
LiveCodeBench (Competitive Coding)

Contamination-free competitive programming problems collected continuously over time.

71%vs83.1%
AIME (Advanced Math Competition)

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

94.6%vs95.4%
Long-Context Reasoning

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

78%vs92.6%
Generation Speed (Throughput)

Tokens emitted per second during active generation streaming.

135 tok/s vs78 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-51.15s
Claude Opus 5.51.40s
Est. End-to-End Response (500 tokens)TTFT + generation time
GPT-54.85s
Claude Opus 5.57.81s

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-5 Monthly API Bill
$11.06 / month
$1.25/1M in · $10/1M out
Claude Opus 5.5 Monthly API Bill
$24.60 / month
$4/1M in · $20/1M out
GPT-5 saves approximately $13.54 / month (55%) under this workload.2.2x Savings

GPT-5 · Strengths & Key Advantages

  • Fenêtre de contexte de 400K et capacité de sortie maximale de 128K tokens (SWE-bench Verified 74.9% · GPQA Diamond 85.7%)
  • Débit rapide de 135 tokens/seconde avec une latence au premier token (TTFT) de 1150 ms
  • Tarification API optimisée ($1.25/$10 par million de tokens) avec prise en charge du cache de prompts et des schémas JSON stricts
Considerations & Trade-offs
  • Modèle cloud propriétaire ne permettant pas le téléchargement local des poids sur serveur isolé
  • Sur les problèmes de recherche fondamentale très complexes, les modèles de raisonnement lourd restent supérieurs

Claude Opus 5.5 · Strengths & Key Advantages

  • Fenêtre de contexte de 1M et capacité de sortie maximale de 128K tokens (SWE-bench Verified 84.6% · GPQA Diamond 82.3%)
  • Débit rapide de 78 tokens/seconde avec une latence au premier token (TTFT) de 1400 ms
  • Tarification API optimisée ($4/$20 par million de tokens) avec prise en charge du cache de prompts et des schémas JSON stricts
Considerations & Trade-offs
  • Modèle cloud propriétaire ne permettant pas le téléchargement local des poids sur serveur isolé
  • Pour les charges à très fort volume, l’activation du cache de prompts et de l’API Batch est recommandée

Token Use & Task Economics

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

MetricGPT-5Claude Opus 5.5
Cost per Task
Estimated USD to finish one task
$1.55$3.85
Output Tokens / Task
Tokens generated per task
55K68K
Reasoning Tokens / Task
Thinking tokens burned per task
29K42K

Spécifications Techniques

Architecture, release timeline, capabilities, and modalities.

CaractéristiqueGPT-5Claude Opus 5.5
Official API Model ID (SDK)gpt-5claude-opus-5-5-20260901
API ProtocolOpenAI Responses API & Chat Completions v1Anthropic Messages API + AWS Bedrock + Vertex AI
Release Date2025-082026-09
Knowledge CutoffSeptember 2024June 2026
ArchitectureUnified reasoning model (fast + thinking modes)Extended Autonomous Hybrid Reasoning Transformer
ParametersConfidentialConfidential
Enterprise Rate Limits (RPM / TPM)10,000 – 30,000 RPM (Tier 5 Enterprise) · 800,000 – 2,000,000 TPM4,000 – 10,000 RPM (Tier 4 + Priority Tier) · 4,000,000 – 10,000,000 TPM
Long-Context Tier (>128K/200K)Flat rate ($1.25/1M in) across full 400K windowStandard rate up to 200K tokens; 2x input/output tier above 200K tokens
Prompt Cache Policy & TTLAutomatic prefix caching at $0.125/1M (no extra cache-write fee)$0.4/1M cached read (90% off); 5-min default & 1-hour extended 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 RAGNative Web Search Citations + Code Execution Tool + MCP Connectors
Official Fine-Tuning SupportSupervised Fine-Tuning (SFT), Direct Preference (DPO) & Reinforcement Fine-Tuning (RFT)Custom Model Tuning via Amazon Bedrock & Prompt 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)
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 PublishedAnthropic RSP ASL-2 / ASL-3 Constitutional Safety Evaluated
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
Output Modalitiestexttext

GPT-5 vs Claude Opus 5.5: Réponses Rapides (FAQ)

Which is more intelligent, GPT-5 or Claude Opus 5.5?

Claude Opus 5.5 is more intelligent. It scores 94 compared with 58 on the composite Intelligence Index.

Which model is faster?

GPT-5 is faster, generating 135 tokens per second compared with 78 tokens per second.

Which model is cheaper to run?

GPT-5 is cheaper at $1.34 per 1M tokens blended, compared with $3.08 (7:2:1 cache:input:output ratio).

Which model has lower latency?

GPT-5 has lower latency, with a time to first token of 1.15s compared with 1.40s.

Which model has a larger context window?

Claude Opus 5.5 has a larger context window, supporting 1M tokens compared with 400K tokens.

Verdict

Choose GPT-5 for conçu pour le raisonnement logique profond, les mathématiques formelles et l’analyse scientifique, l’intégration rag et les pipelines de production évolutifs., or choose Claude Opus 5.5 for conçu pour le raisonnement d’entreprise de pointe, l’ingénierie logicielle et la production ia, l’intégration rag et les pipelines de production évolutifs..

Questions fréquentes

Which is cheaper: GPT-5 or Claude Opus 5.5?+

GPT-5 costs $1.25/1M input and $10/1M output tokens, while Claude Opus 5.5 costs $4/1M input and $20/1M output tokens.

Which model has a larger context window: GPT-5 or Claude Opus 5.5?+

GPT-5 supports 400K tokens whereas Claude Opus 5.5 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 & Anthropic Official Documentation