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Head-to-Head Model Comparison

Veo 3.1 vs Claude Opus 5.5

Benchmarks, API Token Pricing, Context Window & Speed Comparison

GetInfoUs अनुसंधान दल द्वारा समीक्षितअंतिम समीक्षा: October 2026संपादकीय नीति
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Compare Veo 3.1 by Google against Claude Opus 5.5 by Anthropic across real-world coding, reasoning, token economics, and latency.

आमने-सामने मॉडल तुलना (VS)

किसी भी मॉडल को बदलें और तुलना करें

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

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Google

Veo 3.1

फ्लैगशिप फ्रंटियर मॉडल

Google द्वारा विकसित Veo 3.1 एक उन्नत AI मॉडल है, जिसमें 4K टोकन का कॉन्टेक्स्ट विंडो और $7/1M इनपुट तथा $450/1M आउटपुट मूल्य निर्धारण है। यह कोडिंग, विश्लेषण और एंटरप्राइज वर्कफ़्लो के लिए उपयुक्त है।

Intelligence Index88 / 100
Input Token:

$7.00 / 1M

Output Token:

$450.00 / 1M

Context Window:

4.1K tokens

SWE-bench Verified:

N/A

Anthropic

Claude Opus 5.5

डीप रीजनिंग मॉडल

Anthropic द्वारा विकसित Claude Opus 5.5 एक उन्नत AI मॉडल है, जिसमें 1M टोकन का कॉन्टेक्स्ट विंडो और $4.0/1M इनपुट तथा $20.0/1M आउटपुट मूल्य निर्धारण है। यह कोडिंग, विश्लेषण और एंटरप्राइज वर्कफ़्लो के लिए उपयुक्त है।

Intelligence Index94 / 100
Input Token:

$4.00 / 1M

Output Token:

$20.00 / 1M

Context Window:

1M tokens

SWE-bench Verified:

84.6%

एक नज़र में मुख्य अंतर

  • Claude Opus 5.5 is 16.9x cheaper for API usage (input + output tokens combined).
  • Claude Opus 5.5 has a larger context window (1M vs 4K tokens).
  • Claude Opus 5.5 is faster at 78 tok/s vs 14 tok/s.
Need definitions for token pricing, context, or benchmarks?Explore AI Glossary →
FeatureVeo 3.1Claude Opus 5.5
Intelligence Index
Composite reasoning & knowledge score (0-100)
8894
Provider
GoogleAnthropic
Input Price
Cost per million input tokens
$7.00 / 1M$4.00 / 1M
Output Price
Cost per million output tokens
$450.00 / 1M$20.00 / 1M
Blended Price
Weighted 7:2:1 cache:input:output per 1M
$46.40 / 1M$3.08 / 1M
Context Window
Maximum input + output tokens
4.1K tokens~6 A4 pages of text1M tokens~1,500 A4 pages of text
Max Output Tokens
Per single request
4K128K
Throughput Speed
Tokens generated per second
14 tok/s78 tok/s
SWE-bench Verified
Real-world software engineering
N/A84.6%
GPQA Diamond
Graduate-level reasoning
N/A82.3%
Cached Input Price
Prompt caching discount per 1M tokens
$0.00 / 1M$0.40 / 1M

किस क्षेत्र में कौन आगे है?

At-a-glance decision framework
Coding

Evaluations ongoing

Cost
Claude Opus 5.5
16.9x cheaper monthly runtime
Speed
Claude Opus 5.5
+457% faster generation
Context
Claude Opus 5.5
1M tokens window

सत्यापित बेंचमार्क स्कोर तुलना

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

Veo 3.1Claude Opus 5.5
SWE-bench Verified (Autonomous Coding)

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

N/Avs84.6%
GPQA Diamond (Doctorate-Level Science & Math)

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

N/Avs82.3%
MMLU-Pro (Multi-task Language Understanding)

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

N/Avs91.5%
LMSYS Chatbot Arena Elo

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

1450ptsvs1507pts
Humanity's Last Exam (Frontier Expert Knowledge)

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

N/Avs19.8%
Terminal-Bench (Agentic Coding & Terminal Use)

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

N/Avs66.4%
SciCode (Scientific Computing)

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

N/Avs58.7%
LiveCodeBench (Competitive Coding)

Contamination-free competitive programming problems collected continuously over time.

N/Avs83.1%
AIME (Advanced Math Competition)

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

N/Avs95.4%
Long-Context Reasoning

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

N/Avs92.6%
Generation Speed (Throughput)

Tokens emitted per second during active generation streaming.

14 tok/s vs78 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
Veo 3.14.20s
Claude Opus 5.51.40s
Est. End-to-End Response (500 tokens)TTFT + generation time
Veo 3.139.91s
Claude Opus 5.57.81s

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)
Veo 3.1 Monthly API Bill
$415.50 / month
$7/1M in · $450/1M out
Claude Opus 5.5 Monthly API Bill
$24.60 / month
$4/1M in · $20/1M out
Claude Opus 5.5 saves approximately $390.90 / month (94%) under this workload.16.9x Savings

Veo 3.1 · Strengths & Key Advantages

  • Google की उन्नत Controllable audio-video generation and in-context video editor आर्किटेक्चर और 4K कॉन्टेक्स्ट विंडो क्षमता
  • किफायती और पारदर्शी API मूल्य ($7/1M इनपुट, $450/1M 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

Claude Opus 5.5 · Strengths & Key Advantages

  • Anthropic की उन्नत Extended Autonomous Hybrid Reasoning Transformer आर्किटेक्चर और 1M कॉन्टेक्स्ट विंडो क्षमता
  • किफायती और पारदर्शी API मूल्य ($4.0/1M इनपुट, $20.0/1M 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.

MetricVeo 3.1Claude Opus 5.5
Cost per Task
Estimated USD to finish one task
$3.00$3.85
Output Tokens / Task
Tokens generated per task
0K68K
Reasoning Tokens / Task
Thinking tokens burned per task
0K42K

तकनीकी विशिष्टताएँ (Specs)

Architecture, release timeline, capabilities, and modalities.

FeatureVeo 3.1Claude Opus 5.5
Official API Model ID (SDK)models/veo-3-1claude-opus-5-5-20260901
API ProtocolGoogle Gemini API (generateContent) + OpenAI-Compatible SDKAnthropic Messages API + AWS Bedrock + Vertex AI
Release Date2025-102026-09
Knowledge CutoffJuly 2025June 2026
ArchitectureControllable audio-video generation and in-context video editorExtended Autonomous Hybrid Reasoning 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) · 4,000,000 – 10,000,000 TPM
Long-Context Tier (>128K/200K)Flat rate ($7/1M in) across full 4K windowStandard rate up to 200K tokens; 2x input/output tier above 200K tokens
Prompt Cache Policy & TTLImplicit + Explicit Context Caching at $0/1M with configurable TTL$0.4/1M 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 CallingPrompt-based JSON extraction onlyNative MCP Client/Server ready · Parallel function calling · 100% Strict JSON Schema
Web Search Grounding & SandboxBuilt-in Google Search Grounding + Managed Python Code Execution SandboxNative Web Search Citations + Code Execution Tool + MCP Connectors
Official Fine-Tuning SupportVertex AI Supervised Adapter Tuning & Context DistillationCustom 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 ClassificationGoogle DeepMind Frontier Safety Framework VerifiedAnthropic 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 Modalitiesvideotext

Veo 3.1 vs Claude Opus 5.5: त्वरित प्रश्नोत्तर (FAQ)

Which is more intelligent, Veo 3.1 or Claude Opus 5.5?

Claude Opus 5.5 is more intelligent. It scores 94 compared with 88 on the composite Intelligence Index.

Which model is faster?

Claude Opus 5.5 is faster, generating 78 tokens per second compared with 14 tokens per second.

Which model is cheaper to run?

Claude Opus 5.5 is cheaper at $3.08 per 1M tokens blended, compared with $46.40 (7:2:1 cache:input:output ratio).

Which model has lower latency?

Claude Opus 5.5 has lower latency, with a time to first token of 1.40s compared with 4.20s.

Which model has a larger context window?

Claude Opus 5.5 has a larger context window, supporting 1M tokens compared with 4.1K tokens.

निष्कर्ष

Choose Veo 3.1 for एंटरप्राइज ऑटोमेशन, सॉफ्टवेयर डेवलपमेंट, ai एजेंट्स और google आधारित प्रोडक्शन सिस्टम, or choose Claude Opus 5.5 for एंटरप्राइज ऑटोमेशन, सॉफ्टवेयर डेवलपमेंट, ai एजेंट्स और anthropic आधारित प्रोडक्शन सिस्टम.

अक्सर पूछे जाने वाले प्रश्न (FAQ)

Which is cheaper: Veo 3.1 or Claude Opus 5.5?+

Veo 3.1 costs $7/1M input and $450/1M output tokens, while Claude Opus 5.5 costs $4/1M input and $20/1M output tokens.

Which model has a larger context window: Veo 3.1 or Claude Opus 5.5?+

Veo 3.1 supports 4K tokens whereas Claude Opus 5.5 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.

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.

स्रोत: Google & Anthropic Official Documentation