Head-to-Head Model Comparison

Amazon Nova Pro vs Claude Opus 5.5

Benchmarks, API Token Pricing, Context Window & Speed Comparison

Geprüft vom GetInfoUs-ForschungsteamZuletzt geprüft: October 2026Redaktionelle Richtlinien
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Compare Amazon Nova Pro by Amazon against Claude Opus 5.5 by Anthropic across real-world coding, reasoning, token economics, and latency.

Direktvergleich (VS)

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Popular Matchups:
Amazon

Amazon Nova Pro

Deep-Reasoning-Modell

Amazon Nova Pro von Amazon ist ein leistungsstarkes KI-Modell mit einem Kontextfenster von 300K Token zu API-Preisen von $0.8/1M Input- und $3.2/1M Output-Token für Softwareentwicklung, Analyse und Enterprise-Workflows.

Intelligence Index82 / 100
Input Token:

$0.80 / 1M

Output Token:

$3.20 / 1M

Context Window:

300K tokens

SWE-bench Verified:

N/A

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

  • Amazon Nova Pro is 5.6x cheaper for API usage (input + output tokens combined).
  • Claude Opus 5.5 has a larger context window (1M vs 300K tokens).
  • Amazon Nova Pro is faster at 85 tok/s vs 78 tok/s.
Need definitions for token pricing, context, or benchmarks?Explore AI Glossary →
FeatureAmazon Nova ProClaude Opus 5.5
Intelligence Index
Composite reasoning & knowledge score (0-100)
8294
Provider
AmazonAnthropic
Input Price
Cost per million input tokens
$0.80 / 1M$4.00 / 1M
Output Price
Cost per million output tokens
$3.20 / 1M$20.00 / 1M
Blended Price
Weighted 7:2:1 cache:input:output per 1M
$0.62 / 1M$3.08 / 1M
Context Window
Maximum input + output tokens
300K tokens~450 A4 pages of text1M tokens~1,500 A4 pages of text
Max Output Tokens
Per single request
8K128K
Throughput Speed
Tokens generated per second
85 tok/s78 tok/s
SWE-bench Verified
Real-world software engineering
N/A84.6%
GPQA Diamond
Graduate-level reasoning
62%82.3%
Cached Input Price
Prompt caching discount per 1M tokens
$0.20 / 1M$0.40 / 1M

Wer gewinnt in welcher Disziplin?

At-a-glance decision framework
Coding

Evaluations ongoing

Cost
Amazon Nova Pro
5.6x cheaper monthly runtime
Speed
Amazon Nova Pro
+9% 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.

Amazon Nova ProClaude Opus 5.5
SWE-bench Verified (Autonomous Coding)

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

N/Avs84.6%
GPQA Diamond (Doctorate-Level Science & Math)

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

62%vs82.3%
MMLU-Pro (Multi-task Language Understanding)

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

79%vs91.5%
LMSYS Chatbot Arena Elo

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

1330ptsvs1507pts
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.

85 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
Amazon Nova Pro0.44s
Claude Opus 5.51.40s
Est. End-to-End Response (500 tokens)TTFT + generation time
Amazon Nova Pro6.32s
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)
Amazon Nova Pro Monthly API Bill
$4.38 / month
$0.8/1M in · $3.2/1M out
Claude Opus 5.5 Monthly API Bill
$24.60 / month
$4/1M in · $20/1M out
Amazon Nova Pro saves approximately $20.22 / month (82%) under this workload.5.6x Savings

Amazon Nova Pro · Strengths & Key Advantages

  • Fortschrittliche Enterprise Multimodal Foundation Transformer-Architektur von Amazon mit 300K Token Kontextfenster
  • Starkes Preis-Leistungs-Verhältnis ($0.8/1M Input, $3.2/1M 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.

MetricAmazon Nova ProClaude Opus 5.5
Cost per Task
Estimated USD to finish one task
$0.16$3.85
Output Tokens / Task
Tokens generated per task
18K68K
Reasoning Tokens / Task
Thinking tokens burned per task
4K42K

Technische Spezifikationen

Architecture, release timeline, capabilities, and modalities.

FeatureAmazon Nova ProClaude Opus 5.5
Official API Model ID (SDK)nova-proclaude-opus-5-5-20260901
API ProtocolAmazon REST API (OpenAI-Compatible)Anthropic Messages API + AWS Bedrock + Vertex AI
Release Date2024-122026-09
Knowledge CutoffOctober 2024June 2026
ArchitectureEnterprise Multimodal Foundation 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 ($0.8/1M in) across full 300K windowStandard rate up to 200K tokens; 2x input/output tier above 200K tokens
Prompt Cache Policy & TTLCached input at $0.2/1M tokens$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 & 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) · Vision (~258–765 tokens per image tile) · Video (~258–300 tokens/sec)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 ClassificationAmazon 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 Modalitiestext, vision, videotext, vision
Output Modalitiestexttext

Amazon Nova Pro vs Claude Opus 5.5: Schnelle Antworten (FAQ)

Which is more intelligent, Amazon Nova Pro or Claude Opus 5.5?

Claude Opus 5.5 is more intelligent. It scores 94 compared with 82 on the composite Intelligence Index.

Which model is faster?

Amazon Nova Pro is faster, generating 85 tokens per second compared with 78 tokens per second.

Which model is cheaper to run?

Amazon Nova Pro is cheaper at $0.62 per 1M tokens blended, compared with $3.08 (7:2:1 cache:input:output ratio).

Which model has lower latency?

Amazon Nova Pro has lower latency, with a time to first token of 0.44s 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 300K tokens.

Fazit

Choose Amazon Nova Pro for unternehmensautomatisierung, software-engineering, autonome ki-agenten und amazon-produktionssysteme, or choose Claude Opus 5.5 for unternehmensautomatisierung, software-engineering, autonome ki-agenten und anthropic-produktionssysteme.

Häufig gestellte Fragen (FAQ)

Which is cheaper: Amazon Nova Pro or Claude Opus 5.5?+

Amazon Nova Pro costs $0.8/1M input and $3.2/1M output tokens, while Claude Opus 5.5 costs $4/1M input and $20/1M output tokens.

Which model has a larger context window: Amazon Nova Pro or Claude Opus 5.5?+

Amazon Nova Pro supports 300K 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: Amazon & Anthropic Official Documentation