GetInfoUs
Head-to-Head Model Comparison

Gemini Omni Flash vs Veo 3.1

Benchmarks, API Token Pricing, Context Window & Speed Comparison

Ditinjau oleh tim riset GetInfoUsPeninjauan terakhir: October 2026Kebijakan editorial
Bagikan
Related topics (12)
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

Gemini Omni Flash dari Google dan Veo 3.1 dari Google adalah dua model AI unggulan. Gemini Omni Flash menawarkan jendela konteks 1.05M token dengan harga $2.00/$15.00 per 1 juta token, sedangkan Veo 3.1 menyediakan konteks 4.1K token seharga $7.00/$450.00 per 1 juta token. Berikut perbandingan lengkap benchmark, latensi, dan biayanya.

Perbandingan Langsung (VS)

Ganti & Bandingkan Model Apa Saja

Select any AI models from our verified benchmark database to generate live side-by-side matrices.

Profile
Profile
Multi-Model Arena Stack:
5-Model Matrix Workbench
Popular Matchups:
Google

Gemini Omni Flash

Model Generasi Video AI

Gemini Omni Flash dari Google adalah model AI yang dirancang untuk pembuatan video sinematik AI dan sintesis gerakan yang mulus, menghadirkan jendela konteks 1.0M, kecepatan 75 token/detik, indeks kecerdasan 86/100, serta tarif $2/$15 per 1

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

Model Generasi Video AI

Veo 3.1 dari Google adalah model AI yang dirancang untuk pembuatan video sinematik AI dan sintesis gerakan yang mulus, menghadirkan jendela konteks 4K, kecepatan 14 token/detik, indeks kecerdasan 88/100, serta tarif $7/$450 per 1M token.

Intelligence Index88 / 100
Input Token:

$7.00 / 1M

Output Token:

$450.00 / 1M

Context Window:

4.1K tokens

SWE-bench Verified:

N/A

Perbedaan Utama Sekilas

  • 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

Siapa Unggul di Mana?

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

Skor Benchmark Terverifikasi

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

Latensi & Waktu Respons

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

Simulator Biaya Token Interaktif

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

  • Jendela konteks 1.0M dengan kapasitas output maksimum hingga 33K token (Arena Elo 1440)
  • Kecepatan generasi tinggi 75 token/detik dengan latensi token pertama (TTFT) hanya 800 ms
  • Skema harga API kompetitif (tarif $2/$15 per 1M token) dengan dukungan cache prompt dan output JSON terstruktur
Considerations & Trade-offs
  • Model cloud proprietari tertutup; bobot model tidak dapat diunduh untuk penggunaan lokal offline
  • Untuk trafik produksi skala besar, disarankan mengaktifkan fitur Prompt Caching dan Batch API guna menghemat biaya

Veo 3.1 · Strengths & Key Advantages

  • Jendela konteks 4K dengan kapasitas output maksimum hingga 4K token (Arena Elo 1450)
  • Kecepatan generasi tinggi 14 token/detik dengan latensi token pertama (TTFT) hanya 4200 ms
  • Skema harga API kompetitif (tarif $7/$450 per 1M token) dengan dukungan cache prompt dan output JSON terstruktur
Considerations & Trade-offs
  • Model cloud proprietari tertutup; bobot model tidak dapat diunduh untuk penggunaan lokal offline
  • Untuk trafik produksi skala besar, disarankan mengaktifkan fitur Prompt Caching dan Batch API guna menghemat biaya

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

Spesifikasi Teknis

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: Jawaban Cepat (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.

Kesimpulan

Baik Gemini Omni Flash (Sangat cocok untuk pembuatan video sinematik AI dan sintesis gerakan yang mulus, sistem RAG perusahaan, dan integrasi API skala produksi.) maupun Veo 3.1 (Sangat cocok untuk pembuatan video sinematik AI dan sintesis gerakan yang mulus, sistem RAG perusahaan, dan integrasi API skala produksi.) sangat tangguh: Veo 3.1 unggul dalam penalaran dan pemrograman, Gemini Omni Flash memberikan kecepatan generasi token lebih tinggi, dan Gemini Omni Flash lebih hemat biaya untuk penggunaan API skala besar.

Pertanyaan Umum (FAQ)

Mana yang lebih baik untuk coding dan penalaran, Gemini Omni Flash atau Veo 3.1?+

Dalam indeks kecerdasan gabungan dan benchmark coding, Veo 3.1 memimpin. Lihat skor SWE-bench dan GPQA di atas untuk detailnya.

Berapa perbandingan harga API Gemini Omni Flash vs Veo 3.1?+

Gemini Omni Flash mengenakan biaya $2.00 / $15.00 per 1M token input/output, sedangkan Veo 3.1 sebesar $7.00 / $450.00. Secara keseluruhan, Gemini Omni Flash lebih hemat biaya.

Model mana yang memiliki jendela konteks lebih besar dan kecepatan lebih tinggi?+

Gemini Omni Flash mendukung konteks 1.05M token dibandingkan 4.1K token pada Veo 3.1, sementara Gemini Omni Flash unggul dalam kecepatan output token per detik.

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.

Sumber resmi: Dokumentasi API resmi Google & Google serta evaluasi benchmark independen (2026).