Head-to-Head Model Comparison

o3 vs Claude Opus 4.5

Benchmarks, API Token Pricing, Context Window & Speed Comparison

Verificato dal team di ricerca di GetInfoUsUltima verifica: October 2026Politica editoriale
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AI CompareAI BenchmarkToken PricingModel CostModel SpecsSWE-bench CodingModel VersusWhich AI ModelLLM Speed & LatencyReasoning ModelsExtended ThinkingPrompt Caching ROI
o3 vs Claude Opus 4.5: Benchmarks, Pricing & Speed Comparison

o3 di OpenAI e Claude Opus 4.5 di Anthropic sono due modelli di IA di riferimento. o3 offre una finestra di contesto di 200K token a $2.00/$8.00 per milione di token, mentre Claude Opus 4.5 mette a disposizione 200K token di contesto a $5.00/$25.00 per milione di token. Di seguito analizziamo benchmark, latenza e costi.

Confronto Diretto (VS)

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o3

Motore di Ragionamento Profondo

o3 di OpenAI è un modello di IA progettato per il ragionamento logico profondo, la matematica avanzata e l’analisi scientifica, con finestra di contesto da 200K, velocità di 75 token/s, indice di intelligenza di 56/100 e tariffa di $2/$8 pe

Intelligence Index56 / 100
Input Token:

$2.00 / 1M

Output Token:

$8.00 / 1M

Context Window:

200K tokens

SWE-bench Verified:

69.1%

Anthropic

Claude Opus 4.5

Modello Ammiraglia di Frontiera

Claude Opus 4.5 di Anthropic è un modello di IA progettato per il ragionamento aziendale di frontiera, la programmazione avanzata e i carichi di produzione, con finestra di contesto da 200K, velocità di 62 token/s, indice di intelligenza di

Intelligence Index63 / 100
Input Token:

$5.00 / 1M

Output Token:

$25.00 / 1M

Context Window:

200K tokens

SWE-bench Verified:

77.2%

Differenze Chiave a Colpo d’Occhio

  • o3 is 2.8x cheaper for API usage (input + output tokens combined).
  • o3 is faster at 75 tok/s vs 62 tok/s.
  • Claude Opus 4.5 leads on SWE-bench coding (77.2% vs 69.1%).
Need definitions for token pricing, context, or benchmarks?Explore AI Glossary →
Featureo3Claude Opus 4.5
Intelligence Index
Composite reasoning & knowledge score (0-100)
5663
Provider
OpenAIAnthropic
Input Price
Cost per million input tokens
$2.00 / 1M$5.00 / 1M
Output Price
Cost per million output tokens
$8.00 / 1M$25.00 / 1M
Blended Price
Weighted 7:2:1 cache:input:output per 1M
$1.55 / 1M$3.85 / 1M
Context Window
Maximum input + output tokens
200K tokens~300 A4 pages of text200K tokens~300 A4 pages of text
Max Output Tokens
Per single request
100K64K
Throughput Speed
Tokens generated per second
75 tok/s62 tok/s
SWE-bench Verified
Real-world software engineering
69.1%77.2%
GPQA Diamond
Graduate-level reasoning
76.5%74.8%
Cached Input Price
Prompt caching discount per 1M tokens
$0.50 / 1M$0.50 / 1M

Chi vince in ogni categoria?

At-a-glance decision framework
Coding
Claude Opus 4.5
+8.1% SWE-bench lead
Cost
o3
2.8x cheaper monthly runtime
Speed
o3
+21% faster generation
Context
Tied
200K tokens window

Punteggi Benchmark Verificati

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

o3Claude Opus 4.5
SWE-bench Verified (Autonomous Coding)

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

69.1%vs77.2%
GPQA Diamond (Doctorate-Level Science & Math)

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

76.5%vs74.8%
MMLU-Pro (Multi-task Language Understanding)

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

87%vs87.3%
LMSYS Chatbot Arena Elo

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

1345ptsvs1376pts
Humanity's Last Exam (Frontier Expert Knowledge)

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

12.9%vs13.7%
Terminal-Bench (Agentic Coding & Terminal Use)

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

42%vs49.2%
SciCode (Scientific Computing)

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

42.5%vs45.6%
LiveCodeBench (Competitive Coding)

Contamination-free competitive programming problems collected continuously over time.

70.5%vs74.1%
AIME (Advanced Math Competition)

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

91.6%vs88.5%
Long-Context Reasoning

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

78.5%vs79.4%
Generation Speed (Throughput)

Tokens emitted per second during active generation streaming.

75 tok/s vs62 tok/s

Latenza e Tempo di Risposta

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
o32.80s
Claude Opus 4.52.10s
Est. End-to-End Response (500 tokens)TTFT + generation time
o39.47s
Claude Opus 4.510.16s

Simulatore Interattivo dei Costi Token

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)
o3 Monthly API Bill
$10.95 / month
$2/1M in · $8/1M out
Claude Opus 4.5 Monthly API Bill
$30.75 / month
$5/1M in · $25/1M out
o3 saves approximately $19.80 / month (64%) under this workload.2.8x Savings

o3 · Strengths & Key Advantages

  • Finestra di contesto da 200K con capacità massima di output fino a 100K token (SWE-bench Verified 69.1% · GPQA Diamond 76.5%)
  • Throughput elevato di 75 token/secondo con latenza al primo token (TTFT) di soli 2800 ms
  • Economia API competitiva ($2/$8 per 1M di token) con supporto per prompt caching, tool calling e output JSON strutturati
Considerations & Trade-offs
  • Modello cloud proprietario chiuso; non consente il download locale dei pesi per l’esecuzione offline
  • Per volumi di traffico elevati in produzione si consiglia di attivare il prompt caching e la Batch API

Claude Opus 4.5 · Strengths & Key Advantages

  • Finestra di contesto da 200K con capacità massima di output fino a 64K token (SWE-bench Verified 77.2% · GPQA Diamond 74.8%)
  • Throughput elevato di 62 token/secondo con latenza al primo token (TTFT) di soli 2100 ms
  • Economia API competitiva ($5/$25 per 1M di token) con supporto per prompt caching, tool calling e output JSON strutturati
Considerations & Trade-offs
  • Modello cloud proprietario chiuso; non consente il download locale dei pesi per l’esecuzione offline
  • Per volumi di traffico elevati in produzione si consiglia di attivare il prompt caching e la Batch API

Token Use & Task Economics

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

Metrico3Claude Opus 4.5
Cost per Task
Estimated USD to finish one task
$1.35$5.86
Output Tokens / Task
Tokens generated per task
48K73K
Reasoning Tokens / Task
Thinking tokens burned per task
26K43K

Specifiche Tecniche

Architecture, release timeline, capabilities, and modalities.

Featureo3Claude Opus 4.5
Official API Model ID (SDK)o3claude-opus-4-5-20251101
API ProtocolOpenAI Responses API & Chat Completions v1Anthropic Messages API + AWS Bedrock + Vertex AI
Release Date2025-042025-11
Knowledge CutoffJune 2024March 2025
ArchitectureReasoning transformer with adjustable thinking effortHybrid Reasoning
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) · 800,000 – 2,000,000 TPM
Long-Context Tier (>128K/200K)Flat rate ($2/1M in) across full 200K windowStandard rate up to 200K tokens; 2x input/output tier above 200K tokens
Prompt Cache Policy & TTLAutomatic prefix caching at $0.5/1M (no extra cache-write fee)$0.5/1M 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

o3 vs Claude Opus 4.5: Risposte Rapide (FAQ)

Which is more intelligent, o3 or Claude Opus 4.5?

Claude Opus 4.5 is more intelligent. It scores 63 compared with 56 on the composite Intelligence Index.

Which model is faster?

o3 is faster, generating 75 tokens per second compared with 62 tokens per second.

Which model is cheaper to run?

o3 is cheaper at $1.55 per 1M tokens blended, compared with $3.85 (7:2:1 cache:input:output ratio).

Which model has lower latency?

Claude Opus 4.5 has lower latency, with a time to first token of 2.10s compared with 2.80s.

Verdetto

Sia o3 (Ideale per il ragionamento logico profondo, la matematica avanzata e l’analisi scientifica, sistemi RAG aziendali e integrazioni API scalabili.) sia Claude Opus 4.5 (Ideale per il ragionamento aziendale di frontiera, la programmazione avanzata e i carichi di produzione, sistemi RAG aziendali e integrazioni API scalabili.) eccellono in produzione: Claude Opus 4.5 guida nei benchmark di ragionamento e programmazione, o3 garantisce una generazione più rapida e o3 offre il miglior rapporto qualità-prezzo per carichi API elevati.

Domande Frequenti (FAQ)

Quale modello è migliore per coding e ragionamento, o3 o Claude Opus 4.5?+

Nell’indice di intelligenza composito e nei benchmark di programmazione prevale Claude Opus 4.5. Consulta i punteggi SWE-bench e GPQA qui sopra per tutti i dettagli.

Qual è la differenza di prezzo API tra o3 e Claude Opus 4.5?+

o3 costa $2.00 / $8.00 per milione di token di input/output, mentre Claude Opus 4.5 costa $5.00 / $25.00. Nel costo combinato, o3 risulta più economico.

Quale modello ha la finestra di contesto più ampia e la velocità maggiore?+

o3 supporta 200K token di contesto contro 200K token di Claude Opus 4.5, mentre o3 offre una velocità di generazione superiore.

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.

Fonti ufficiali: Documentazione API ufficiale di OpenAI e Anthropic, schede di sistema e benchmark indipendenti (2026).