Head-to-Head Model Comparison

Nex-N2-Pro vs Claude Opus 5.5

Benchmarks, API Token Pricing, Context Window & Speed Comparison

Geprüft vom GetInfoUs-ForschungsteamZuletzt geprüft: October 2026Redaktionelle Richtlinien
Teilen
Related topics (4)
Nex AGIAnthropicflagshipflagship

Compare Nex-N2-Pro by Nex AGI against Claude Opus 5.5 by Anthropic across real-world coding, reasoning, token economics, and latency.

Direktvergleich (VS)

Beliebige Modelle wechseln & vergleichen

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

Live comparison: no in-depth editorial review has been published for this pair yet.

Popular Matchups:
Nex AGI

Nex-N2-Pro

Deep-Reasoning-Engine

Nex-N2-Pro von Nex AGI ist ein KI-Modell für tiefgehendes logisches Denken, komplexe Mathematik und wissenschaftliche Analysen mit 262K Kontextfenster, 85 Token/s Durchsatz, einem Intelligenz-Index von 81/100 und $0.4/$1.6 pro 1M Token.

Intelligence Index81 / 100
Input Token:

$0.40 / 1M

Output Token:

$1.60 / 1M

Context Window:

262.1K tokens

SWE-bench Verified:

N/A

Anthropic

Claude Opus 5.5

Frontier-Flaggschiff-Modell

Claude Opus 5.5 von Anthropic ist ein KI-Modell für anspruchsvolles Enterprise-Reasoning, Softwareentwicklung und produktive KI-Workflows mit 1M Kontextfenster, 78 Token/s Durchsatz, einem Intelligenz-Index von 94/100 und $4/$20 pro 1M Toke

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

  • Nex-N2-Pro is 11.7x cheaper for API usage (input + output tokens combined).
  • Claude Opus 5.5 has a larger context window (1M vs 262K tokens).
  • Nex-N2-Pro is faster at 85 tok/s vs 78 tok/s.
Need definitions for token pricing, context, or benchmarks?Explore AI Glossary →
FeatureNex-N2-ProClaude Opus 5.5
Intelligence Index
Composite reasoning & knowledge score (0-100)
8194
Provider
Nex AGIAnthropic
Input Price
Cost per million input tokens
$0.40 / 1M$4.00 / 1M
Output Price
Cost per million output tokens
$1.60 / 1M$20.00 / 1M
Blended Price
Weighted 7:2:1 cache:input:output per 1M
$0.27 / 1M$3.08 / 1M
Context Window
Maximum input + output tokens
262.1K tokens~393 A4 pages of text1M tokens~1,500 A4 pages of text
Max Output Tokens
Per single request
16K128K
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
$0.04 / 1M$0.40 / 1M

Wer gewinnt in welcher Disziplin?

At-a-glance decision framework
Coding

Evaluations ongoing

Cost
Nex-N2-Pro
11.7x cheaper monthly runtime
Speed
Nex-N2-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.

Nex-N2-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.

78%vs91.5%
LMSYS Chatbot Arena Elo

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

1320ptsvs1507pts
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
Nex-N2-Pro0.46s
Claude Opus 5.51.40s
Est. End-to-End Response (500 tokens)TTFT + generation time
Nex-N2-Pro6.34s
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)
Nex-N2-Pro Monthly API Bill
$2.10 / month
$0.4/1M in · $1.6/1M out
Claude Opus 5.5 Monthly API Bill
$24.60 / month
$4/1M in · $20/1M out
Nex-N2-Pro saves approximately $22.50 / month (91%) under this workload.11.7x Savings

Nex-N2-Pro · Strengths & Key Advantages

  • 262K Kontextfenster und bis zu 16K maximale Output-Token (GPQA Diamond 62% · MMLU-Pro 78%)
  • Hohe Generierungsgeschwindigkeit von 85 Token/Sekunde bei nur 460 ms Erstlatenz (TTFT)
  • Effiziente API-Struktur ($0.4/$1.6 pro 1M Token) inklusive Prompt-Caching, Tool-Calling und strikter JSON-Ausgabe
Considerations & Trade-offs
  • Proprietäres Cloud-Modell ohne Möglichkeit zum lokalen Download der Modellgewichte
  • Bei extrem komplexen mehrstufigen Forschungsfragen bieten schwere Reasoning-Spezialmodelle noch tiefere Analysen

Claude Opus 5.5 · Strengths & Key Advantages

  • 1M Kontextfenster und bis zu 128K maximale Output-Token (SWE-bench Verified 84.6% · GPQA Diamond 82.3%)
  • Hohe Generierungsgeschwindigkeit von 78 Token/Sekunde bei nur 1400 ms Erstlatenz (TTFT)
  • Effiziente API-Struktur ($4/$20 pro 1M Token) inklusive Prompt-Caching, Tool-Calling und strikter JSON-Ausgabe
Considerations & Trade-offs
  • Proprietäres Cloud-Modell ohne Möglichkeit zum lokalen Download der Modellgewichte
  • Bei hohem Anfragevolumen empfiehlt sich der Einsatz von Prompt-Caching und Batch-API zur Kostenoptimierung

Token Use & Task Economics

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

MetricNex-N2-ProClaude Opus 5.5
Cost per Task
Estimated USD to finish one task
$0.12$3.85
Output Tokens / Task
Tokens generated per task
18K68K
Reasoning Tokens / Task
Thinking tokens burned per task
5K42K

Technische Spezifikationen

Architecture, release timeline, capabilities, and modalities.

FeatureNex-N2-ProClaude Opus 5.5
Official API Model ID (SDK)nex-n2-proclaude-opus-5-5-20260901
API ProtocolNex AGI REST API (OpenAI-Compatible)Anthropic Messages API + AWS Bedrock + Vertex AI
Release Date2026-062026-09
Knowledge CutoffMarch 2026June 2026
ArchitectureMid-Tier Reasoning 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 ($0.4/1M in) across full 262K windowStandard rate up to 200K tokens; 2x input/output tier above 200K tokens
Prompt Cache Policy & TTLCached input at $0.04/1M 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 ClassificationNex AGI 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

Nex-N2-Pro vs Claude Opus 5.5: Schnelle Antworten (FAQ)

Which is more intelligent, Nex-N2-Pro or Claude Opus 5.5?

Claude Opus 5.5 is more intelligent. It scores 94 compared with 81 on the composite Intelligence Index.

Which model is faster?

Nex-N2-Pro is faster, generating 85 tokens per second compared with 78 tokens per second.

Which model is cheaper to run?

Nex-N2-Pro is cheaper at $0.27 per 1M tokens blended, compared with $3.08 (7:2:1 cache:input:output ratio).

Which model has lower latency?

Nex-N2-Pro has lower latency, with a time to first token of 0.46s 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 262.1K tokens.

Fazit

Choose Nex-N2-Pro for optimal für tiefgehendes logisches denken, komplexe mathematik und wissenschaftliche analysen, enterprise-rag-systeme und skalierbare api-pipelines., or choose Claude Opus 5.5 for optimal für anspruchsvolles enterprise-reasoning, softwareentwicklung und produktive ki-workflows, enterprise-rag-systeme und skalierbare api-pipelines..

Häufig gestellte Fragen (FAQ)

Which is cheaper: Nex-N2-Pro or Claude Opus 5.5?+

Nex-N2-Pro costs $0.4/1M input and $1.6/1M output tokens, while Claude Opus 5.5 costs $4/1M input and $20/1M output tokens.

Which model has a larger context window: Nex-N2-Pro or Claude Opus 5.5?+

Nex-N2-Pro supports 262K 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: Nex AGI & Anthropic Official Documentation