Head-to-Head Model Comparison

GPT-6 Astra vs GPT-6 Sol

Benchmarks, API Token Pricing, Context Window & Speed Comparison

Geprüft vom GetInfoUs-ForschungsteamZuletzt geprüft: October 2026Redaktionelle Richtlinien
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Compare GPT-6 Astra by OpenAI against GPT-6 Sol by OpenAI across real-world coding, reasoning, token economics, and latency.

Direktvergleich (VS)

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Popular Matchups:
OpenAI

GPT-6 Astra

Deep-Reasoning-Modell

GPT-6 Astra von OpenAI ist ein leistungsstarkes KI-Modell mit einem Kontextfenster von 1M Token zu API-Preisen von $10.0/1M Input- und $50.0/1M Output-Token für Softwareentwicklung, Analyse und Enterprise-Workflows.

Intelligence Index96 / 100
Input Token:

$10.00 / 1M

Output Token:

$50.00 / 1M

Context Window:

272K tokens

SWE-bench Verified:

82.4%

OpenAI

GPT-6 Sol

Deep-Reasoning-Modell

GPT-6 Sol von OpenAI ist ein leistungsstarkes KI-Modell mit einem Kontextfenster von 1M Token zu API-Preisen von $2.0/1M Input- und $10.0/1M Output-Token für Softwareentwicklung, Analyse und Enterprise-Workflows.

Intelligence Index93 / 100
Input Token:

$2.00 / 1M

Output Token:

$10.00 / 1M

Context Window:

1M tokens

SWE-bench Verified:

82.1%

Wichtigste Unterschiede auf einen Blick

  • GPT-6 Sol is 5.1x cheaper for API usage (input + output tokens combined).
  • GPT-6 Sol has a larger context window (1M vs 272K tokens).
  • GPT-6 Sol is faster at 116 tok/s vs 100 tok/s.
  • GPT-6 Astra leads on SWE-bench coding (82.4% vs 82.1%).
Need definitions for token pricing, context, or benchmarks?Explore AI Glossary →
FeatureGPT-6 AstraGPT-6 Sol
Intelligence Index
Composite reasoning & knowledge score (0-100)
9693
Provider
OpenAIOpenAI
Input Price
Cost per million input tokens
$10.00 / 1M$2.00 / 1M
Output Price
Cost per million output tokens
$50.00 / 1M$10.00 / 1M
Blended Price
Weighted 7:2:1 cache:input:output per 1M
$7.70 / 1M$1.47 / 1M
Context Window
Maximum input + output tokens
272K tokens~408 A4 pages of text1M tokens~1,500 A4 pages of text
Max Output Tokens
Per single request
128K128K
Throughput Speed
Tokens generated per second
100 tok/s116 tok/s
SWE-bench Verified
Real-world software engineering
82.4%82.1%
GPQA Diamond
Graduate-level reasoning
80.9%80.6%
Cached Input Price
Prompt caching discount per 1M tokens
$1.00 / 1M$0.10 / 1M

Wer gewinnt in welcher Disziplin?

At-a-glance decision framework
Coding
GPT-6 Astra
+0.3% SWE-bench lead
Cost
GPT-6 Sol
5.1x cheaper monthly runtime
Speed
GPT-6 Sol
+16% faster generation
Context
GPT-6 Sol
1M tokens window

Geprüfte Benchmark-Ergebnisse im Vergleich

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

GPT-6 AstraGPT-6 Sol
SWE-bench Verified (Autonomous Coding)

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

82.4%vs82.1%
GPQA Diamond (Doctorate-Level Science & Math)

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

80.9%vs80.6%
MMLU-Pro (Multi-task Language Understanding)

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

89.9%vs89.8%
LMSYS Chatbot Arena Elo

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

1520ptsvs1516pts
Humanity's Last Exam (Frontier Expert Knowledge)

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

18.2%vs18%
Terminal-Bench (Agentic Coding & Terminal Use)

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

63.8%vs63.2%
SciCode (Scientific Computing)

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

54.9%vs54.5%
LiveCodeBench (Competitive Coding)

Contamination-free competitive programming problems collected continuously over time.

79.8%vs79.5%
AIME (Advanced Math Competition)

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

93.6%vs93.4%
Long-Context Reasoning

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

91.2%vs90.8%
Generation Speed (Throughput)

Tokens emitted per second during active generation streaming.

100 tok/s vs116 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-6 Astra0.95s
GPT-6 Sol1.16s
Est. End-to-End Response (500 tokens)TTFT + generation time
GPT-6 Astra5.95s
GPT-6 Sol5.47s

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-6 Astra Monthly API Bill
$61.50 / month
$10/1M in · $50/1M out
GPT-6 Sol Monthly API Bill
$12.15 / month
$2/1M in · $10/1M out
GPT-6 Sol saves approximately $49.35 / month (80%) under this workload.5.1x Savings

GPT-6 Astra · Strengths & Key Advantages

  • Fortschrittliche Omni-Adaptive Autoregressive with Dynamic CoT-Architektur von OpenAI mit 1M Token Kontextfenster
  • Starkes Preis-Leistungs-Verhältnis ($10.0/1M Input, $50.0/1M Output) bei hoher Durchsatzrate
  • Hohe Präzision bei Code-Generierung, logischem Schließen und mehrsprachigen Benchmarks
Considerations & Trade-offs
  • Bei sehr großen Kontextmengen ist eine sorgfältige Token-Budgetierung ratsam
  • Spezialisierte Fachaufgaben profitieren von gezieltem Prompt-Engineering

GPT-6 Sol · Strengths & Key Advantages

  • Fortschrittliche Cost-efficient frontier unified reasoning model-Architektur von OpenAI mit 1M Token Kontextfenster
  • Starkes Preis-Leistungs-Verhältnis ($2.0/1M Input, $10.0/1M Output) bei hoher Durchsatzrate
  • Hohe Präzision bei Code-Generierung, logischem Schließen und mehrsprachigen Benchmarks
Considerations & Trade-offs
  • Bei sehr großen Kontextmengen ist eine sorgfältige Token-Budgetierung ratsam
  • Spezialisierte Fachaufgaben profitieren von gezieltem Prompt-Engineering

Token Use & Task Economics

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

MetricGPT-6 AstraGPT-6 Sol
Cost per Task
Estimated USD to finish one task
$2.15$2.00
Output Tokens / Task
Tokens generated per task
58K62K
Reasoning Tokens / Task
Thinking tokens burned per task
32K36K

Technische Spezifikationen

Architecture, release timeline, capabilities, and modalities.

FeatureGPT-6 AstraGPT-6 Sol
Official API Model ID (SDK)gpt-6-astragpt-6-sol
API ProtocolOpenAI Responses API & Chat Completions v1OpenAI Responses API & Chat Completions v1
Release Date2026-092026-09
Knowledge CutoffJune 2026April 2026
ArchitectureOmni-Adaptive Autoregressive with Dynamic CoTCost-efficient frontier unified reasoning model
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) · 4,000,000 – 10,000,000 TPM
Long-Context Tier (>128K/200K)Flat rate ($10/1M in) across full 272K windowFlat rate ($2/1M in) across full 1000K window
Prompt Cache Policy & TTLAutomatic prefix caching at $1/1M (no extra cache-write fee)Automatic prefix caching at $0.1/1M (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) · Audio (~25–32 tokens/sec)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 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, vision, audiotext, vision
Output Modalitiestext, audiotext

GPT-6 Astra vs GPT-6 Sol: Schnelle Antworten (FAQ)

Which is more intelligent, GPT-6 Astra or GPT-6 Sol?

GPT-6 Astra is more intelligent. It scores 96 compared with 93 on the composite Intelligence Index.

Which model is faster?

GPT-6 Sol is faster, generating 116 tokens per second compared with 100 tokens per second.

Which model is cheaper to run?

GPT-6 Sol is cheaper at $1.47 per 1M tokens blended, compared with $7.70 (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 1.16s.

Which model has a larger context window?

GPT-6 Sol has a larger context window, supporting 1M tokens compared with 272K tokens.

Fazit

Choose GPT-6 Astra for unternehmensautomatisierung, software-engineering, autonome ki-agenten und openai-produktionssysteme, or choose GPT-6 Sol for unternehmensautomatisierung, software-engineering, autonome ki-agenten und openai-produktionssysteme.

Häufig gestellte Fragen (FAQ)

Which is cheaper: GPT-6 Astra or GPT-6 Sol?+

GPT-6 Astra costs $10/1M input and $50/1M output tokens, while GPT-6 Sol costs $2/1M input and $10/1M output tokens.

Which model has a larger context window: GPT-6 Astra or GPT-6 Sol?+

GPT-6 Astra supports 272K tokens whereas GPT-6 Sol supports 1M tokens.

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: OpenAI & OpenAI Official Documentation