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o3-pro vs GPT-6 Astra

Benchmarks, API Token Pricing, Context Window & Speed Comparison

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AI CompareAI BenchmarkToken PricingModel CostModel SpecsSWE-bench CodingModel VersusWhich AI ModelLLM Speed & LatencyReasoning ModelsExtended ThinkingPrompt Caching ROI
o3-pro vs GPT-6 Astra: Benchmarks, Pricing & Speed Comparison

o3-pro von OpenAI und GPT-6 Astra von OpenAI 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 GPT-6 Astra 272K Tokens Kontext zu $10.00/$50.00 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%

OpenAI

GPT-6 Astra

Natives Sprach- & Audiomodell

GPT-6 Astra von OpenAI ist ein KI-Modell für natürliche Sprachsynthese, Echtzeit-Audioverarbeitung und präzise Transkription mit 272K Kontextfenster, 100 Token/s Durchsatz, einem Intelligenz-Index von 96/100 und $10/$50 pro 1M Token.

Intelligence Index96 / 100
Input Token:

$10.00 / 1M

Output Token:

$50.00 / 1M

Context Window:

272K tokens

SWE-bench Verified:

82.4%

Wichtigste Unterschiede auf einen Blick

  • GPT-6 Astra is 1.8x cheaper for API usage (input + output tokens combined).
  • GPT-6 Astra has a larger context window (272K vs 200K tokens).
  • GPT-6 Astra is faster at 100 tok/s vs 30 tok/s.
  • GPT-6 Astra leads on SWE-bench coding (82.4% vs 71.5%).
Need definitions for token pricing, context, or benchmarks?Explore AI Glossary →
Featureo3-proGPT-6 Astra
Intelligence Index
Composite reasoning & knowledge score (0-100)
5896
Provider
OpenAIOpenAI
Input Price
Cost per million input tokens
$20.00 / 1M$10.00 / 1M
Output Price
Cost per million output tokens
$80.00 / 1M$50.00 / 1M
Blended Price
Weighted 7:2:1 cache:input:output per 1M
$15.50 / 1M$7.70 / 1M
Context Window
Maximum input + output tokens
200K tokens~300 A4 pages of text272K tokens~408 A4 pages of text
Max Output Tokens
Per single request
100K128K
Throughput Speed
Tokens generated per second
30 tok/s100 tok/s
SWE-bench Verified
Real-world software engineering
71.5%82.4%
GPQA Diamond
Graduate-level reasoning
79.5%80.9%
Cached Input Price
Prompt caching discount per 1M tokens
$5.00 / 1M$1.00 / 1M

Wer gewinnt in welcher Disziplin?

At-a-glance decision framework
Coding
GPT-6 Astra
+10.9% SWE-bench lead
Cost
GPT-6 Astra
1.8x cheaper monthly runtime
Speed
GPT-6 Astra
+233% faster generation
Context
GPT-6 Astra
272K tokens window

Geprüfte Benchmark-Ergebnisse im Vergleich

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

o3-proGPT-6 Astra
SWE-bench Verified (Autonomous Coding)

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

71.5%vs82.4%
GPQA Diamond (Doctorate-Level Science & Math)

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

79.5%vs80.9%
MMLU-Pro (Multi-task Language Understanding)

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

88.5%vs89.9%
LMSYS Chatbot Arena Elo

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

1352ptsvs1520pts
Humanity's Last Exam (Frontier Expert Knowledge)

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

13.6%vs18.2%
Terminal-Bench (Agentic Coding & Terminal Use)

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

47.5%vs63.8%
SciCode (Scientific Computing)

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

45.5%vs54.9%
LiveCodeBench (Competitive Coding)

Contamination-free competitive programming problems collected continuously over time.

73%vs79.8%
AIME (Advanced Math Competition)

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

93%vs93.6%
Long-Context Reasoning

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

80.5%vs91.2%
Generation Speed (Throughput)

Tokens emitted per second during active generation streaming.

30 tok/s vs100 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
GPT-6 Astra0.95s
Est. End-to-End Response (500 tokens)TTFT + generation time
o3-pro21.87s
GPT-6 Astra5.95s

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
GPT-6 Astra Monthly API Bill
$61.50 / month
$10/1M in · $50/1M out
GPT-6 Astra saves approximately $48.00 / month (44%) under this workload.1.8x 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

GPT-6 Astra · Strengths & Key Advantages

  • 272K Kontextfenster und bis zu 128K maximale Output-Token (SWE-bench Verified 82.4% · GPQA Diamond 80.9%)
  • Hohe Generierungsgeschwindigkeit von 100 Token/Sekunde bei nur 950 ms Erstlatenz (TTFT)
  • Effiziente API-Struktur ($10/$50 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-proGPT-6 Astra
Cost per Task
Estimated USD to finish one task
$11.68$2.15
Output Tokens / Task
Tokens generated per task
58K58K
Reasoning Tokens / Task
Thinking tokens burned per task
38K32K

Technische Spezifikationen

Architecture, release timeline, capabilities, and modalities.

Featureo3-proGPT-6 Astra
Official API Model ID (SDK)o3-progpt-6-astra
API ProtocolOpenAI Responses API & Chat Completions v1OpenAI Responses API & Chat Completions v1
Release Date2025-062026-09
Knowledge CutoffJune 2024June 2026
ArchitectureHigh-effort reasoning transformerOmni-Adaptive Autoregressive with Dynamic CoT
ParametersConfidentialConfidential
Enterprise Rate Limits (RPM / TPM)10,000 – 30,000 RPM (Tier 5 Enterprise) · 800,000 – 2,000,000 TPM10,000 – 30,000 RPM (Tier 5 Enterprise) · 800,000 – 2,000,000 TPM
Long-Context Tier (>128K/200K)Flat rate ($20/1M in) across full 200K windowFlat rate ($10/1M in) across full 272K window
Prompt Cache Policy & TTLAutomatic prefix caching at $5/1M (no extra cache-write fee)Automatic prefix caching at $1/1M (no extra cache-write fee)
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 tool + Hosted Code Interpreter & File Search RAG
Official Fine-Tuning SupportSupervised Fine-Tuning (SFT), Direct Preference (DPO) & Reinforcement Fine-Tuning (RFT)Supervised 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) · Audio (~25–32 tokens/sec)
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 PublishedOpenAI 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, audio
Output Modalitiestexttext, audio

o3-pro vs GPT-6 Astra: Schnelle Antworten (FAQ)

Which is more intelligent, o3-pro or GPT-6 Astra?

GPT-6 Astra is more intelligent. It scores 96 compared with 58 on the composite Intelligence Index.

Which model is faster?

GPT-6 Astra is faster, generating 100 tokens per second compared with 30 tokens per second.

Which model is cheaper to run?

GPT-6 Astra is cheaper at $7.70 per 1M tokens blended, compared with $15.50 (7:2:1 cache:input:output ratio).

Which model has lower latency?

GPT-6 Astra has lower latency, with a time to first token of 0.95s compared with 5.20s.

Which model has a larger context window?

GPT-6 Astra has a larger context window, supporting 272K 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 GPT-6 Astra (Optimal für natürliche Sprachsynthese, Echtzeit-Audioverarbeitung und präzise Transkription, Enterprise-RAG-Systeme und skalierbare API-Pipelines.) überzeugen im Produktionseinsatz: GPT-6 Astra führt bei komplexem Reasoning und Coding, GPT-6 Astra liefert den höheren Token-Durchsatz und GPT-6 Astra ist die kosteneffizienteste Wahl für große API-Workloads.

Häufig gestellte Fragen (FAQ)

Welches Modell ist besser für Coding und Reasoning – o3-pro oder GPT-6 Astra?+

Im Gesamt-Intelligenzindex und bei Software-Benchmarks liegt GPT-6 Astra vorn. Prüfen Sie oben die SWE-bench- und GPQA-Werte für Ihren Anwendungsfall.

Wie unterscheiden sich die API-Preise von o3-pro und GPT-6 Astra?+

o3-pro kostet $20.00 / $80.00 pro 1M Input-/Output-Tokens, GPT-6 Astra liegt bei $10.00 / $50.00. Beim gewichteten Gesamtpreis ist GPT-6 Astra günstiger.

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

o3-pro bietet 200K Tokens Kontext gegenüber 272K Tokens bei GPT-6 Astra. Bei der Generierungsgeschwindigkeit liegt GPT-6 Astra 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 OpenAI, Systemkarten und unabhängige Benchmark-Auswertungen (2026).