Head-to-Head Model Comparison

Kimi K2 Thinking Turbo 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
Kimi K2 Thinking Turbo vs Claude Opus 4.5: Benchmarks, Pricing & Speed Comparison

Kimi K2 Thinking Turbo di Moonshot AI e Claude Opus 4.5 di Anthropic sono due modelli di IA di riferimento. Kimi K2 Thinking Turbo offre una finestra di contesto di 262.1K token a $0.60/$2.40 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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Moonshot AI

Kimi K2 Thinking Turbo

Motore di Ragionamento Profondo

Kimi K2 Thinking Turbo di Moonshot AI è un modello di IA progettato per il ragionamento logico profondo, la matematica avanzata e l’analisi scientifica, con finestra di contesto da 262K, velocità di 90 token/s, indice di intelligenza di 84/

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

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

  • 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

Chi vince in ogni categoria?

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

Punteggi Benchmark Verificati

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

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
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

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)
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

  • Finestra di contesto da 262K con capacità massima di output fino a 16K token (GPQA Diamond 68.5% · MMLU-Pro 81.5%)
  • Throughput elevato di 90 token/secondo con latenza al primo token (TTFT) di soli 520 ms
  • Economia API competitiva ($0.6/$2.4 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
  • Nelle dimostrazioni scientifiche più estreme, i modelli di ragionamento pesante dedicati offrono maggiore profondità

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.

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

Specifiche Tecniche

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: Risposte Rapide (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.

Verdetto

Sia Kimi K2 Thinking Turbo (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: Kimi K2 Thinking Turbo guida nei benchmark di ragionamento e programmazione, Kimi K2 Thinking Turbo garantisce una generazione più rapida e Kimi K2 Thinking Turbo offre il miglior rapporto qualità-prezzo per carichi API elevati.

Domande Frequenti (FAQ)

Quale modello è migliore per coding e ragionamento, Kimi K2 Thinking Turbo o Claude Opus 4.5?+

Nell’indice di intelligenza composito e nei benchmark di programmazione prevale Kimi K2 Thinking Turbo. Consulta i punteggi SWE-bench e GPQA qui sopra per tutti i dettagli.

Qual è la differenza di prezzo API tra Kimi K2 Thinking Turbo e Claude Opus 4.5?+

Kimi K2 Thinking Turbo costa $0.60 / $2.40 per milione di token di input/output, mentre Claude Opus 4.5 costa $5.00 / $25.00. Nel costo combinato, Kimi K2 Thinking Turbo risulta più economico.

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

Kimi K2 Thinking Turbo supporta 262.1K token di contesto contro 200K token di Claude Opus 4.5, mentre Kimi K2 Thinking Turbo 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 Moonshot AI e Anthropic, schede di sistema e benchmark indipendenti (2026).