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GPT-5 mini vs Claude Haiku 4.5

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

GPT-5 mini von OpenAI und Claude Haiku 4.5 von Anthropic gehören zu den führenden KI-Modellen. GPT-5 mini bietet ein Kontextfenster von 400K Tokens bei API-Preisen von $0.25/$2.00 pro 1M Tokens, während Claude Haiku 4.5 200K Tokens Kontext zu $1.00/$5.00 pro 1M Tokens bereitstellt. Hier finden Sie den vollständigen Benchmark-, Latenz- und Kostenvergleich.

Direktvergleich (VS)

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OpenAI

GPT-5 mini

Kompaktes Effizienz-Modell

GPT-5 mini von OpenAI ist ein KI-Modell für maximale Kosteneffizienz pro Token und ressourcenschonende Produktions-Workloads mit 400K Kontextfenster, 185 Token/s Durchsatz, einem Intelligenz-Index von 46/100 und $0.25/$2 pro 1M Token.

Intelligence Index46 / 100
Input Token:

$0.25 / 1M

Output Token:

$2.00 / 1M

Context Window:

400K tokens

SWE-bench Verified:

52%

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%

Wichtigste Unterschiede auf einen Blick

  • GPT-5 mini is 2.8x cheaper for API usage (input + output tokens combined).
  • GPT-5 mini has a larger context window (400K vs 200K tokens).
  • GPT-5 mini is faster at 185 tok/s vs 140 tok/s.
  • Claude Haiku 4.5 leads on SWE-bench coding (58.2% vs 52.0%).
Need definitions for token pricing, context, or benchmarks?Explore AI Glossary →
FeatureGPT-5 miniClaude Haiku 4.5
Intelligence Index
Composite reasoning & knowledge score (0-100)
4654
Provider
OpenAIAnthropic
Input Price
Cost per million input tokens
$0.25 / 1M$1.00 / 1M
Output Price
Cost per million output tokens
$2.00 / 1M$5.00 / 1M
Blended Price
Weighted 7:2:1 cache:input:output per 1M
$0.27 / 1M$0.77 / 1M
Context Window
Maximum input + output tokens
400K tokens~600 A4 pages of text200K tokens~300 A4 pages of text
Max Output Tokens
Per single request
128K64K
Throughput Speed
Tokens generated per second
185 tok/s140 tok/s
SWE-bench Verified
Real-world software engineering
52%58.2%
GPQA Diamond
Graduate-level reasoning
66%62.1%
Cached Input Price
Prompt caching discount per 1M tokens
$0.03 / 1M$0.10 / 1M

Wer gewinnt in welcher Disziplin?

At-a-glance decision framework
Coding
Claude Haiku 4.5
+6.2% SWE-bench lead
Cost
GPT-5 mini
2.8x cheaper monthly runtime
Speed
GPT-5 mini
+32% faster generation
Context
GPT-5 mini
400K tokens window

Geprüfte Benchmark-Ergebnisse im Vergleich

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

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

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

52%vs58.2%
GPQA Diamond (Doctorate-Level Science & Math)

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

66%vs62.1%
MMLU-Pro (Multi-task Language Understanding)

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

78.5%vs79.5%
LMSYS Chatbot Arena Elo

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

1315ptsvs1324pts
Humanity's Last Exam (Frontier Expert Knowledge)

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

9.2%vsN/A
Terminal-Bench (Agentic Coding & Terminal Use)

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

30.5%vsN/A
SciCode (Scientific Computing)

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

32%vsN/A
LiveCodeBench (Competitive Coding)

Contamination-free competitive programming problems collected continuously over time.

56.5%vsN/A
AIME (Advanced Math Competition)

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

84%vsN/A
Long-Context Reasoning

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

68.5%vsN/A
Generation Speed (Throughput)

Tokens emitted per second during active generation streaming.

185 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
GPT-5 mini0.70s
Claude Haiku 4.50.28s
Est. End-to-End Response (500 tokens)TTFT + generation time
GPT-5 mini3.40s
Claude Haiku 4.53.85s

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)
GPT-5 mini Monthly API Bill
$2.21 / month
$0.25/1M in · $2/1M out
Claude Haiku 4.5 Monthly API Bill
$6.15 / month
$1/1M in · $5/1M out
GPT-5 mini saves approximately $3.94 / month (64%) under this workload.2.8x Savings

GPT-5 mini · Strengths & Key Advantages

  • 400K Kontextfenster und bis zu 128K maximale Output-Token (SWE-bench Verified 52% · GPQA Diamond 66%)
  • Hohe Generierungsgeschwindigkeit von 185 Token/Sekunde bei nur 700 ms Erstlatenz (TTFT)
  • Effiziente API-Struktur ($0.25/$2 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 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

Token Use & Task Economics

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

MetricGPT-5 miniClaude Haiku 4.5
Cost per Task
Estimated USD to finish one task
$0.32$0.70
Output Tokens / Task
Tokens generated per task
50K20K
Reasoning Tokens / Task
Thinking tokens burned per task
24K10K

Technische Spezifikationen

Architecture, release timeline, capabilities, and modalities.

FeatureGPT-5 miniClaude Haiku 4.5
Official API Model ID (SDK)gpt-5-miniclaude-haiku-4-5-20251001
API ProtocolOpenAI Responses API & Chat Completions v1Anthropic Messages API + AWS Bedrock + Vertex AI
Release Date2025-082025-10
Knowledge CutoffSeptember 2024July 2025
ArchitectureCompact unified reasoning modelLightweight High-Speed Multimodal Transformer
ParametersConfidentialConfidential
Enterprise Rate Limits (RPM / TPM)10,000 – 30,000 RPM (Tier 5 Enterprise) · 800,000 – 2,000,000 TPM4,000 – 10,000 RPM (Tier 4 + Priority Tier) · 800,000 – 2,000,000 TPM
Long-Context Tier (>128K/200K)Flat rate ($0.25/1M in) across full 400K windowStandard rate up to 200K tokens; 2x input/output tier above 200K tokens
Prompt Cache Policy & TTLAutomatic prefix caching at $0.025/1M (no extra cache-write fee)$0.1/1M 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 & SandboxNative Web Search tool + Hosted Code Interpreter & File Search RAGNative Web Search Citations + Code Execution Tool + MCP Connectors
Official Fine-Tuning SupportSupervised Fine-Tuning (SFT), Direct Preference (DPO) & Reinforcement Fine-Tuning (RFT)Custom Model Tuning via Amazon Bedrock & Prompt 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 ClassificationOpenAI Preparedness Framework Audited & System Card PublishedAnthropic 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, visiontext, vision
Output Modalitiestexttext

GPT-5 mini vs Claude Haiku 4.5: Schnelle Antworten (FAQ)

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

Claude Haiku 4.5 is more intelligent. It scores 54 compared with 46 on the composite Intelligence Index.

Which model is faster?

GPT-5 mini is faster, generating 185 tokens per second compared with 140 tokens per second.

Which model is cheaper to run?

GPT-5 mini is cheaper at $0.27 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 0.70s.

Which model has a larger context window?

GPT-5 mini has a larger context window, supporting 400K tokens compared with 200K tokens.

Fazit

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

Häufig gestellte Fragen (FAQ)

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

Im Gesamt-Intelligenzindex und bei Software-Benchmarks liegt Claude Haiku 4.5 vorn. Prüfen Sie oben die SWE-bench- und GPQA-Werte für Ihren Anwendungsfall.

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

GPT-5 mini kostet $0.25 / $2.00 pro 1M Input-/Output-Tokens, Claude Haiku 4.5 liegt bei $1.00 / $5.00. Beim gewichteten Gesamtpreis ist GPT-5 mini günstiger.

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

GPT-5 mini bietet 400K Tokens Kontext gegenüber 200K Tokens bei Claude Haiku 4.5. Bei der Generierungsgeschwindigkeit liegt GPT-5 mini 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 OpenAI und Anthropic, Systemkarten und unabhängige Benchmark-Auswertungen (2026).