Head-to-Head Model Comparison

Claude Opus 4.5 vs GPT-6 Astra

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 Claude Opus 4.5 by Anthropic against GPT-6 Astra by OpenAI across real-world coding, reasoning, token economics, and latency.

Comparaison Face-à-Face (VS)

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Anthropic

Claude Opus 4.5

Leader en qualité

Le modèle phare de référence en qualité d'Anthropic offrant un raisonnement de pointe et une créativité remarquable pour un coût 66% inférieur à Opus 4.1.

Intelligence Index63 / 100
Input Token:

$5.00 / 1M

Output Token:

$25.00 / 1M

Context Window:

200K tokens

SWE-bench Verified:

77.2%

OpenAI

GPT-6 Astra

Agent d'OS autonome

d'OpenAI late-2026 phare modèle de fondation intégrant natif utilisation de l'ordinateur agents, dynamic UI orchestration, et profond STEM raisonnement.

Intelligence Index96 / 100
Input Token:

$10.00 / 1M

Output Token:

$50.00 / 1M

Context Window:

272K tokens

SWE-bench Verified:

82.4%

Différences Clés en un Coup d’Œil

  • Claude Opus 4.5 is 2.0x cheaper for API usage (input + output tokens combined).
  • GPT-6 Astra has a larger context window (272K vs 200K tokens).
  • GPT-6 Astra is faster at 100 tok/s vs 62 tok/s.
  • GPT-6 Astra leads on SWE-bench coding (82.4% vs 77.2%).
Need definitions for token pricing, context, or benchmarks?Explore AI Glossary →
CaractéristiqueClaude Opus 4.5GPT-6 Astra
Intelligence Index
Composite reasoning & knowledge score (0-100)
6396
Provider
AnthropicOpenAI
Input Price
Cost per million input tokens
$5.00 / 1M$10.00 / 1M
Output Price
Cost per million output tokens
$25.00 / 1M$50.00 / 1M
Blended Price
Weighted 7:2:1 cache:input:output per 1M
$3.85 / 1M$7.70 / 1M
Context Window
Maximum input + output tokens
200K tokens~300 A4 pages of text272K tokens~408 A4 pages of text
Max Output Tokens
Per single request
64K128K
Throughput Speed
Tokens generated per second
62 tok/s100 tok/s
SWE-bench Verified
Real-world software engineering
77.2%82.4%
GPQA Diamond
Graduate-level reasoning
74.8%80.9%
Cached Input Price
Prompt caching discount per 1M tokens
$0.50 / 1M$1.00 / 1M

Qui gagne où ?

At-a-glance decision framework
Code
GPT-6 Astra
+5.2% SWE-bench lead
Coût
Claude Opus 4.5
2.0x cheaper monthly runtime
Vitesse
GPT-6 Astra
+61% faster generation
Contexte
GPT-6 Astra
272K tokens window

Scores de Benchmarks Vérifiés

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

Claude Opus 4.5GPT-6 Astra
SWE-bench Verified (Autonomous Coding)

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

77.2%vs82.4%
GPQA Diamond (Doctorate-Level Science & Math)

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

74.8%vs80.9%
MMLU-Pro (Multi-task Language Understanding)

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

87.3%vs89.9%
LMSYS Chatbot Arena Elo

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

1376ptsvs1520pts
Humanity's Last Exam (Frontier Expert Knowledge)

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

13.7%vs18.2%
Terminal-Bench (Agentic Coding & Terminal Use)

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

49.2%vs63.8%
SciCode (Scientific Computing)

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

45.6%vs54.9%
LiveCodeBench (Competitive Coding)

Contamination-free competitive programming problems collected continuously over time.

74.1%vs79.8%
AIME (Advanced Math Competition)

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

88.5%vs93.6%
Long-Context Reasoning

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

79.4%vs91.2%
Generation Speed (Throughput)

Tokens emitted per second during active generation streaming.

62 tok/s vs100 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
Claude Opus 4.52.10s
GPT-6 Astra0.95s
Est. End-to-End Response (500 tokens)TTFT + generation time
Claude Opus 4.510.16s
GPT-6 Astra5.95s

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)
Claude Opus 4.5 Monthly API Bill
$30.75 / month
$5/1M in · $25/1M out
GPT-6 Astra Monthly API Bill
$61.50 / month
$10/1M in · $50/1M out
Claude Opus 4.5 saves approximately $30.75 / month (50%) under this workload.2.0x Savings

Claude Opus 4.5 · Strengths & Key Advantages

  • meilleur-dans-classe complexe raisonnement et nuanced analyse
  • 66% cheaper que Opus 4.1 tandis que keeping phare qualité
  • Excellent au format long créatif et élevé-stakes decision sortie
  • 90% cached-entrée discount ($0.50 par 1M tokens)
Considerations & Trade-offs
  • le plus élevé sortie prix ($25/1M) among mainstream flagships
  • Slower débit et supérieur latence que léger modèles

GPT-6 Astra · Strengths & Key Advantages

  • Flawless OS-level navigation et utilisation de l'ordinateur automatisation
  • Seamless en temps réel multimodal voix et vision interactivity
  • Dynamic chaîne de pensée qui self-adjusts profondeur based sur query difficulty
  • immense 1M fenêtre de contexte avec instant prefix caching
Considerations & Trade-offs
  • Strict sécurité filters peut occasionally throttle complexe penetration testing prompts
  • Slightly supérieur raisonnement latence sur élevé-effort mathématiques queries

Token Use & Task Economics

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

MetricClaude Opus 4.5GPT-6 Astra
Cost per Task
Estimated USD to finish one task
$5.86$2.15
Output Tokens / Task
Tokens generated per task
73K58K
Reasoning Tokens / Task
Thinking tokens burned per task
43K32K

Spécifications Techniques

Architecture, release timeline, capabilities, and modalities.

CaractéristiqueClaude Opus 4.5GPT-6 Astra
Official API Model ID (SDK)claude-opus-4-5-20251101gpt-6-astra
API ProtocolAnthropic Messages API + AWS Bedrock + Vertex AIOpenAI Responses API & Chat Completions v1
Release Date2025-112026-09
Knowledge CutoffMarch 2025June 2026
ArchitectureHybrid ReasoningOmni-Adaptive Autoregressive with Dynamic CoT
ParametersConfidentialConfidential
Enterprise Rate Limits (RPM / TPM)4,000 – 10,000 RPM (Tier 4 + Priority Tier) · 800,000 – 2,000,000 TPM10,000 – 30,000 RPM (Tier 5 Enterprise) · 800,000 – 2,000,000 TPM
Long-Context Tier (>128K/200K)Standard rate up to 200K tokens; 2x input/output tier above 200K tokensFlat rate ($10/1M in) across full 272K window
Prompt Cache Policy & TTL$0.5/1M cached read (90% off); 5-min default & 1-hour extended TTLAutomatic prefix caching at $1/1M (no extra cache-write fee)
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 Citations + Code Execution Tool + MCP ConnectorsNative Web Search tool + Hosted Code Interpreter & File Search RAG
Official Fine-Tuning SupportCustom Model Tuning via Amazon Bedrock & Prompt DistillationSupervised Fine-Tuning (SFT), Direct Preference (DPO) & Reinforcement Fine-Tuning (RFT)
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)
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 ClassificationAnthropic RSP ASL-2 / ASL-3 Constitutional Safety EvaluatedOpenAI Preparedness Framework Audited & System Card Published
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
Output Modalitiestexttext, audio

Claude Opus 4.5 vs GPT-6 Astra: Réponses Rapides (FAQ)

Which is more intelligent, Claude Opus 4.5 or GPT-6 Astra?

GPT-6 Astra is more intelligent. It scores 96 compared with 63 on the composite Intelligence Index.

Which model is faster?

GPT-6 Astra is faster, generating 100 tokens per second compared with 62 tokens per second.

Which model is cheaper to run?

Claude Opus 4.5 is cheaper at $3.85 per 1M tokens blended, compared with $7.70 (7:2:1 cache:input:output ratio).

Which model has lower latency?

GPT-6 Astra has lower latency, with a time to first token of 0.95s compared with 2.10s.

Which model has a larger context window?

GPT-6 Astra has a larger context window, supporting 272K tokens compared with 200K tokens.

Verdict

Choose Claude Opus 4.5 for analyses juridiques et financières critiques, refactorisation complexe de code et rédaction créative, or choose GPT-6 Astra for autonome browser/computer flux de travail, en temps réel voix agents, et élevé-difficulty mathématique raisonnement.

Questions fréquentes

Which is cheaper: Claude Opus 4.5 or GPT-6 Astra?+

Claude Opus 4.5 costs $5/1M input and $25/1M output tokens, while GPT-6 Astra costs $10/1M input and $50/1M output tokens.

Which model has a larger context window: Claude Opus 4.5 or GPT-6 Astra?+

Claude Opus 4.5 supports 200K tokens whereas GPT-6 Astra supports 272K 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: Anthropic & OpenAI Official Documentation