Head-to-Head Model Comparison

GPT-4.5 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-4.5 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-4.5

Géant d'avant le raisonnement

d'OpenAI largest dense modèle — stronger général intelligence et monde knowledge sans un raisonnement mode.

Intelligence Index46 / 100
Input Token:

$75.00 / 1M

Output Token:

$150.00 / 1M

Context Window:

128K tokens

SWE-bench Verified:

42%

Anthropic

Claude Opus 5.5

Titan d'intelligence de pointe

d'Anthropic pinnacle modèle de pointe conçu pour à long terme agentic ingénierie logicielle, dense multimodal document synthèse, et autonome recherche flux de travail.

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

  • Claude Opus 5.5 is 11.2x cheaper for API usage (input + output tokens combined).
  • Claude Opus 5.5 has a larger context window (1M vs 128K tokens).
  • Claude Opus 5.5 is faster at 78 tok/s vs 45 tok/s.
  • Claude Opus 5.5 leads on SWE-bench coding (84.6% vs 42.0%).
Need definitions for token pricing, context, or benchmarks?Explore AI Glossary →
CaractéristiqueGPT-4.5Claude Opus 5.5
Intelligence Index
Composite reasoning & knowledge score (0-100)
4694
Provider
OpenAIAnthropic
Input Price
Cost per million input tokens
$75.00 / 1M$4.00 / 1M
Output Price
Cost per million output tokens
$150.00 / 1M$20.00 / 1M
Blended Price
Weighted 7:2:1 cache:input:output per 1M
$43.13 / 1M$3.08 / 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
16K128K
Throughput Speed
Tokens generated per second
45 tok/s78 tok/s
SWE-bench Verified
Real-world software engineering
42%84.6%
GPQA Diamond
Graduate-level reasoning
66.5%82.3%
Cached Input Price
Prompt caching discount per 1M tokens
$18.75 / 1M$0.40 / 1M

Qui gagne où ?

At-a-glance decision framework
Code
Claude Opus 5.5
+42.6% SWE-bench lead
Coût
Claude Opus 5.5
11.2x cheaper monthly runtime
Vitesse
Claude Opus 5.5
+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-4.5Claude Opus 5.5
SWE-bench Verified (Autonomous Coding)

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

42%vs84.6%
GPQA Diamond (Doctorate-Level Science & Math)

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

66.5%vs82.3%
MMLU-Pro (Multi-task Language Understanding)

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

81.5%vs91.5%
LMSYS Chatbot Arena Elo

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

1332ptsvs1507pts
Humanity's Last Exam (Frontier Expert Knowledge)

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

9.4%vs19.8%
Terminal-Bench (Agentic Coding & Terminal Use)

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

25%vs66.4%
SciCode (Scientific Computing)

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

34.5%vs58.7%
LiveCodeBench (Competitive Coding)

Contamination-free competitive programming problems collected continuously over time.

56%vs83.1%
AIME (Advanced Math Competition)

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

60%vs95.4%
Long-Context Reasoning

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

68%vs92.6%
Generation Speed (Throughput)

Tokens emitted per second during active generation streaming.

45 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-4.51.60s
Claude Opus 5.51.40s
Est. End-to-End Response (500 tokens)TTFT + generation time
GPT-4.512.71s
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-4.5 Monthly API Bill
$275.63 / month
$75/1M in · $150/1M out
Claude Opus 5.5 Monthly API Bill
$24.60 / month
$4/1M in · $20/1M out
Claude Opus 5.5 saves approximately $251.03 / month (91%) under this workload.11.2x Savings

GPT-4.5 · Strengths & Key Advantages

  • Exceptionally natural, créatif et emotionally fluent writing
  • faible hallucination rate par rapport à son génération
  • Broad monde knowledge et Excellent suivi des instructions
  • Notably meilleur à nuance, humour et emotional register que GPT-4
Considerations & Trade-offs
  • Extremely expensive à $75 / $150 par 1M tokens
  • No raisonnement mode — beaten par o-series et GPT-5 sur hard tâches
  • Withdrawn du API dans July 2025

Claude Opus 5.5 · Strengths & Key Advantages

  • inégalé autonome multi-étapes codage agentique et refactorisation
  • Flawless multidocument raisonnement sur 1M token contexte avec no long-prompt surcharge
  • le plus élevé Artificial analyse intelligence Index ever measured (58/100), leading SWE-bench Pro à 89.9%
  • Precise outil exécution avec robust error-recovery boucles
Considerations & Trade-offs
  • Premium sortie tarification ($20.00/M) plus heavy raisonnement-token usage (~119K sortie tokens par index tâche) keeps long agentic fonctionne expensive
  • long pensée times à maximum effort peut push un unique hard agentic tâche toward ~$13

Token Use & Task Economics

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

MetricGPT-4.5Claude Opus 5.5
Cost per Task
Estimated USD to finish one task
$17.85$3.85
Output Tokens / Task
Tokens generated per task
55K68K
Reasoning Tokens / Task
Thinking tokens burned per task
0K42K

Spécifications Techniques

Architecture, release timeline, capabilities, and modalities.

CaractéristiqueGPT-4.5Claude Opus 5.5
Official API Model ID (SDK)gpt-4-5claude-opus-5-5-20260901
API ProtocolOpenAI Responses API & Chat Completions v1Anthropic Messages API + AWS Bedrock + Vertex AI
Release Date2025-022026-09
Knowledge CutoffOctober 2023June 2026
ArchitectureLarge dense pre-reasoning transformerExtended 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 ($75/1M in) across full 128K windowStandard rate up to 200K tokens; 2x input/output tier above 200K tokens
Prompt Cache Policy & TTLAutomatic prefix caching at $18.75/1M (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-4.5 vs Claude Opus 5.5: Réponses Rapides (FAQ)

Which is more intelligent, GPT-4.5 or Claude Opus 5.5?

Claude Opus 5.5 is more intelligent. It scores 94 compared with 46 on the composite Intelligence Index.

Which model is faster?

Claude Opus 5.5 is faster, generating 78 tokens per second compared with 45 tokens per second.

Which model is cheaper to run?

Claude Opus 5.5 is cheaper at $3.08 per 1M tokens blended, compared with $43.13 (7:2:1 cache:input:output ratio).

Which model has lower latency?

Claude Opus 5.5 has lower latency, with a time to first token of 1.40s compared with 1.60s.

Which model has a larger context window?

Claude Opus 5.5 has a larger context window, supporting 1M tokens compared with 128K tokens.

Verdict

Choose GPT-4.5 for créatif et editorial writing où ton matters plus que coût, or choose Claude Opus 5.5 for grand-échelle logiciel development agents, d'entreprise codebases, et mission critique scientifique synthèse.

Questions fréquentes

Which is cheaper: GPT-4.5 or Claude Opus 5.5?+

GPT-4.5 costs $75/1M input and $150/1M output tokens, while Claude Opus 5.5 costs $4/1M input and $20/1M output tokens.

Which model has a larger context window: GPT-4.5 or Claude Opus 5.5?+

GPT-4.5 supports 128K 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