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Head-to-Head Model Comparison

GPT-5.6 Sol 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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Related topics (12)
AI CompareAI BenchmarkToken PricingModel CostModel SpecsSWE-bench CodingModel VersusWhich AI ModelLLM Speed & LatencyReasoning ModelsExtended ThinkingPrompt Caching ROI
GPT-5.6 Sol vs Claude Opus 5.5: Benchmarks, Pricing & Speed Comparison

GPT-5.6 Sol dari OpenAI dan Claude Opus 5.5 dari Anthropic adalah dua model AI unggulan. GPT-5.6 Sol menawarkan jendela konteks 1.05M token dengan harga $4.00/$20.00 per 1 juta token, sedangkan Claude Opus 5.5 menyediakan konteks 1M token seharga $4.00/$20.00 per 1 juta token. Berikut perbandingan lengkap benchmark, latensi, dan biayanya.

Perbandingan Langsung (VS)

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OpenAI

GPT-5.6 Sol

Model Unggulan Garis Depan

GPT-5.6 Sol dari OpenAI adalah model AI yang dirancang untuk penalaran perusahaan garis depan, pemrograman tingkat lanjut, dan produksi AI, menghadirkan jendela konteks 1.1M, kecepatan 108 token/detik, indeks kecerdasan 89/100, serta tarif

Intelligence Index89 / 100
Input Token:

$4.00 / 1M

Output Token:

$20.00 / 1M

Context Window:

1.05M tokens

SWE-bench Verified:

83.8%

Anthropic

Claude Opus 5.5

Model Unggulan Garis Depan

Claude Opus 5.5 dari Anthropic adalah model AI yang dirancang untuk penalaran perusahaan garis depan, pemrograman tingkat lanjut, dan produksi AI, menghadirkan jendela konteks 1M, kecepatan 78 token/detik, indeks kecerdasan 94/100, serta ta

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

  • Both models cost the same under this workload — choose on capability, not price.
  • GPT-5.6 Sol has a larger context window (1M vs 1M tokens).
  • GPT-5.6 Sol is faster at 108 tok/s vs 78 tok/s.
  • Claude Opus 5.5 leads on SWE-bench coding (84.6% vs 83.8%).
Need definitions for token pricing, context, or benchmarks?Explore AI Glossary →
FeatureGPT-5.6 SolClaude Opus 5.5
Intelligence Index
Composite reasoning & knowledge score (0-100)
8994
Provider
OpenAIAnthropic
Input Price
Cost per million input tokens
$4.00 / 1M$4.00 / 1M
Output Price
Cost per million output tokens
$20.00 / 1M$20.00 / 1M
Blended Price
Weighted 7:2:1 cache:input:output per 1M
$3.08 / 1M$3.08 / 1M
Context Window
Maximum input + output tokens
1.05M tokens~1,575 A4 pages of text1M tokens~1,500 A4 pages of text
Max Output Tokens
Per single request
128K128K
Throughput Speed
Tokens generated per second
108 tok/s78 tok/s
SWE-bench Verified
Real-world software engineering
83.8%84.6%
GPQA Diamond
Graduate-level reasoning
82%82.3%
Cached Input Price
Prompt caching discount per 1M tokens
$0.40 / 1M$0.40 / 1M

Siapa Unggul di Mana?

At-a-glance decision framework
Coding
Claude Opus 5.5
+0.8% SWE-bench lead
Cost
Tied
Identical monthly runtime cost
Speed
GPT-5.6 Sol
+38% faster generation
Context
GPT-5.6 Sol
1.05M tokens window

Skor Benchmark Terverifikasi

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

GPT-5.6 SolClaude Opus 5.5
SWE-bench Verified (Autonomous Coding)

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

83.8%vs84.6%
GPQA Diamond (Doctorate-Level Science & Math)

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

82%vs82.3%
MMLU-Pro (Multi-task Language Understanding)

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

90.8%vs91.5%
LMSYS Chatbot Arena Elo

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

1496ptsvs1507pts
Humanity's Last Exam (Frontier Expert Knowledge)

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

17.8%vs19.8%
Terminal-Bench (Agentic Coding & Terminal Use)

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

61%vs66.4%
SciCode (Scientific Computing)

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

55%vs58.7%
LiveCodeBench (Competitive Coding)

Contamination-free competitive programming problems collected continuously over time.

80.6%vs83.1%
AIME (Advanced Math Competition)

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

95.8%vs95.4%
Long-Context Reasoning

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

89.6%vs92.6%
Generation Speed (Throughput)

Tokens emitted per second during active generation streaming.

108 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
GPT-5.6 Sol1.21s
Claude Opus 5.51.40s
Est. End-to-End Response (500 tokens)TTFT + generation time
GPT-5.6 Sol5.84s
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)
GPT-5.6 Sol Monthly API Bill
$24.60 / month
$4/1M in · $20/1M out
Claude Opus 5.5 Monthly API Bill
$24.60 / month
$4/1M in · $20/1M out
These models cost the same under this workload — no savings either way.Break-even

GPT-5.6 Sol · Strengths & Key Advantages

  • Jendela konteks 1.1M dengan kapasitas output maksimum hingga 128K token (SWE-bench Verified 83.8% · GPQA Diamond 82%)
  • Kecepatan generasi tinggi 108 token/detik dengan latensi token pertama (TTFT) hanya 1210 ms
  • Skema harga API kompetitif (tarif $4/$20 per 1M token) dengan dukungan cache prompt dan output JSON terstruktur
Considerations & Trade-offs
  • Model cloud proprietari tertutup; bobot model tidak dapat diunduh untuk penggunaan lokal offline
  • Untuk trafik produksi skala besar, disarankan mengaktifkan fitur Prompt Caching dan Batch API guna menghemat biaya

Claude Opus 5.5 · Strengths & Key Advantages

  • Jendela konteks 1M dengan kapasitas output maksimum hingga 128K token (SWE-bench Verified 84.6% · GPQA Diamond 82.3%)
  • Kecepatan generasi tinggi 78 token/detik dengan latensi token pertama (TTFT) hanya 1400 ms
  • Skema harga API kompetitif (tarif $4/$20 per 1M token) dengan dukungan cache prompt dan output JSON terstruktur
Considerations & Trade-offs
  • Model cloud proprietari tertutup; bobot model tidak dapat diunduh untuk penggunaan lokal offline
  • Untuk trafik produksi skala besar, disarankan mengaktifkan fitur Prompt Caching dan Batch API guna menghemat biaya

Token Use & Task Economics

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

MetricGPT-5.6 SolClaude Opus 5.5
Cost per Task
Estimated USD to finish one task
$3.30$3.85
Output Tokens / Task
Tokens generated per task
64K68K
Reasoning Tokens / Task
Thinking tokens burned per task
38K42K

Spesifikasi Teknis

Architecture, release timeline, capabilities, and modalities.

FeatureGPT-5.6 SolClaude Opus 5.5
Official API Model ID (SDK)gpt-5-6-solclaude-opus-5-5-20260901
API ProtocolOpenAI Responses API & Chat Completions v1Anthropic Messages API + AWS Bedrock + Vertex AI
Release Date2026-072026-09
Knowledge CutoffFebruary 2026June 2026
ArchitectureFrontier unified reasoning modelExtended Autonomous Hybrid Reasoning Transformer
ParametersConfidentialConfidential
Enterprise Rate Limits (RPM / TPM)10,000 – 30,000 RPM (Tier 5 Enterprise) · 4,000,000 – 10,000,000 TPM4,000 – 10,000 RPM (Tier 4 + Priority Tier) · 4,000,000 – 10,000,000 TPM
Long-Context Tier (>128K/200K)Flat rate ($4/1M in) across full 1050K windowStandard rate up to 200K tokens; 2x input/output tier above 200K tokens
Prompt Cache Policy & TTLAutomatic prefix caching at $0.4/1M (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-5.6 Sol vs Claude Opus 5.5: Jawaban Cepat (FAQ)

Which is more intelligent, GPT-5.6 Sol or Claude Opus 5.5?

Claude Opus 5.5 is more intelligent. It scores 94 compared with 89 on the composite Intelligence Index.

Which model is faster?

GPT-5.6 Sol is faster, generating 108 tokens per second compared with 78 tokens per second.

Which model has lower latency?

GPT-5.6 Sol has lower latency, with a time to first token of 1.21s compared with 1.40s.

Which model has a larger context window?

GPT-5.6 Sol has a larger context window, supporting 1.05M tokens compared with 1M tokens.

Kesimpulan

Baik GPT-5.6 Sol (Sangat cocok untuk penalaran perusahaan garis depan, pemrograman tingkat lanjut, dan produksi AI, sistem RAG perusahaan, dan integrasi API skala produksi.) maupun Claude Opus 5.5 (Sangat cocok untuk penalaran perusahaan garis depan, pemrograman tingkat lanjut, dan produksi AI, sistem RAG perusahaan, dan integrasi API skala produksi.) sangat tangguh: Claude Opus 5.5 unggul dalam penalaran dan pemrograman, GPT-5.6 Sol memberikan kecepatan generasi token lebih tinggi, dan GPT-5.6 Sol lebih hemat biaya untuk penggunaan API skala besar.

Pertanyaan Umum (FAQ)

Mana yang lebih baik untuk coding dan penalaran, GPT-5.6 Sol atau Claude Opus 5.5?+

Dalam indeks kecerdasan gabungan dan benchmark coding, Claude Opus 5.5 memimpin. Lihat skor SWE-bench dan GPQA di atas untuk detailnya.

Berapa perbandingan harga API GPT-5.6 Sol vs Claude Opus 5.5?+

GPT-5.6 Sol mengenakan biaya $4.00 / $20.00 per 1M token input/output, sedangkan Claude Opus 5.5 sebesar $4.00 / $20.00. Secara keseluruhan, GPT-5.6 Sol lebih hemat biaya.

Model mana yang memiliki jendela konteks lebih besar dan kecepatan lebih tinggi?+

GPT-5.6 Sol mendukung konteks 1.05M token dibandingkan 1M token pada Claude Opus 5.5, sementara GPT-5.6 Sol unggul dalam kecepatan output token per detik.

AI Terminology & Guide
Explore Glossary →

Understand key metrics like context window, token pricing, reasoning mode, and SWE-bench scores in our comprehensive AI glossary.

Tokens & PricingContext WindowAI BenchmarksReasoning ModelsTool CallingModel Context Protocol (MCP)

Related reading

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: Dokumentasi API resmi OpenAI & Anthropic serta evaluasi benchmark independen (2026).