Head-to-Head Model Comparison

Claude Opus 4.1 vs Gemini 2.5 Computer Use

Benchmarks, API Token Pricing, Context Window & Speed Comparison

Geprüft vom GetInfoUs-ForschungsteamZuletzt geprüft: October 2026Redaktionelle Richtlinien
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AI CompareAI BenchmarkToken PricingModel CostModel SpecsSWE-bench CodingModel VersusWhich AI ModelLLM Speed & LatencyReasoning ModelsExtended ThinkingPrompt Caching ROI
Claude Opus 4.1 vs Gemini 2.5 Computer Use: Benchmarks, Pricing & Speed Comparison

Claude Opus 4.1 von Anthropic und Gemini 2.5 Computer Use von Google gehören zu den führenden KI-Modellen. Claude Opus 4.1 bietet ein Kontextfenster von 200K Tokens bei API-Preisen von $15.00/$75.00 pro 1M Tokens, während Gemini 2.5 Computer Use 128K Tokens Kontext zu $1.50/$8.00 pro 1M Tokens bereitstellt. Hier finden Sie den vollständigen Benchmark-, Latenz- und Kostenvergleich.

Direktvergleich (VS)

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Anthropic

Claude Opus 4.1

Autonomes Agenten-Modell

Claude Opus 4.1 von Anthropic ist ein KI-Modell für autonome Agenten-Workflows, zuverlässiges Tool-Calling und mehrstufige Automatisierung mit 200K Kontextfenster, 46 Token/s Durchsatz, einem Intelligenz-Index von 62/100 und $15/$75 pro 1M

Intelligence Index62 / 100
Input Token:

$15.00 / 1M

Output Token:

$75.00 / 1M

Context Window:

200K tokens

SWE-bench Verified:

74.5%

Google

Gemini 2.5 Computer Use

Autonomes Agenten-Modell

Gemini 2.5 Computer Use von Google ist ein KI-Modell für autonome Agenten-Workflows, zuverlässiges Tool-Calling und mehrstufige Automatisierung mit 128K Kontextfenster, 85 Token/s Durchsatz, einem Intelligenz-Index von 65/100 und $1.5/$8 pr

Intelligence Index65 / 100
Input Token:

$1.50 / 1M

Output Token:

$8.00 / 1M

Context Window:

128K tokens

SWE-bench Verified:

N/A

Wichtigste Unterschiede auf einen Blick

  • Gemini 2.5 Computer Use is 9.2x cheaper for API usage (input + output tokens combined).
  • Claude Opus 4.1 has a larger context window (200K vs 128K tokens).
  • Gemini 2.5 Computer Use is faster at 85 tok/s vs 46 tok/s.
Need definitions for token pricing, context, or benchmarks?Explore AI Glossary →
FeatureClaude Opus 4.1Gemini 2.5 Computer Use
Intelligence Index
Composite reasoning & knowledge score (0-100)
6265
Provider
AnthropicGoogle
Input Price
Cost per million input tokens
$15.00 / 1M$1.50 / 1M
Output Price
Cost per million output tokens
$75.00 / 1M$8.00 / 1M
Blended Price
Weighted 7:2:1 cache:input:output per 1M
$11.55 / 1M$1.36 / 1M
Context Window
Maximum input + output tokens
200K tokens~300 A4 pages of text128K tokens~192 A4 pages of text
Max Output Tokens
Per single request
32K16K
Throughput Speed
Tokens generated per second
46 tok/s85 tok/s
SWE-bench Verified
Real-world software engineering
74.5%N/A
GPQA Diamond
Graduate-level reasoning
74.4%N/A
Cached Input Price
Prompt caching discount per 1M tokens
$1.50 / 1M$0.38 / 1M

Wer gewinnt in welcher Disziplin?

At-a-glance decision framework
Coding

Evaluations ongoing

Cost
Gemini 2.5 Computer Use
9.2x cheaper monthly runtime
Speed
Gemini 2.5 Computer Use
+85% faster generation
Context
Claude Opus 4.1
200K tokens window

Geprüfte Benchmark-Ergebnisse im Vergleich

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

Claude Opus 4.1Gemini 2.5 Computer Use
SWE-bench Verified (Autonomous Coding)

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

74.5%vsN/A
GPQA Diamond (Doctorate-Level Science & Math)

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

74.4%vsN/A
MMLU-Pro (Multi-task Language Understanding)

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

86.8%vsN/A
LMSYS Chatbot Arena Elo

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

1372ptsvs1365pts
Terminal-Bench (Agentic Coding & Terminal Use)

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

45%vs45.2%
Generation Speed (Throughput)

Tokens emitted per second during active generation streaming.

46 tok/s vs85 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
Claude Opus 4.11.70s
Gemini 2.5 Computer Use0.65s
Est. End-to-End Response (500 tokens)TTFT + generation time
Claude Opus 4.112.57s
Gemini 2.5 Computer Use6.53s

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)
Claude Opus 4.1 Monthly API Bill
$92.25 / month
$15/1M in · $75/1M out
Gemini 2.5 Computer Use Monthly API Bill
$10.01 / month
$1.5/1M in · $8/1M out
Gemini 2.5 Computer Use saves approximately $82.24 / month (89%) under this workload.9.2x Savings

Claude Opus 4.1 · Strengths & Key Advantages

  • 200K Kontextfenster und bis zu 32K maximale Output-Token (SWE-bench Verified 74.5% · GPQA Diamond 74.4%)
  • Hohe Generierungsgeschwindigkeit von 46 Token/Sekunde bei nur 1700 ms Erstlatenz (TTFT)
  • Effiziente API-Struktur ($15/$75 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

Gemini 2.5 Computer Use · Strengths & Key Advantages

  • 128K Kontextfenster und bis zu 16K maximale Output-Token (Arena Elo 1365)
  • Hohe Generierungsgeschwindigkeit von 85 Token/Sekunde bei nur 650 ms Erstlatenz (TTFT)
  • Effiziente API-Struktur ($1.5/$8 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

Token Use & Task Economics

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

MetricClaude Opus 4.1Gemini 2.5 Computer Use
Cost per Task
Estimated USD to finish one task
$16.46$1.15
Output Tokens / Task
Tokens generated per task
72K15K
Reasoning Tokens / Task
Thinking tokens burned per task
37K6K

Technische Spezifikationen

Architecture, release timeline, capabilities, and modalities.

FeatureClaude Opus 4.1Gemini 2.5 Computer Use
Official API Model ID (SDK)claude-opus-4-1-20250801models/gemini-2-5-computer-use
API ProtocolAnthropic Messages API + AWS Bedrock + Vertex AIGoogle Gemini API (generateContent) + OpenAI-Compatible SDK
Release Date2025-082025-10
Knowledge CutoffMarch 2025June 2025
ArchitectureRefined Frontier Reasoning TransformerAction-grounded vision-language agent model
ParametersConfidentialConfidential
Enterprise Rate Limits (RPM / TPM)4,000 – 10,000 RPM (Tier 4 + Priority Tier) · 800,000 – 2,000,000 TPM10,000 – 30,000 RPM (Tier 5 Enterprise) · 800,000 – 2,000,000 TPM
Long-Context Tier (>128K/200K)Standard rate up to 200K tokens; 2x input/output tier above 200K tokensFlat rate ($1.5/1M in) across full 128K window
Prompt Cache Policy & TTL$1.5/1M cached read (90% off); 5-min default & 1-hour extended TTLImplicit + Explicit Context Caching at $0.375/1M with configurable 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 & SandboxNative Web Search Citations + Code Execution Tool + MCP ConnectorsBuilt-in Google Search Grounding + Managed Python Code Execution Sandbox
Official Fine-Tuning SupportCustom Model Tuning via Amazon Bedrock & Prompt DistillationVertex AI Supervised Adapter Tuning & Context Distillation
Multimodal Token BillingText BPE (~4 chars/token) · Vision (~258–765 tokens per image tile)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 ClassificationAnthropic RSP ASL-2 / ASL-3 Constitutional Safety EvaluatedGoogle DeepMind Frontier Safety Framework Verified
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, visiontext, vision
Output Modalitiestexttext

Claude Opus 4.1 vs Gemini 2.5 Computer Use: Schnelle Antworten (FAQ)

Which is more intelligent, Claude Opus 4.1 or Gemini 2.5 Computer Use?

Gemini 2.5 Computer Use is more intelligent. It scores 65 compared with 62 on the composite Intelligence Index.

Which model is faster?

Gemini 2.5 Computer Use is faster, generating 85 tokens per second compared with 46 tokens per second.

Which model is cheaper to run?

Gemini 2.5 Computer Use is cheaper at $1.36 per 1M tokens blended, compared with $11.55 (7:2:1 cache:input:output ratio).

Which model has lower latency?

Gemini 2.5 Computer Use has lower latency, with a time to first token of 0.65s compared with 1.70s.

Which model has a larger context window?

Claude Opus 4.1 has a larger context window, supporting 200K tokens compared with 128K tokens.

Fazit

Sowohl Claude Opus 4.1 (Optimal für autonome Agenten-Workflows, zuverlässiges Tool-Calling und mehrstufige Automatisierung, Enterprise-RAG-Systeme und skalierbare API-Pipelines.) als auch Gemini 2.5 Computer Use (Optimal für autonome Agenten-Workflows, zuverlässiges Tool-Calling und mehrstufige Automatisierung, Enterprise-RAG-Systeme und skalierbare API-Pipelines.) überzeugen im Produktionseinsatz: Gemini 2.5 Computer Use führt bei komplexem Reasoning und Coding, Gemini 2.5 Computer Use liefert den höheren Token-Durchsatz und Gemini 2.5 Computer Use ist die kosteneffizienteste Wahl für große API-Workloads.

Häufig gestellte Fragen (FAQ)

Welches Modell ist besser für Coding und Reasoning – Claude Opus 4.1 oder Gemini 2.5 Computer Use?+

Im Gesamt-Intelligenzindex und bei Software-Benchmarks liegt Gemini 2.5 Computer Use vorn. Prüfen Sie oben die SWE-bench- und GPQA-Werte für Ihren Anwendungsfall.

Wie unterscheiden sich die API-Preise von Claude Opus 4.1 und Gemini 2.5 Computer Use?+

Claude Opus 4.1 kostet $15.00 / $75.00 pro 1M Input-/Output-Tokens, Gemini 2.5 Computer Use liegt bei $1.50 / $8.00. Beim gewichteten Gesamtpreis ist Gemini 2.5 Computer Use günstiger.

Welches Modell hat das größere Kontextfenster und die höhere Geschwindigkeit?+

Claude Opus 4.1 bietet 200K Tokens Kontext gegenüber 128K Tokens bei Gemini 2.5 Computer Use. Bei der Generierungsgeschwindigkeit liegt Gemini 2.5 Computer Use vorn.

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: Offizielle API-Dokumentation von Anthropic und Google, Systemkarten und unabhängige Benchmark-Auswertungen (2026).