Head-to-Head Model Comparison

Claude Opus 4.6 vs GPT-6 Astra

Benchmarks, API Token Pricing, Context Window & Speed Comparison

GetInfoUs अनुसंधान दल द्वारा समीक्षितअंतिम समीक्षा: October 2026संपादकीय नीति
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Compare Claude Opus 4.6 by Anthropic against GPT-6 Astra by OpenAI across real-world coding, reasoning, token economics, and latency.

आमने-सामने मॉडल तुलना (VS)

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Live comparison: no in-depth editorial review has been published for this pair yet.

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Anthropic

Claude Opus 4.6

डीप रीजनिंग मॉडल

Anthropic द्वारा विकसित Claude Opus 4.6 एक उन्नत AI मॉडल है, जिसमें 1M टोकन का कॉन्टेक्स्ट विंडो और $5/1M इनपुट तथा $25/1M आउटपुट मूल्य निर्धारण है। यह कोडिंग, विश्लेषण और एंटरप्राइज वर्कफ़्लो के लिए उपयुक्त है।

Intelligence Index65 / 100
Input Token:

$5.00 / 1M

Output Token:

$25.00 / 1M

Context Window:

1M tokens

SWE-bench Verified:

78.4%

OpenAI

GPT-6 Astra

डीप रीजनिंग मॉडल

OpenAI द्वारा विकसित GPT-6 Astra एक उन्नत AI मॉडल है, जिसमें 1M टोकन का कॉन्टेक्स्ट विंडो और $10.0/1M इनपुट तथा $50.0/1M आउटपुट मूल्य निर्धारण है। यह कोडिंग, विश्लेषण और एंटरप्राइज वर्कफ़्लो के लिए उपयुक्त है।

Intelligence Index96 / 100
Input Token:

$10.00 / 1M

Output Token:

$50.00 / 1M

Context Window:

272K tokens

SWE-bench Verified:

82.4%

एक नज़र में मुख्य अंतर

  • Claude Opus 4.6 is 2.0x cheaper for API usage (input + output tokens combined).
  • Claude Opus 4.6 has a larger context window (1M vs 272K tokens).
  • GPT-6 Astra is faster at 100 tok/s vs 55 tok/s.
  • GPT-6 Astra leads on SWE-bench coding (82.4% vs 78.4%).
Need definitions for token pricing, context, or benchmarks?Explore AI Glossary →
FeatureClaude Opus 4.6GPT-6 Astra
Intelligence Index
Composite reasoning & knowledge score (0-100)
6596
Provider
AnthropicOpenAI
Input Price
Cost per million input tokens
$5.00 / 1M$10.00 / 1M
Output Price
Cost per million output tokens
$25.00 / 1M$50.00 / 1M
Blended Price
Weighted 7:2:1 cache:input:output per 1M
$3.85 / 1M$7.70 / 1M
Context Window
Maximum input + output tokens
1M tokens~1,500 A4 pages of text272K tokens~408 A4 pages of text
Max Output Tokens
Per single request
128K128K
Throughput Speed
Tokens generated per second
55 tok/s100 tok/s
SWE-bench Verified
Real-world software engineering
78.4%82.4%
GPQA Diamond
Graduate-level reasoning
76.5%80.9%
Cached Input Price
Prompt caching discount per 1M tokens
$0.50 / 1M$1.00 / 1M

किस क्षेत्र में कौन आगे है?

At-a-glance decision framework
Coding
GPT-6 Astra
+4.0% SWE-bench lead
Cost
Claude Opus 4.6
2.0x cheaper monthly runtime
Speed
GPT-6 Astra
+82% faster generation
Context
Claude Opus 4.6
1M tokens window

सत्यापित बेंचमार्क स्कोर तुलना

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

Claude Opus 4.6GPT-6 Astra
SWE-bench Verified (Autonomous Coding)

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

78.4%vs82.4%
GPQA Diamond (Doctorate-Level Science & Math)

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

76.5%vs80.9%
MMLU-Pro (Multi-task Language Understanding)

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

88.2%vs89.9%
LMSYS Chatbot Arena Elo

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

1395ptsvs1520pts
Humanity's Last Exam (Frontier Expert Knowledge)

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

N/Avs18.2%
Terminal-Bench (Agentic Coding & Terminal Use)

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

51.4%vs63.8%
SciCode (Scientific Computing)

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

N/Avs54.9%
LiveCodeBench (Competitive Coding)

Contamination-free competitive programming problems collected continuously over time.

N/Avs79.8%
AIME (Advanced Math Competition)

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

N/Avs93.6%
Long-Context Reasoning

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

N/Avs91.2%
Generation Speed (Throughput)

Tokens emitted per second during active generation streaming.

55 tok/s vs100 tok/s

लेटेंसी और रिस्पॉन्स समय

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 Opus 4.61.90s
GPT-6 Astra0.95s
Est. End-to-End Response (500 tokens)TTFT + generation time
Claude Opus 4.610.99s
GPT-6 Astra5.95s

रियल-टाइम टोकन लागत सिम्युलेटर

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 Opus 4.6 Monthly API Bill
$30.75 / month
$5/1M in · $25/1M out
GPT-6 Astra Monthly API Bill
$61.50 / month
$10/1M in · $50/1M out
Claude Opus 4.6 saves approximately $30.75 / month (50%) under this workload.2.0x Savings

Claude Opus 4.6 · Strengths & Key Advantages

  • Anthropic की उन्नत Megacontext Frontier Reasoning Transformer आर्किटेक्चर और 1M कॉन्टेक्स्ट विंडो क्षमता
  • किफायती और पारदर्शी API मूल्य ($5/1M इनपुट, $25/1M आउटपुट) तेज़ रिस्पॉन्स के साथ
  • जटिल कोडिंग, तार्किक विश्लेषण और बहुभाषी कार्यों में उच्च सटीकता
Considerations & Trade-offs
  • बड़े पैमाने पर लंबे कॉन्टेक्स्ट प्रॉम्प्ट्स के लिए टोकन बजट प्रबंधन आवश्यक है
  • विशिष्ट डोमेन कार्यों में सर्वोत्तम परिणाम के लिए सटीक प्रॉम्प्ट इंजीनियरिंग की आवश्यकता होती है

GPT-6 Astra · Strengths & Key Advantages

  • OpenAI की उन्नत Omni-Adaptive Autoregressive with Dynamic CoT आर्किटेक्चर और 1M कॉन्टेक्स्ट विंडो क्षमता
  • किफायती और पारदर्शी API मूल्य ($10.0/1M इनपुट, $50.0/1M आउटपुट) तेज़ रिस्पॉन्स के साथ
  • जटिल कोडिंग, तार्किक विश्लेषण और बहुभाषी कार्यों में उच्च सटीकता
Considerations & Trade-offs
  • बड़े पैमाने पर लंबे कॉन्टेक्स्ट प्रॉम्प्ट्स के लिए टोकन बजट प्रबंधन आवश्यक है
  • विशिष्ट डोमेन कार्यों में सर्वोत्तम परिणाम के लिए सटीक प्रॉम्प्ट इंजीनियरिंग की आवश्यकता होती है

Token Use & Task Economics

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

MetricClaude Opus 4.6GPT-6 Astra
Cost per Task
Estimated USD to finish one task
$5.49$2.15
Output Tokens / Task
Tokens generated per task
72K58K
Reasoning Tokens / Task
Thinking tokens burned per task
37K32K

तकनीकी विशिष्टताएँ (Specs)

Architecture, release timeline, capabilities, and modalities.

FeatureClaude Opus 4.6GPT-6 Astra
Official API Model ID (SDK)claude-opus-4-6-20260201gpt-6-astra
API ProtocolAnthropic Messages API + AWS Bedrock + Vertex AIOpenAI Responses API & Chat Completions v1
Release Date2026-022026-09
Knowledge CutoffDecember 2025June 2026
ArchitectureMegacontext Frontier Reasoning TransformerOmni-Adaptive Autoregressive with Dynamic CoT
ParametersConfidentialConfidential
Enterprise Rate Limits (RPM / TPM)4,000 – 10,000 RPM (Tier 4 + Priority Tier) · 4,000,000 – 10,000,000 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 tokensFlat rate ($10/1M in) across full 272K window
Prompt Cache Policy & TTL$0.5/1M cached read (90% off); 5-min default & 1-hour extended TTLAutomatic 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 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) · 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 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, audio
Output Modalitiestexttext, audio

Claude Opus 4.6 vs GPT-6 Astra: त्वरित प्रश्नोत्तर (FAQ)

Which is more intelligent, Claude Opus 4.6 or GPT-6 Astra?

GPT-6 Astra is more intelligent. It scores 96 compared with 65 on the composite Intelligence Index.

Which model is faster?

GPT-6 Astra is faster, generating 100 tokens per second compared with 55 tokens per second.

Which model is cheaper to run?

Claude Opus 4.6 is cheaper at $3.85 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 1.90s.

Which model has a larger context window?

Claude Opus 4.6 has a larger context window, supporting 1M tokens compared with 272K tokens.

निष्कर्ष

Choose Claude Opus 4.6 for एंटरप्राइज ऑटोमेशन, सॉफ्टवेयर डेवलपमेंट, ai एजेंट्स और anthropic आधारित प्रोडक्शन सिस्टम, or choose GPT-6 Astra for एंटरप्राइज ऑटोमेशन, सॉफ्टवेयर डेवलपमेंट, ai एजेंट्स और openai आधारित प्रोडक्शन सिस्टम.

अक्सर पूछे जाने वाले प्रश्न (FAQ)

Which is cheaper: Claude Opus 4.6 or GPT-6 Astra?+

Claude Opus 4.6 costs $5/1M input and $25/1M output tokens, while GPT-6 Astra costs $10/1M input and $50/1M output tokens.

Which model has a larger context window: Claude Opus 4.6 or GPT-6 Astra?+

Claude Opus 4.6 supports 1M tokens whereas GPT-6 Astra supports 272K 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.

स्रोत: Anthropic & OpenAI Official Documentation