Head-to-Head Model Comparison

o3 vs Claude Opus 5.5

Benchmarks, API Token Pricing, Context Window & Speed Comparison

Ditinjau oleh tim riset GetInfoUsPeninjauan terakhir: October 2026Kebijakan editorial
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OpenAIAnthropicreasoningflagship

Compare o3 by OpenAI against Claude Opus 5.5 by Anthropic across real-world coding, reasoning, token economics, and latency.

Perbandingan Langsung (VS)

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Popular Matchups:
OpenAI

o3

Model Penalaran Mendalam

o3 dari OpenAI adalah model AI canggih dengan jendela konteks 200K token serta harga API $2/1M token input dan $8/1M token output untuk pemrograman, penalaran, dan otomasi bisnis.

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 5.5

Model Penalaran Mendalam

Claude Opus 5.5 dari Anthropic adalah model AI canggih dengan jendela konteks 1M token serta harga API $4.0/1M token input dan $20.0/1M token output untuk pemrograman, penalaran, dan otomasi bisnis.

Intelligence Index94 / 100
Input Token:

$4.00 / 1M

Output Token:

$20.00 / 1M

Context Window:

1M tokens

SWE-bench Verified:

84.6%

Perbedaan Utama Sekilas

  • o3 is 2.2x cheaper for API usage (input + output tokens combined).
  • Claude Opus 5.5 has a larger context window (1M vs 200K tokens).
  • Claude Opus 5.5 is faster at 78 tok/s vs 75 tok/s.
  • Claude Opus 5.5 leads on SWE-bench coding (84.6% vs 69.1%).
Need definitions for token pricing, context, or benchmarks?Explore AI Glossary →
Featureo3Claude Opus 5.5
Intelligence Index
Composite reasoning & knowledge score (0-100)
5694
Provider
OpenAIAnthropic
Input Price
Cost per million input tokens
$2.00 / 1M$4.00 / 1M
Output Price
Cost per million output tokens
$8.00 / 1M$20.00 / 1M
Blended Price
Weighted 7:2:1 cache:input:output per 1M
$1.55 / 1M$3.08 / 1M
Context Window
Maximum input + output tokens
200K tokens~300 A4 pages of text1M tokens~1,500 A4 pages of text
Max Output Tokens
Per single request
100K128K
Throughput Speed
Tokens generated per second
75 tok/s78 tok/s
SWE-bench Verified
Real-world software engineering
69.1%84.6%
GPQA Diamond
Graduate-level reasoning
76.5%82.3%
Cached Input Price
Prompt caching discount per 1M tokens
$0.50 / 1M$0.40 / 1M

Siapa Unggul di Mana?

At-a-glance decision framework
Coding
Claude Opus 5.5
+15.5% SWE-bench lead
Cost
o3
2.2x cheaper monthly runtime
Speed
Claude Opus 5.5
+4% faster generation
Context
Claude Opus 5.5
1M tokens window

Skor Benchmark Terverifikasi

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

o3Claude Opus 5.5
SWE-bench Verified (Autonomous Coding)

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

69.1%vs84.6%
GPQA Diamond (Doctorate-Level Science & Math)

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

76.5%vs82.3%
MMLU-Pro (Multi-task Language Understanding)

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

87%vs91.5%
LMSYS Chatbot Arena Elo

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

1345ptsvs1507pts
Humanity's Last Exam (Frontier Expert Knowledge)

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

12.9%vs19.8%
Terminal-Bench (Agentic Coding & Terminal Use)

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

42%vs66.4%
SciCode (Scientific Computing)

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

42.5%vs58.7%
LiveCodeBench (Competitive Coding)

Contamination-free competitive programming problems collected continuously over time.

70.5%vs83.1%
AIME (Advanced Math Competition)

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

91.6%vs95.4%
Long-Context Reasoning

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

78.5%vs92.6%
Generation Speed (Throughput)

Tokens emitted per second during active generation streaming.

75 tok/s vs78 tok/s

Latensi & Waktu Respons

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 5.51.40s
Est. End-to-End Response (500 tokens)TTFT + generation time
o39.47s
Claude Opus 5.57.81s

Simulator Biaya Token Interaktif

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 5.5 Monthly API Bill
$24.60 / month
$4/1M in · $20/1M out
o3 saves approximately $13.65 / month (55%) under this workload.2.2x Savings

o3 · Strengths & Key Advantages

  • Arsitektur Reasoning transformer with adjustable thinking effort mutakhir dari OpenAI dengan dukungan konteks 200K token
  • Efisiensi biaya API yang kompetitif ($2/1M input, $8/1M output) dan respons cepat
  • Performa andal dalam pembuatan kode, analisis logika, serta pemahaman multibahasa
Considerations & Trade-offs
  • Penggunaan konteks berukuran penuh memerlukan pengelolaan anggaran token yang cermat
  • Membutuhkan perancangan prompt yang tepat untuk kasus penggunaan industri spesifik

Claude Opus 5.5 · Strengths & Key Advantages

  • Arsitektur Extended Autonomous Hybrid Reasoning Transformer mutakhir dari Anthropic dengan dukungan konteks 1M token
  • Efisiensi biaya API yang kompetitif ($4.0/1M input, $20.0/1M output) dan respons cepat
  • Performa andal dalam pembuatan kode, analisis logika, serta pemahaman multibahasa
Considerations & Trade-offs
  • Penggunaan konteks berukuran penuh memerlukan pengelolaan anggaran token yang cermat
  • Membutuhkan perancangan prompt yang tepat untuk kasus penggunaan industri spesifik

Token Use & Task Economics

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

Metrico3Claude Opus 5.5
Cost per Task
Estimated USD to finish one task
$1.35$3.85
Output Tokens / Task
Tokens generated per task
48K68K
Reasoning Tokens / Task
Thinking tokens burned per task
26K42K

Spesifikasi Teknis

Architecture, release timeline, capabilities, and modalities.

Featureo3Claude Opus 5.5
Official API Model ID (SDK)o3claude-opus-5-5-20260901
API ProtocolOpenAI Responses API & Chat Completions v1Anthropic Messages API + AWS Bedrock + Vertex AI
Release Date2025-042026-09
Knowledge CutoffJune 2024June 2026
ArchitectureReasoning transformer with adjustable thinking effortExtended 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 ($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)$0.4/1M 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

o3 vs Claude Opus 5.5: Jawaban Cepat (FAQ)

Which is more intelligent, o3 or Claude Opus 5.5?

Claude Opus 5.5 is more intelligent. It scores 94 compared with 56 on the composite Intelligence Index.

Which model is faster?

Claude Opus 5.5 is faster, generating 78 tokens per second compared with 75 tokens per second.

Which model is cheaper to run?

o3 is cheaper at $1.55 per 1M tokens blended, compared with $3.08 (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 2.80s.

Which model has a larger context window?

Claude Opus 5.5 has a larger context window, supporting 1M tokens compared with 200K tokens.

Kesimpulan

Choose o3 for otomasi perusahaan, pengembangan perangkat lunak, agen ai, dan alur kerja produksi berbasis openai, or choose Claude Opus 5.5 for otomasi perusahaan, pengembangan perangkat lunak, agen ai, dan alur kerja produksi berbasis anthropic.

Pertanyaan Umum (FAQ)

Which is cheaper: o3 or Claude Opus 5.5?+

o3 costs $2/1M input and $8/1M output tokens, while Claude Opus 5.5 costs $4/1M input and $20/1M output tokens.

Which model has a larger context window: o3 or Claude Opus 5.5?+

o3 supports 200K 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.

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.

Sumber resmi: OpenAI & Anthropic Official Documentation