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Head-to-Head Model Comparison

Gemini Omni Flash vs Veo 3.1

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
Gemini Omni Flash vs Veo 3.1: Benchmarks, Pricing & Speed Comparison

Google 的 Gemini Omni Flash 与 Google 的 Veo 3.1 是当前备受关注的两款主力 AI 模型。Gemini Omni Flash 提供 1.05M Token 上下文窗口，API 定价为每百万 Token 输入 $2.00 / 输出 $15.00；而 Veo 3.1 提供 4.1K Token 上下文窗口，定价为每百万 Token 输入 $7.00 / 输出 $450.00。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

Gemini Omni Flash

AI 视频生成大模型

Google 推出的 Gemini Omni Flash 是一款面向电影级视频生成、物理运动模拟与多镜头叙事的大模型，具备 1.0M 上下文窗口、75 Token/秒生成速度与 86/100 综合智能指数（每百万 Token $2 输入 / $15 输出）。

Intelligence Index86 / 100
Input Token:

$2.00 / 1M

Output Token:

$15.00 / 1M

Context Window:

1.05M tokens

SWE-bench Verified:

N/A

Google

Veo 3.1

AI 视频生成大模型

Google 推出的 Veo 3.1 是一款面向电影级视频生成、物理运动模拟与多镜头叙事的大模型，具备 4K 上下文窗口、14 Token/秒生成速度与 88/100 综合智能指数（每百万 Token $7 输入 / $450 输出）。

Intelligence Index88 / 100
Input Token:

$7.00 / 1M

Output Token:

$450.00 / 1M

Context Window:

4.1K tokens

SWE-bench Verified:

N/A

核心差异一览

  • Gemini Omni Flash is 24.1x cheaper for API usage (input + output tokens combined).
  • Gemini Omni Flash has a larger context window (1M vs 4K tokens).
  • Gemini Omni Flash is faster at 75 tok/s vs 14 tok/s.
Need definitions for token pricing, context, or benchmarks?Explore AI Glossary →
FeatureGemini Omni FlashVeo 3.1
Intelligence Index
Composite reasoning & knowledge score (0-100)
8688
Provider
GoogleGoogle
Input Price
Cost per million input tokens
$2.00 / 1M$7.00 / 1M
Output Price
Cost per million output tokens
$15.00 / 1M$450.00 / 1M
Blended Price
Weighted 7:2:1 cache:input:output per 1M
$2.25 / 1M$46.40 / 1M
Context Window
Maximum input + output tokens
1.05M tokens~1,573 A4 pages of text4.1K tokens~6 A4 pages of text
Max Output Tokens
Per single request
33K4K
Throughput Speed
Tokens generated per second
75 tok/s14 tok/s
SWE-bench Verified
Real-world software engineering
N/AN/A
Cached Input Price
Prompt caching discount per 1M tokens
$0.50 / 1M$0.00 / 1M

各项指标谁更胜一筹？

At-a-glance decision framework
Coding

Evaluations ongoing

Cost
Gemini Omni Flash
24.1x cheaper monthly runtime
Speed
Gemini Omni Flash
+436% faster generation
Context
Gemini Omni Flash
1.05M tokens window

权威基准测试得分对比

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

Gemini Omni FlashVeo 3.1
LMSYS Chatbot Arena Elo

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

1440ptsvs1450pts
Generation Speed (Throughput)

Tokens emitted per second during active generation streaming.

75 tok/s vs14 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
Gemini Omni Flash0.80s
Veo 3.14.20s
Est. End-to-End Response (500 tokens)TTFT + generation time
Gemini Omni Flash7.47s
Veo 3.139.91s

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)
Gemini Omni Flash Monthly API Bill
$17.25 / month
$2/1M in · $15/1M out
Veo 3.1 Monthly API Bill
$415.50 / month
$7/1M in · $450/1M out
Gemini Omni Flash saves approximately $398.25 / month (96%) under this workload.24.1x Savings

Gemini Omni Flash · Strengths & Key Advantages

  • 提供 1.0M 上下文窗口与最高 33K 输出容量，核心基准表现优异（Arena Elo 1440）
  • 高达 75 Token/秒的生成吞吐量，首字延迟 (TTFT) 仅约 800 毫秒
  • 极具竞争力的 API 定价（每百万 Token $2 输入 / $15 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 3.1 · Strengths & Key Advantages

  • 提供 4K 上下文窗口与最高 4K 输出容量，核心基准表现优异（Arena Elo 1450）
  • 高达 14 Token/秒的生成吞吐量，首字延迟 (TTFT) 仅约 4200 毫秒
  • 极具竞争力的 API 定价（每百万 Token $7 输入 / $450 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.

MetricGemini Omni FlashVeo 3.1
Cost per Task
Estimated USD to finish one task
$1.50$3.00
Output Tokens / Task
Tokens generated per task
15K0K
Reasoning Tokens / Task
Thinking tokens burned per task
4K0K

技术规格参数

Architecture, release timeline, capabilities, and modalities.

FeatureGemini Omni FlashVeo 3.1
Official API Model ID (SDK)models/gemini-omni-flashmodels/veo-3-1
API ProtocolGoogle Gemini API (generateContent) + OpenAI-Compatible SDKGoogle Gemini API (generateContent) + OpenAI-Compatible SDK
Release Date2026-062025-10
Knowledge CutoffFebruary 2026July 2025
ArchitectureUnified real-time text-to-video and conversational streaming engineControllable audio-video generation and in-context video editor
ParametersConfidentialConfidential
Enterprise Rate Limits (RPM / TPM)10,000 – 30,000 RPM (Tier 5 Enterprise) · 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 ($7/1M in) across full 4K window
Prompt Cache Policy & TTLImplicit + Explicit Context Caching at $0.5/1M 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 CallingNative MCP Client/Server ready · Parallel function calling · 100% Strict JSON SchemaPrompt-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

Gemini Omni Flash vs Veo 3.1: 常见问题解答 (FAQ)

Which is more intelligent, Gemini Omni Flash or Veo 3.1?

Veo 3.1 is more intelligent. It scores 88 compared with 86 on the composite Intelligence Index.

Which model is faster?

Gemini Omni Flash is faster, generating 75 tokens per second compared with 14 tokens per second.

Which model is cheaper to run?

Gemini Omni Flash is cheaper at $2.25 per 1M tokens blended, compared with $46.40 (7:2:1 cache:input:output ratio).

Which model has lower latency?

Gemini Omni Flash has lower latency, with a time to first token of 0.80s compared with 4.20s.

Which model has a larger context window?

Gemini Omni Flash has a larger context window, supporting 1.05M tokens compared with 4.1K tokens.

综合结论

综合来看，Gemini Omni Flash（适合：面向电影级视频生成、物理运动模拟与多镜头叙事的任务、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 3.1（适合：面向电影级视频生成、物理运动模拟与多镜头叙事的任务、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 3.1 在综合智能与编程基准测试中表现更强，Gemini Omni Flash 拥有更快的 Token 生成速度，而 Gemini Omni Flash 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，Gemini Omni Flash 和 Veo 3.1 哪个更强？+

在综合智能指数与编程基准评测中，Veo 3.1 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。

Gemini Omni Flash 与 Veo 3.1 的 API 价格哪个更便宜？+

Gemini Omni Flash 的 API 价格为输入 $2.00 / 输出 $15.00（每百万 Token），Veo 3.1 为输入 $7.00 / 输出 $450.00。综合混合成本来看，Gemini Omni Flash 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？+

Gemini Omni Flash 支持 1.05M Token 上下文窗口，而 Veo 3.1 支持 4.1K Token。在流式生成速度方面，Gemini Omni Flash 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)。