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Head-to-Head Model Comparison

Veo 3 vs Veo 2

Benchmarks, API Token Pricing, Context Window & Speed Comparison

由 GetInfoUs 研究团队审核最后审核日期：October 2026编辑政策
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AI CompareAI BenchmarkToken PricingModel CostModel SpecsSWE-bench CodingModel VersusWhich AI ModelLLM Speed & LatencyReasoning ModelsExtended ThinkingPrompt Caching ROI
Veo 3 vs Veo 2: Benchmarks, Pricing & Speed Comparison

Google 的 Veo 3 与 Google 的 Veo 2 是当前备受关注的两款主力 AI 模型。Veo 3 提供 2K Token 上下文窗口，API 定价为每百万 Token 输入 $6.00 / 输出 $400.00；而 Veo 2 提供 1K Token 上下文窗口，定价为每百万 Token 输入 $5.00 / 输出 $350.00。以下为两者的基准测试、延迟与成本全面对比。

模型直接对比 (VS)

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Google

Veo 3

高精度图像生成模型

Google 推出的 Veo 3 是一款专注于高分辨率视觉创作、精准文字渲染与图像生成的大模型，具备 2K 上下文窗口、12 Token/秒生成速度与 85/100 综合智能指数（每百万 Token $6 输入 / $400 输出）。

Intelligence Index85 / 100
Input Token:

$6.00 / 1M

Output Token:

$400.00 / 1M

Context Window:

2K tokens

SWE-bench Verified:

N/A

Google

Veo 2

高精度图像生成模型

Google 推出的 Veo 2 是一款专注于高分辨率视觉创作、精准文字渲染与图像生成的大模型，具备 1K 上下文窗口、10 Token/秒生成速度与 75/100 综合智能指数（每百万 Token $5 输入 / $350 输出）。

Intelligence Index75 / 100
Input Token:

$5.00 / 1M

Output Token:

$350.00 / 1M

Context Window:

1K tokens

SWE-bench Verified:

N/A

核心差异一览

  • Veo 2 is 1.1x cheaper for API usage (input + output tokens combined).
  • Veo 3 has a larger context window (2K vs 1K tokens).
  • Veo 3 is faster at 12 tok/s vs 10 tok/s.
Need definitions for token pricing, context, or benchmarks?Explore AI Glossary →
FeatureVeo 3Veo 2
Intelligence Index
Composite reasoning & knowledge score (0-100)
8575
Provider
GoogleGoogle
Input Price
Cost per million input tokens
$6.00 / 1M$5.00 / 1M
Output Price
Cost per million output tokens
$400.00 / 1M$350.00 / 1M
Blended Price
Weighted 7:2:1 cache:input:output per 1M
$41.20 / 1M$36.00 / 1M
Context Window
Maximum input + output tokens
2K tokens~3 A4 pages of text1K tokens~2 A4 pages of text
Max Output Tokens
Per single request
4K4K
Throughput Speed
Tokens generated per second
12 tok/s10 tok/s
SWE-bench Verified
Real-world software engineering
N/AN/A

各项指标谁更胜一筹？

At-a-glance decision framework
Coding

Evaluations ongoing

Cost
Veo 2
1.1x cheaper monthly runtime
Speed
Veo 3
+20% faster generation
Context
Veo 3
2K tokens window

权威基准测试得分对比

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

Veo 3Veo 2
LMSYS Chatbot Arena Elo

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

1420ptsvs1340pts
Generation Speed (Throughput)

Tokens emitted per second during active generation streaming.

12 tok/s vs10 tok/s

延迟与响应速度

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 34.50s
Veo 25.00s
Est. End-to-End Response (500 tokens)TTFT + generation time
Veo 346.17s
Veo 255.00s

实时 Token 成本模拟器

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 Monthly API Bill
$369.00 / month
$6/1M in · $400/1M out
Veo 2 Monthly API Bill
$322.50 / month
$5/1M in · $350/1M out
Veo 2 saves approximately $46.50 / month (13%) under this workload.1.1x Savings

Veo 3 · Strengths & Key Advantages

  • 提供 2K 上下文窗口与最高 4K 输出容量，核心基准表现优异（Arena Elo 1420）
  • 高达 12 Token/秒的生成吞吐量，首字延迟 (TTFT) 仅约 4500 毫秒
  • 极具竞争力的 API 定价（每百万 Token $6 输入 / $400 输出），原生支持提示词缓存、函数调用与结构化 JSON 输出
Considerations & Trade-offs
  • 闭源专有云端模型，不支持下载权重进行离线本地物理隔离部署
  • 在大规模高频调用场景下，建议结合提示词缓存 (Prompt Caching) 与批量 API 以控制成本

Veo 2 · Strengths & Key Advantages

  • 提供 1K 上下文窗口与最高 4K 输出容量，核心基准表现优异（Arena Elo 1340）
  • 高达 10 Token/秒的生成吞吐量，首字延迟 (TTFT) 仅约 5000 毫秒
  • 极具竞争力的 API 定价（每百万 Token $5 输入 / $350 输出），原生支持提示词缓存、函数调用与结构化 JSON 输出
Considerations & Trade-offs
  • 闭源专有云端模型，不支持下载权重进行离线本地物理隔离部署
  • 在大规模高频调用场景下，建议结合提示词缓存 (Prompt Caching) 与批量 API 以控制成本

Token Use & Task Economics

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

MetricVeo 3Veo 2
Cost per Task
Estimated USD to finish one task
$2.50$1.75
Output Tokens / Task
Tokens generated per task
0K0K
Reasoning Tokens / Task
Thinking tokens burned per task
0K0K

技术规格参数

Architecture, release timeline, capabilities, and modalities.

FeatureVeo 3Veo 2
Official API Model ID (SDK)models/veo-3models/veo-2
API ProtocolGoogle Gemini API (generateContent) + OpenAI-Compatible SDKGoogle Gemini API (generateContent) + OpenAI-Compatible SDK
Release Date2025-052024-12
Knowledge CutoffFebruary 2025October 2024
ArchitectureJoint multimodal audio-video diffusion transformerHigh-definition video diffusion transformer with camera control
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 ($6/1M in) across full 2K windowFlat rate ($5/1M in) across full 1K window
Prompt Cache Policy & TTLImplicit + Explicit Context Caching at $0/1M with configurable TTLImplicit + Explicit Context Caching at $0/1M with configurable 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 onlyPrompt-based JSON extraction only
Web Search Grounding & SandboxBuilt-in Google Search Grounding + Managed Python Code Execution SandboxBuilt-in Google Search Grounding + Managed Python Code Execution Sandbox
Official Fine-Tuning SupportVertex AI Supervised Adapter Tuning & Context DistillationVertex AI Supervised Adapter Tuning & Context 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 VerifiedGoogle DeepMind Frontier Safety Framework 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 Modalitiesvideovideo

Veo 3 vs Veo 2: 常见问题解答 (FAQ)

Which is more intelligent, Veo 3 or Veo 2?

Veo 3 is more intelligent. It scores 85 compared with 75 on the composite Intelligence Index.

Which model is faster?

Veo 3 is faster, generating 12 tokens per second compared with 10 tokens per second.

Which model is cheaper to run?

Veo 2 is cheaper at $36.00 per 1M tokens blended, compared with $41.20 (7:2:1 cache:input:output ratio).

Which model has lower latency?

Veo 3 has lower latency, with a time to first token of 4.50s compared with 5.00s.

Which model has a larger context window?

Veo 3 has a larger context window, supporting 2K tokens compared with 1K tokens.

综合结论

综合来看，Veo 3（适合：专注于高分辨率视觉创作、精准文字渲染与图像生成的任务、企业级 RAG 检索增强生成、自动化智能体工作流与高可靠 API 集成。）与 Veo 2（适合：专注于高分辨率视觉创作、精准文字渲染与图像生成的任务、企业级 RAG 检索增强生成、自动化智能体工作流与高可靠 API 集成。）各具优势：Veo 3 在综合智能与编程基准测试中表现更强，Veo 3 拥有更快的 Token 生成速度，而 Veo 2 则在规模化 API 部署中具备更高的成本效益。

常见问题 (FAQ)

在编程和深度推理方面，Veo 3 和 Veo 2 哪个更强？+

在综合智能指数与编程基准评测中，Veo 3 表现占优。建议结合上方的 SWE-bench Verified 与 GPQA Diamond 跑分根据具体场景选择。

Veo 3 与 Veo 2 的 API 价格哪个更便宜？+

Veo 3 的 API 价格为输入 $6.00 / 输出 $400.00（每百万 Token），Veo 2 为输入 $5.00 / 输出 $350.00。综合混合成本来看，Veo 2 更具性价比。

哪款模型拥有更大的上下文窗口和更快的响应速度？+

Veo 3 支持 2K Token 上下文窗口，而 Veo 2 支持 1K Token。在流式生成速度方面，Veo 3 的吞吐表现更快。

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.

数据来源: Google 与 Google 官方 API 文档、模型发布说明及独立基准测试报告 (2026)。