Head-to-Head Model Comparison

KAT-Coder-Pro V2.5 vs Claude Opus 5.5

Benchmarks, API Token Pricing, Context Window & Speed Comparison

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Compare KAT-Coder-Pro V2.5 by Kwaipilot against Claude Opus 5.5 by Anthropic across real-world coding, reasoning, token economics, and latency.

Direktvergleich (VS)

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Kwaipilot

KAT-Coder-Pro V2.5

Deep-Reasoning-Modell

KAT-Coder-Pro V2.5 von Kwaipilot ist ein leistungsstarkes KI-Modell mit einem Kontextfenster von 256K Token zu API-Preisen von $0.5/1M Input- und $2/1M Output-Token für Softwareentwicklung, Analyse und Enterprise-Workflows.

Intelligence Index85 / 100
Input Token:

$0.50 / 1M

Output Token:

$2.00 / 1M

Context Window:

256K tokens

SWE-bench Verified:

58%

Anthropic

Claude Opus 5.5

Deep-Reasoning-Modell

Claude Opus 5.5 von Anthropic ist ein leistungsstarkes KI-Modell mit einem Kontextfenster von 1M Token zu API-Preisen von $4.0/1M Input- und $20.0/1M Output-Token für Softwareentwicklung, Analyse und Enterprise-Workflows.

Intelligence Index94 / 100
Input Token:

$4.00 / 1M

Output Token:

$20.00 / 1M

Context Window:

1M tokens

SWE-bench Verified:

84.6%

Wichtigste Unterschiede auf einen Blick

  • KAT-Coder-Pro V2.5 is 9.4x cheaper for API usage (input + output tokens combined).
  • Claude Opus 5.5 has a larger context window (1M vs 256K tokens).
  • KAT-Coder-Pro V2.5 is faster at 80 tok/s vs 78 tok/s.
  • Claude Opus 5.5 leads on SWE-bench coding (84.6% vs 58.0%).
Need definitions for token pricing, context, or benchmarks?Explore AI Glossary →
FeatureKAT-Coder-Pro V2.5Claude Opus 5.5
Intelligence Index
Composite reasoning & knowledge score (0-100)
8594
Provider
KwaipilotAnthropic
Input Price
Cost per million input tokens
$0.50 / 1M$4.00 / 1M
Output Price
Cost per million output tokens
$2.00 / 1M$20.00 / 1M
Blended Price
Weighted 7:2:1 cache:input:output per 1M
$0.34 / 1M$3.08 / 1M
Context Window
Maximum input + output tokens
256K tokens~384 A4 pages of text1M tokens~1,500 A4 pages of text
Max Output Tokens
Per single request
16K128K
Throughput Speed
Tokens generated per second
80 tok/s78 tok/s
SWE-bench Verified
Real-world software engineering
58%84.6%
GPQA Diamond
Graduate-level reasoning
67%82.3%
Cached Input Price
Prompt caching discount per 1M tokens
$0.05 / 1M$0.40 / 1M

Wer gewinnt in welcher Disziplin?

At-a-glance decision framework
Coding
Claude Opus 5.5
+26.6% SWE-bench lead
Cost
KAT-Coder-Pro V2.5
9.4x cheaper monthly runtime
Speed
KAT-Coder-Pro V2.5
+3% faster generation
Context
Claude Opus 5.5
1M tokens window

Geprüfte Benchmark-Ergebnisse im Vergleich

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

KAT-Coder-Pro V2.5Claude Opus 5.5
SWE-bench Verified (Autonomous Coding)

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

58%vs84.6%
GPQA Diamond (Doctorate-Level Science & Math)

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

67%vs82.3%
MMLU-Pro (Multi-task Language Understanding)

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

81%vs91.5%
LMSYS Chatbot Arena Elo

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

1360ptsvs1507pts
Humanity's Last Exam (Frontier Expert Knowledge)

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

N/Avs19.8%
Terminal-Bench (Agentic Coding & Terminal Use)

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

N/Avs66.4%
SciCode (Scientific Computing)

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

N/Avs58.7%
LiveCodeBench (Competitive Coding)

Contamination-free competitive programming problems collected continuously over time.

N/Avs83.1%
AIME (Advanced Math Competition)

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

N/Avs95.4%
Long-Context Reasoning

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

N/Avs92.6%
Generation Speed (Throughput)

Tokens emitted per second during active generation streaming.

80 tok/s vs78 tok/s

Latenz & Antwortzeit

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
KAT-Coder-Pro V2.50.51s
Claude Opus 5.51.40s
Est. End-to-End Response (500 tokens)TTFT + generation time
KAT-Coder-Pro V2.56.76s
Claude Opus 5.57.81s

Interaktiver Token-Kosten-Simulator

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)
KAT-Coder-Pro V2.5 Monthly API Bill
$2.63 / month
$0.5/1M in · $2/1M out
Claude Opus 5.5 Monthly API Bill
$24.60 / month
$4/1M in · $20/1M out
KAT-Coder-Pro V2.5 saves approximately $21.98 / month (89%) under this workload.9.4x Savings

KAT-Coder-Pro V2.5 · Strengths & Key Advantages

  • Fortschrittliche Agentic Code-Specialized Transformer-Architektur von Kwaipilot mit 256K Token Kontextfenster
  • Starkes Preis-Leistungs-Verhältnis ($0.5/1M Input, $2/1M Output) bei hoher Durchsatzrate
  • Hohe Präzision bei Code-Generierung, logischem Schließen und mehrsprachigen Benchmarks
Considerations & Trade-offs
  • Bei sehr großen Kontextmengen ist eine sorgfältige Token-Budgetierung ratsam
  • Spezialisierte Fachaufgaben profitieren von gezieltem Prompt-Engineering

Claude Opus 5.5 · Strengths & Key Advantages

  • Fortschrittliche Extended Autonomous Hybrid Reasoning Transformer-Architektur von Anthropic mit 1M Token Kontextfenster
  • Starkes Preis-Leistungs-Verhältnis ($4.0/1M Input, $20.0/1M Output) bei hoher Durchsatzrate
  • Hohe Präzision bei Code-Generierung, logischem Schließen und mehrsprachigen Benchmarks
Considerations & Trade-offs
  • Bei sehr großen Kontextmengen ist eine sorgfältige Token-Budgetierung ratsam
  • Spezialisierte Fachaufgaben profitieren von gezieltem Prompt-Engineering

Token Use & Task Economics

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

MetricKAT-Coder-Pro V2.5Claude Opus 5.5
Cost per Task
Estimated USD to finish one task
$0.18$3.85
Output Tokens / Task
Tokens generated per task
22K68K
Reasoning Tokens / Task
Thinking tokens burned per task
7K42K

Technische Spezifikationen

Architecture, release timeline, capabilities, and modalities.

FeatureKAT-Coder-Pro V2.5Claude Opus 5.5
Official API Model ID (SDK)kat-coder-pro-v2-5claude-opus-5-5-20260901
API ProtocolKwaipilot REST API (OpenAI-Compatible)Anthropic Messages API + AWS Bedrock + Vertex AI
Release Date2026-072026-09
Knowledge CutoffApril 2026June 2026
ArchitectureAgentic Code-Specialized TransformerExtended Autonomous Hybrid Reasoning Transformer
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) · 4,000,000 – 10,000,000 TPM
Long-Context Tier (>128K/200K)Flat rate ($0.5/1M in) across full 256K windowStandard rate up to 200K tokens; 2x input/output tier above 200K tokens
Prompt Cache Policy & TTLCached input at $0.05/1M tokens$0.4/1M 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 ClassificationKwaipilot 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

KAT-Coder-Pro V2.5 vs Claude Opus 5.5: Schnelle Antworten (FAQ)

Which is more intelligent, KAT-Coder-Pro V2.5 or Claude Opus 5.5?

Claude Opus 5.5 is more intelligent. It scores 94 compared with 85 on the composite Intelligence Index.

Which model is faster?

KAT-Coder-Pro V2.5 is faster, generating 80 tokens per second compared with 78 tokens per second.

Which model is cheaper to run?

KAT-Coder-Pro V2.5 is cheaper at $0.34 per 1M tokens blended, compared with $3.08 (7:2:1 cache:input:output ratio).

Which model has lower latency?

KAT-Coder-Pro V2.5 has lower latency, with a time to first token of 0.51s compared with 1.40s.

Which model has a larger context window?

Claude Opus 5.5 has a larger context window, supporting 1M tokens compared with 256K tokens.

Fazit

Choose KAT-Coder-Pro V2.5 for unternehmensautomatisierung, software-engineering, autonome ki-agenten und kwaipilot-produktionssysteme, or choose Claude Opus 5.5 for unternehmensautomatisierung, software-engineering, autonome ki-agenten und anthropic-produktionssysteme.

Häufig gestellte Fragen (FAQ)

Which is cheaper: KAT-Coder-Pro V2.5 or Claude Opus 5.5?+

KAT-Coder-Pro V2.5 costs $0.5/1M input and $2/1M output tokens, while Claude Opus 5.5 costs $4/1M input and $20/1M output tokens.

Which model has a larger context window: KAT-Coder-Pro V2.5 or Claude Opus 5.5?+

KAT-Coder-Pro V2.5 supports 256K 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.

Offizielle Quellen: Kwaipilot & Anthropic Official Documentation