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Claude Haiku 4.5 vs GPT-5 Chat

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 Haiku 4.5 vs GPT-5 Chat: Benchmarks, Pricing & Speed Comparison

Claude Haiku 4.5 von Anthropic und GPT-5 Chat von OpenAI gehören zu den führenden KI-Modellen. Claude Haiku 4.5 bietet ein Kontextfenster von 200K Tokens bei API-Preisen von $1.00/$5.00 pro 1M Tokens, während GPT-5 Chat 128K Tokens Kontext zu $0.00/$0.00 pro 1M Tokens bereitstellt. Hier finden Sie den vollständigen Benchmark-, Latenz- und Kostenvergleich.

Direktvergleich (VS)

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Anthropic

Claude Haiku 4.5

Ultraschnelle Echtzeit-Inferenz

Claude Haiku 4.5 von Anthropic ist ein KI-Modell für ultraschnelle Echtzeit-Antworten, niedrige Latenz und Hochdurchsatz-Routing mit 200K Kontextfenster, 140 Token/s Durchsatz, einem Intelligenz-Index von 54/100 und $1/$5 pro 1M Token.

Intelligence Index54 / 100
Input Token:

$1.00 / 1M

Output Token:

$5.00 / 1M

Context Window:

200K tokens

SWE-bench Verified:

58.2%

OpenAI

GPT-5 Chat

Frontier-Flaggschiff-Modell

GPT-5 Chat von OpenAI ist ein KI-Modell für anspruchsvolles Enterprise-Reasoning, Softwareentwicklung und produktive KI-Workflows mit 128K Kontextfenster, 140 Token/s Durchsatz, einem Intelligenz-Index von 56/100 und kostenlosem Open-Weight

Intelligence Index56 / 100
Input Token:

$0.00 / 1M

Output Token:

$0.00 / 1M

Context Window:

128K tokens

SWE-bench Verified:

70%

Wichtigste Unterschiede auf einen Blick

  • GPT-5 Chat is 1.0x cheaper for API usage (input + output tokens combined).
  • Claude Haiku 4.5 has a larger context window (200K vs 128K tokens).
  • GPT-5 Chat is faster at 140 tok/s vs 140 tok/s.
  • GPT-5 Chat leads on SWE-bench coding (70.0% vs 58.2%).
Need definitions for token pricing, context, or benchmarks?Explore AI Glossary →
FeatureClaude Haiku 4.5GPT-5 Chat
Intelligence Index
Composite reasoning & knowledge score (0-100)
5456
Provider
AnthropicOpenAI
Input Price
Cost per million input tokens
$1.00 / 1M$0.00 / 1M
Output Price
Cost per million output tokens
$5.00 / 1M$0.00 / 1M
Blended Price
Weighted 7:2:1 cache:input:output per 1M
$0.77 / 1M$0.00 / 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
64K16K
Throughput Speed
Tokens generated per second
140 tok/s140 tok/s
SWE-bench Verified
Real-world software engineering
58.2%70%
GPQA Diamond
Graduate-level reasoning
62.1%79%
Cached Input Price
Prompt caching discount per 1M tokens
$0.10 / 1M$0.00 / 1M

Wer gewinnt in welcher Disziplin?

At-a-glance decision framework
Coding
GPT-5 Chat
+11.8% SWE-bench lead
Cost
GPT-5 Chat
1.0x cheaper monthly runtime
Speed
GPT-5 Chat
+0% faster generation
Context
Claude Haiku 4.5
200K tokens window

Geprüfte Benchmark-Ergebnisse im Vergleich

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

Claude Haiku 4.5GPT-5 Chat
SWE-bench Verified (Autonomous Coding)

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

58.2%vs70%
GPQA Diamond (Doctorate-Level Science & Math)

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

62.1%vs79%
MMLU-Pro (Multi-task Language Understanding)

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

79.5%vs85%
LMSYS Chatbot Arena Elo

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

1324ptsvs1358pts
Humanity's Last Exam (Frontier Expert Knowledge)

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

N/Avs11.6%
Terminal-Bench (Agentic Coding & Terminal Use)

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

N/Avs42.5%
SciCode (Scientific Computing)

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

N/Avs40%
LiveCodeBench (Competitive Coding)

Contamination-free competitive programming problems collected continuously over time.

N/Avs68%
AIME (Advanced Math Competition)

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

N/Avs88%
Long-Context Reasoning

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

N/Avs76%
Generation Speed (Throughput)

Tokens emitted per second during active generation streaming.

140 tok/s vs140 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 Haiku 4.50.28s
GPT-5 Chat1.05s
Est. End-to-End Response (500 tokens)TTFT + generation time
Claude Haiku 4.53.85s
GPT-5 Chat4.62s

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 Haiku 4.5 Monthly API Bill
$6.15 / month
$1/1M in · $5/1M out
GPT-5 Chat Monthly API Bill
$0.00 / month
$0/1M in · $0/1M out
GPT-5 Chat saves approximately $6.15 / month (100%) under this workload.1.0x Savings

Claude Haiku 4.5 · Strengths & Key Advantages

  • 200K Kontextfenster und bis zu 64K maximale Output-Token (SWE-bench Verified 58.2% · GPQA Diamond 62.1%)
  • Hohe Generierungsgeschwindigkeit von 140 Token/Sekunde bei nur 280 ms Erstlatenz (TTFT)
  • Effiziente API-Struktur ($1/$5 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

GPT-5 Chat · Strengths & Key Advantages

  • 128K Kontextfenster und bis zu 16K maximale Output-Token (SWE-bench Verified 70% · GPQA Diamond 79%)
  • Hohe Generierungsgeschwindigkeit von 140 Token/Sekunde bei nur 1050 ms Erstlatenz (TTFT)
  • Effiziente API-Struktur (kostenlosem Open-Weights-Zugang) 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 Haiku 4.5GPT-5 Chat
Cost per Task
Estimated USD to finish one task
$0.70$1.50
Output Tokens / Task
Tokens generated per task
20K54K
Reasoning Tokens / Task
Thinking tokens burned per task
10K28K

Technische Spezifikationen

Architecture, release timeline, capabilities, and modalities.

FeatureClaude Haiku 4.5GPT-5 Chat
Official API Model ID (SDK)claude-haiku-4-5-20251001gpt-5-chat
API ProtocolAnthropic Messages API + AWS Bedrock + Vertex AIOpenAI Responses API & Chat Completions v1
Release Date2025-102025-08
Knowledge CutoffJuly 2025September 2024
ArchitectureLightweight High-Speed Multimodal TransformerChat-tuned unified reasoning 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 tokensFree across full context window (only KV-cache VRAM scales)
Prompt Cache Policy & TTL$0.1/1M cached read (90% off); 5-min default & 1-hour extended TTLAutomatic prefix KV-caching in vLLM / SGLang (0 cost)
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
Web Search Grounding & SandboxNative Web Search Citations + Code Execution Tool + MCP ConnectorsNative Web Search tool + Hosted Code Interpreter & File Search RAG
Official Fine-Tuning SupportCustom Model Tuning via Amazon Bedrock & Prompt DistillationSupervised Fine-Tuning (SFT), Direct Preference (DPO) & Reinforcement Fine-Tuning (RFT)
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 EvaluatedOpenAI Preparedness Framework Audited & System Card Published
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 Haiku 4.5 vs GPT-5 Chat: Schnelle Antworten (FAQ)

Which is more intelligent, Claude Haiku 4.5 or GPT-5 Chat?

GPT-5 Chat is more intelligent. It scores 56 compared with 54 on the composite Intelligence Index.

Which model is cheaper to run?

GPT-5 Chat is cheaper at $0.00 per 1M tokens blended, compared with $0.77 (7:2:1 cache:input:output ratio).

Which model has lower latency?

Claude Haiku 4.5 has lower latency, with a time to first token of 0.28s compared with 1.05s.

Which model has a larger context window?

Claude Haiku 4.5 has a larger context window, supporting 200K tokens compared with 128K tokens.

Fazit

Sowohl Claude Haiku 4.5 (Optimal für ultraschnelle Echtzeit-Antworten, niedrige Latenz und Hochdurchsatz-Routing, Enterprise-RAG-Systeme und skalierbare API-Pipelines.) als auch GPT-5 Chat (Optimal für anspruchsvolles Enterprise-Reasoning, Softwareentwicklung und produktive KI-Workflows, Enterprise-RAG-Systeme und skalierbare API-Pipelines.) überzeugen im Produktionseinsatz: GPT-5 Chat führt bei komplexem Reasoning und Coding, Claude Haiku 4.5 liefert den höheren Token-Durchsatz und GPT-5 Chat ist die kosteneffizienteste Wahl für große API-Workloads.

Häufig gestellte Fragen (FAQ)

Welches Modell ist besser für Coding und Reasoning – Claude Haiku 4.5 oder GPT-5 Chat?+

Im Gesamt-Intelligenzindex und bei Software-Benchmarks liegt GPT-5 Chat vorn. Prüfen Sie oben die SWE-bench- und GPQA-Werte für Ihren Anwendungsfall.

Wie unterscheiden sich die API-Preise von Claude Haiku 4.5 und GPT-5 Chat?+

Claude Haiku 4.5 kostet $1.00 / $5.00 pro 1M Input-/Output-Tokens, GPT-5 Chat liegt bei $0.00 / $0.00. Beim gewichteten Gesamtpreis ist GPT-5 Chat günstiger.

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

Claude Haiku 4.5 bietet 200K Tokens Kontext gegenüber 128K Tokens bei GPT-5 Chat. Bei der Generierungsgeschwindigkeit liegt Claude Haiku 4.5 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.

Tokens & PricingContext WindowAI BenchmarksReasoning ModelsTool CallingModel Context Protocol (MCP)

Related reading

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 OpenAI, Systemkarten und unabhängige Benchmark-Auswertungen (2026).