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o3-pro vs Grok 4.20 (Reasoning)

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
o3-pro vs Grok 4.20 (Reasoning): Benchmarks, Pricing & Speed Comparison

o3-pro von OpenAI und Grok 4.20 (Reasoning) von xAI gehören zu den führenden KI-Modellen. o3-pro bietet ein Kontextfenster von 200K Tokens bei API-Preisen von $20.00/$80.00 pro 1M Tokens, während Grok 4.20 (Reasoning) 1M Tokens Kontext zu $3.00/$15.00 pro 1M Tokens bereitstellt. Hier finden Sie den vollständigen Benchmark-, Latenz- und Kostenvergleich.

Direktvergleich (VS)

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OpenAI

o3-pro

Deep-Reasoning-Engine

o3-pro von OpenAI ist ein KI-Modell für tiefgehendes logisches Denken, komplexe Mathematik und wissenschaftliche Analysen mit 200K Kontextfenster, 30 Token/s Durchsatz, einem Intelligenz-Index von 58/100 und $20/$80 pro 1M Token.

Intelligence Index58 / 100
Input Token:

$20.00 / 1M

Output Token:

$80.00 / 1M

Context Window:

200K tokens

SWE-bench Verified:

71.5%

xAI

Grok 4.20 (Reasoning)

Deep-Reasoning-Engine

Grok 4.20 (Reasoning) von xAI ist ein KI-Modell für tiefgehendes logisches Denken, komplexe Mathematik und wissenschaftliche Analysen mit 1M Kontextfenster, 95 Token/s Durchsatz, einem Intelligenz-Index von 68/100 und $3/$15 pro 1M Token.

Intelligence Index68 / 100
Input Token:

$3.00 / 1M

Output Token:

$15.00 / 1M

Context Window:

1M tokens

SWE-bench Verified:

68.2%

Wichtigste Unterschiede auf einen Blick

  • Grok 4.20 (Reasoning) is 5.7x cheaper for API usage (input + output tokens combined).
  • Grok 4.20 (Reasoning) has a larger context window (1M vs 200K tokens).
  • Grok 4.20 (Reasoning) is faster at 95 tok/s vs 30 tok/s.
  • o3-pro leads on SWE-bench coding (71.5% vs 68.2%).
Need definitions for token pricing, context, or benchmarks?Explore AI Glossary →
Featureo3-proGrok 4.20 (Reasoning)
Intelligence Index
Composite reasoning & knowledge score (0-100)
5868
Provider
OpenAIxAI
Input Price
Cost per million input tokens
$20.00 / 1M$3.00 / 1M
Output Price
Cost per million output tokens
$80.00 / 1M$15.00 / 1M
Blended Price
Weighted 7:2:1 cache:input:output per 1M
$15.50 / 1M$2.63 / 1M
Context Window
Maximum input + output tokens
200K tokens~300 A4 pages of text1M tokens~1,500 A4 pages of text
Max Output Tokens
Per single request
100K66K
Throughput Speed
Tokens generated per second
30 tok/s95 tok/s
SWE-bench Verified
Real-world software engineering
71.5%68.2%
GPQA Diamond
Graduate-level reasoning
79.5%72.8%
Cached Input Price
Prompt caching discount per 1M tokens
$5.00 / 1M$0.75 / 1M

Wer gewinnt in welcher Disziplin?

At-a-glance decision framework
Coding
o3-pro
+3.3% SWE-bench lead
Cost
Grok 4.20 (Reasoning)
5.7x cheaper monthly runtime
Speed
Grok 4.20 (Reasoning)
+217% faster generation
Context
Grok 4.20 (Reasoning)
1M tokens window

Geprüfte Benchmark-Ergebnisse im Vergleich

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

o3-proGrok 4.20 (Reasoning)
SWE-bench Verified (Autonomous Coding)

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

71.5%vs68.2%
GPQA Diamond (Doctorate-Level Science & Math)

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

79.5%vs72.8%
MMLU-Pro (Multi-task Language Understanding)

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

88.5%vs84.1%
LMSYS Chatbot Arena Elo

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

1352ptsvs1395pts
Humanity's Last Exam (Frontier Expert Knowledge)

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

13.6%vs11.8%
Terminal-Bench (Agentic Coding & Terminal Use)

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

47.5%vs44.5%
SciCode (Scientific Computing)

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

45.5%vs41.2%
LiveCodeBench (Competitive Coding)

Contamination-free competitive programming problems collected continuously over time.

73%vs66.5%
AIME (Advanced Math Competition)

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

93%vs86.4%
Long-Context Reasoning

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

80.5%vs89.2%
Generation Speed (Throughput)

Tokens emitted per second during active generation streaming.

30 tok/s vs95 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
o3-pro5.20s
Grok 4.20 (Reasoning)0.98s
Est. End-to-End Response (500 tokens)TTFT + generation time
o3-pro21.87s
Grok 4.20 (Reasoning)6.24s

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)
o3-pro Monthly API Bill
$109.50 / month
$20/1M in · $80/1M out
Grok 4.20 (Reasoning) Monthly API Bill
$19.13 / month
$3/1M in · $15/1M out
Grok 4.20 (Reasoning) saves approximately $90.38 / month (83%) under this workload.5.7x Savings

o3-pro · Strengths & Key Advantages

  • 200K Kontextfenster und bis zu 100K maximale Output-Token (SWE-bench Verified 71.5% · GPQA Diamond 79.5%)
  • Hohe Generierungsgeschwindigkeit von 30 Token/Sekunde bei nur 5200 ms Erstlatenz (TTFT)
  • Effiziente API-Struktur ($20/$80 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

Grok 4.20 (Reasoning) · Strengths & Key Advantages

  • 1M Kontextfenster und bis zu 66K maximale Output-Token (SWE-bench Verified 68.2% · GPQA Diamond 72.8%)
  • Hohe Generierungsgeschwindigkeit von 95 Token/Sekunde bei nur 980 ms Erstlatenz (TTFT)
  • Effiziente API-Struktur ($3/$15 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.

Metrico3-proGrok 4.20 (Reasoning)
Cost per Task
Estimated USD to finish one task
$11.68$1.45
Output Tokens / Task
Tokens generated per task
58K45K
Reasoning Tokens / Task
Thinking tokens burned per task
38K28K

Technische Spezifikationen

Architecture, release timeline, capabilities, and modalities.

Featureo3-proGrok 4.20 (Reasoning)
Official API Model ID (SDK)o3-progrok-4-20-reasoning-latest
API ProtocolOpenAI Responses API & Chat Completions v1xAI REST API (OpenAI-Compatible)
Release Date2025-062026-03
Knowledge CutoffJune 2024November 2025
ArchitectureHigh-effort reasoning transformerColossus-Scale Reasoning Sparse MoE
ParametersConfidentialConfidential
Enterprise Rate Limits (RPM / TPM)10,000 – 30,000 RPM (Tier 5 Enterprise) · 800,000 – 2,000,000 TPM5,000 – 15,000 RPM (Production Tier) · 4,000,000 – 10,000,000 TPM
Long-Context Tier (>128K/200K)Flat rate ($20/1M in) across full 200K windowFlat rate ($3/1M in) across full 1000K window
Prompt Cache Policy & TTLAutomatic prefix caching at $5/1M (no extra cache-write fee)Cached input at $0.75/1M tokens
Computer Use / GUI AgentSupported (Screen coordinate grounding, browser & desktop GUI action loops)API / CLI Tool-Use & DOM Agent ready (no raw pixel desktop click loop)
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 RAGReal-time Web & X (Twitter) Search Grounding + Code Execution
Official Fine-Tuning SupportSupervised Fine-Tuning (SFT), Direct Preference (DPO) & Reinforcement Fine-Tuning (RFT)API Prompt Engineering & RAG 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 PublishedxAI Production Safety & Alignment 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

o3-pro vs Grok 4.20 (Reasoning): Schnelle Antworten (FAQ)

Which is more intelligent, o3-pro or Grok 4.20 (Reasoning)?

Grok 4.20 (Reasoning) is more intelligent. It scores 68 compared with 58 on the composite Intelligence Index.

Which model is faster?

Grok 4.20 (Reasoning) is faster, generating 95 tokens per second compared with 30 tokens per second.

Which model is cheaper to run?

Grok 4.20 (Reasoning) is cheaper at $2.63 per 1M tokens blended, compared with $15.50 (7:2:1 cache:input:output ratio).

Which model has lower latency?

Grok 4.20 (Reasoning) has lower latency, with a time to first token of 0.98s compared with 5.20s.

Which model has a larger context window?

Grok 4.20 (Reasoning) has a larger context window, supporting 1M tokens compared with 200K tokens.

Fazit

Sowohl o3-pro (Optimal für tiefgehendes logisches Denken, komplexe Mathematik und wissenschaftliche Analysen, Enterprise-RAG-Systeme und skalierbare API-Pipelines.) als auch Grok 4.20 (Reasoning) (Optimal für tiefgehendes logisches Denken, komplexe Mathematik und wissenschaftliche Analysen, Enterprise-RAG-Systeme und skalierbare API-Pipelines.) überzeugen im Produktionseinsatz: Grok 4.20 (Reasoning) führt bei komplexem Reasoning und Coding, Grok 4.20 (Reasoning) liefert den höheren Token-Durchsatz und Grok 4.20 (Reasoning) ist die kosteneffizienteste Wahl für große API-Workloads.

Häufig gestellte Fragen (FAQ)

Welches Modell ist besser für Coding und Reasoning – o3-pro oder Grok 4.20 (Reasoning)?+

Im Gesamt-Intelligenzindex und bei Software-Benchmarks liegt Grok 4.20 (Reasoning) vorn. Prüfen Sie oben die SWE-bench- und GPQA-Werte für Ihren Anwendungsfall.

Wie unterscheiden sich die API-Preise von o3-pro und Grok 4.20 (Reasoning)?+

o3-pro kostet $20.00 / $80.00 pro 1M Input-/Output-Tokens, Grok 4.20 (Reasoning) liegt bei $3.00 / $15.00. Beim gewichteten Gesamtpreis ist Grok 4.20 (Reasoning) günstiger.

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

o3-pro bietet 200K Tokens Kontext gegenüber 1M Tokens bei Grok 4.20 (Reasoning). Bei der Generierungsgeschwindigkeit liegt Grok 4.20 (Reasoning) 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 xAI, Systemkarten und unabhängige Benchmark-Auswertungen (2026).