GetInfoUs
Head-to-Head Model Comparison

Kimi K2 Thinking Turbo vs Claude Opus 4.5

Benchmarks, API Token Pricing, Context Window & Speed Comparison

Ditinjau oleh tim riset GetInfoUsPeninjauan terakhir: October 2026Kebijakan editorial
Bagikan
Related topics (12)
AI CompareAI BenchmarkToken PricingModel CostModel SpecsSWE-bench CodingModel VersusWhich AI ModelLLM Speed & LatencyReasoning ModelsExtended ThinkingPrompt Caching ROI
Kimi K2 Thinking Turbo vs Claude Opus 4.5: Benchmarks, Pricing & Speed Comparison

Kimi K2 Thinking Turbo dari Moonshot AI dan Claude Opus 4.5 dari Anthropic adalah dua model AI unggulan. Kimi K2 Thinking Turbo menawarkan jendela konteks 262.1K token dengan harga $0.60/$2.40 per 1 juta token, sedangkan Claude Opus 4.5 menyediakan konteks 200K token seharga $5.00/$25.00 per 1 juta token. Berikut perbandingan lengkap benchmark, latensi, dan biayanya.

Perbandingan Langsung (VS)

Ganti & Bandingkan Model Apa Saja

Select any AI models from our verified benchmark database to generate live side-by-side matrices.

Profile
Profile
Multi-Model Arena Stack:
5-Model Matrix Workbench
Popular Matchups:
Moonshot AI

Kimi K2 Thinking Turbo

Mesin Penalaran Mendalam

Kimi K2 Thinking Turbo dari Moonshot AI adalah model AI yang dirancang untuk penalaran logis mendalam, matematika tingkat lanjut, dan analisis ilmiah, menghadirkan jendela konteks 262K, kecepatan 90 token/detik, indeks kecerdasan 84/100, se

Intelligence Index84 / 100
Input Token:

$0.60 / 1M

Output Token:

$2.40 / 1M

Context Window:

262.1K tokens

SWE-bench Verified:

N/A

Anthropic

Claude Opus 4.5

Model Unggulan Garis Depan

Claude Opus 4.5 dari Anthropic adalah model AI yang dirancang untuk penalaran perusahaan garis depan, pemrograman tingkat lanjut, dan produksi AI, menghadirkan jendela konteks 200K, kecepatan 62 token/detik, indeks kecerdasan 63/100, serta

Intelligence Index63 / 100
Input Token:

$5.00 / 1M

Output Token:

$25.00 / 1M

Context Window:

200K tokens

SWE-bench Verified:

77.2%

Perbedaan Utama Sekilas

  • Kimi K2 Thinking Turbo is 9.8x cheaper for API usage (input + output tokens combined).
  • Kimi K2 Thinking Turbo has a larger context window (262K vs 200K tokens).
  • Kimi K2 Thinking Turbo is faster at 90 tok/s vs 62 tok/s.
Need definitions for token pricing, context, or benchmarks?Explore AI Glossary →
FeatureKimi K2 Thinking TurboClaude Opus 4.5
Intelligence Index
Composite reasoning & knowledge score (0-100)
8463
Provider
Moonshot AIAnthropic
Input Price
Cost per million input tokens
$0.60 / 1M$5.00 / 1M
Output Price
Cost per million output tokens
$2.40 / 1M$25.00 / 1M
Blended Price
Weighted 7:2:1 cache:input:output per 1M
$0.40 / 1M$3.85 / 1M
Context Window
Maximum input + output tokens
262.1K tokens~393 A4 pages of text200K tokens~300 A4 pages of text
Max Output Tokens
Per single request
16K64K
Throughput Speed
Tokens generated per second
90 tok/s62 tok/s
SWE-bench Verified
Real-world software engineering
N/A77.2%
GPQA Diamond
Graduate-level reasoning
68.5%74.8%
Cached Input Price
Prompt caching discount per 1M tokens
$0.06 / 1M$0.50 / 1M

Siapa Unggul di Mana?

At-a-glance decision framework
Coding

Evaluations ongoing

Cost
Kimi K2 Thinking Turbo
9.8x cheaper monthly runtime
Speed
Kimi K2 Thinking Turbo
+45% faster generation
Context
Kimi K2 Thinking Turbo
262.1K tokens window

Skor Benchmark Terverifikasi

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

Kimi K2 Thinking TurboClaude Opus 4.5
SWE-bench Verified (Autonomous Coding)

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

N/Avs77.2%
GPQA Diamond (Doctorate-Level Science & Math)

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

68.5%vs74.8%
MMLU-Pro (Multi-task Language Understanding)

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

81.5%vs87.3%
LMSYS Chatbot Arena Elo

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

1365ptsvs1376pts
Humanity's Last Exam (Frontier Expert Knowledge)

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

N/Avs13.7%
Terminal-Bench (Agentic Coding & Terminal Use)

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

N/Avs49.2%
SciCode (Scientific Computing)

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

N/Avs45.6%
LiveCodeBench (Competitive Coding)

Contamination-free competitive programming problems collected continuously over time.

N/Avs74.1%
AIME (Advanced Math Competition)

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

81%vs88.5%
Long-Context Reasoning

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

N/Avs79.4%
Generation Speed (Throughput)

Tokens emitted per second during active generation streaming.

90 tok/s vs62 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
Kimi K2 Thinking Turbo0.52s
Claude Opus 4.52.10s
Est. End-to-End Response (500 tokens)TTFT + generation time
Kimi K2 Thinking Turbo6.08s
Claude Opus 4.510.16s

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)
Kimi K2 Thinking Turbo Monthly API Bill
$3.15 / month
$0.6/1M in · $2.4/1M out
Claude Opus 4.5 Monthly API Bill
$30.75 / month
$5/1M in · $25/1M out
Kimi K2 Thinking Turbo saves approximately $27.60 / month (90%) under this workload.9.8x Savings

Kimi K2 Thinking Turbo · Strengths & Key Advantages

  • Jendela konteks 262K dengan kapasitas output maksimum hingga 16K token (GPQA Diamond 68.5% · MMLU-Pro 81.5%)
  • Kecepatan generasi tinggi 90 token/detik dengan latensi token pertama (TTFT) hanya 520 ms
  • Skema harga API kompetitif (tarif $0.6/$2.4 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
  • Pada tugas pembuktian ilmiah tingkat ekstrem, model penalaran berat kelas atas memberikan kedalaman lebih tinggi

Claude Opus 4.5 · Strengths & Key Advantages

  • Jendela konteks 200K dengan kapasitas output maksimum hingga 64K token (SWE-bench Verified 77.2% · GPQA Diamond 74.8%)
  • Kecepatan generasi tinggi 62 token/detik dengan latensi token pertama (TTFT) hanya 2100 ms
  • Skema harga API kompetitif (tarif $5/$25 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.

MetricKimi K2 Thinking TurboClaude Opus 4.5
Cost per Task
Estimated USD to finish one task
$0.18$5.86
Output Tokens / Task
Tokens generated per task
22K73K
Reasoning Tokens / Task
Thinking tokens burned per task
10K43K

Spesifikasi Teknis

Architecture, release timeline, capabilities, and modalities.

FeatureKimi K2 Thinking TurboClaude Opus 4.5
Official API Model ID (SDK)kimi-k2-thinking-turboclaude-opus-4-5-20251101
API ProtocolMoonshot AI REST API (OpenAI-Compatible)Anthropic Messages API + AWS Bedrock + Vertex AI
Release Date2025-112025-11
Knowledge CutoffSeptember 2025March 2025
ArchitectureHosted Accelerated Reasoning EngineHybrid Reasoning
ParametersConfidentialConfidential
Enterprise Rate Limits (RPM / TPM)5,000 – 15,000 RPM (Production Tier) · 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 ($0.6/1M in) across full 262K windowStandard rate up to 200K tokens; 2x input/output tier above 200K tokens
Prompt Cache Policy & TTLCached input at $0.06/1M tokens$0.5/1M cached read (90% off); 5-min default & 1-hour extended TTL
Computer Use / GUI AgentAPI / CLI Tool-Use & DOM Agent ready (no raw pixel desktop click loop)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 & SandboxSupported via external Tavily/Exa Search & E2B/Docker Sandbox toolsNative Web Search Citations + Code Execution Tool + MCP Connectors
Official Fine-Tuning SupportAPI Prompt Engineering & RAG DistillationCustom Model Tuning via Amazon Bedrock & Prompt Distillation
Multimodal Token BillingText BPE (~4 chars/token)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 ClassificationMoonshot AI Production Safety & Alignment VerifiedAnthropic 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 Modalitiestexttext, vision
Output Modalitiestexttext

Kimi K2 Thinking Turbo vs Claude Opus 4.5: Jawaban Cepat (FAQ)

Which is more intelligent, Kimi K2 Thinking Turbo or Claude Opus 4.5?

Kimi K2 Thinking Turbo is more intelligent. It scores 84 compared with 63 on the composite Intelligence Index.

Which model is faster?

Kimi K2 Thinking Turbo is faster, generating 90 tokens per second compared with 62 tokens per second.

Which model is cheaper to run?

Kimi K2 Thinking Turbo is cheaper at $0.40 per 1M tokens blended, compared with $3.85 (7:2:1 cache:input:output ratio).

Which model has lower latency?

Kimi K2 Thinking Turbo has lower latency, with a time to first token of 0.52s compared with 2.10s.

Which model has a larger context window?

Kimi K2 Thinking Turbo has a larger context window, supporting 262.1K tokens compared with 200K tokens.

Kesimpulan

Baik Kimi K2 Thinking Turbo (Sangat cocok untuk penalaran logis mendalam, matematika tingkat lanjut, dan analisis ilmiah, sistem RAG perusahaan, dan integrasi API skala produksi.) maupun Claude Opus 4.5 (Sangat cocok untuk penalaran perusahaan garis depan, pemrograman tingkat lanjut, dan produksi AI, sistem RAG perusahaan, dan integrasi API skala produksi.) sangat tangguh: Kimi K2 Thinking Turbo unggul dalam penalaran dan pemrograman, Kimi K2 Thinking Turbo memberikan kecepatan generasi token lebih tinggi, dan Kimi K2 Thinking Turbo lebih hemat biaya untuk penggunaan API skala besar.

Pertanyaan Umum (FAQ)

Mana yang lebih baik untuk coding dan penalaran, Kimi K2 Thinking Turbo atau Claude Opus 4.5?+

Dalam indeks kecerdasan gabungan dan benchmark coding, Kimi K2 Thinking Turbo memimpin. Lihat skor SWE-bench dan GPQA di atas untuk detailnya.

Berapa perbandingan harga API Kimi K2 Thinking Turbo vs Claude Opus 4.5?+

Kimi K2 Thinking Turbo mengenakan biaya $0.60 / $2.40 per 1M token input/output, sedangkan Claude Opus 4.5 sebesar $5.00 / $25.00. Secara keseluruhan, Kimi K2 Thinking Turbo lebih hemat biaya.

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

Kimi K2 Thinking Turbo mendukung konteks 262.1K token dibandingkan 200K token pada Claude Opus 4.5, sementara Kimi K2 Thinking Turbo 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 Moonshot AI & Anthropic serta evaluasi benchmark independen (2026).