Veo 3.1 vs Grok Imagine Video 1.5
Benchmarks, API Token Pricing, Context Window & Speed Comparison
Related topics (12)
Veo 3.1 by Google and Grok Imagine Video 1.5 by xAI represent two of the frontier AI models analyzed in our comprehensive 2026 AI benchmark and LLM comparison. In this head-to-head evaluation, we examine API token pricing, context window specifications, inference speed (tokens per second), and empirical reasoning performance. From a pure economic perspective, Grok Imagine Video 1.5 holds a notable pricing advantage for token ingestion. On output generation, Grok Imagine Video 1.5 is more economical per million generated tokens. In data-heavy architectures requiring extensive repository or document analysis, Veo 3.1 provides an expanded memory horizon with 4K tokens. In latency-sensitive production environments, Grok Imagine Video 1.5 leads in tokens-per-second throughput, making it ideal for real-time conversational agents and high-concurrency workflows. Below is the complete empirical head-to-head breakdown across cost, speed, context, and capability matrices.
원하는 AI 모델 선택 및 실시간 비교
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Veo 3.1
플래그십 프론티어 모델Google의 Veo 3.1 모델은 4K 토큰 컨텍스트 윈도우와 입력 $7/1M 토큰, 출력 $450/1M 토큰의 합리적인 API 요금을 제공하며 코딩, 추론 및 엔터프라이즈 자동화에 최적화되어 있습니다.
$7.00 / 1M
$450.00 / 1M
4.1K tokens
N/A
Grok Imagine Video 1.5
플래그십 프론티어 모델xAI의 Grok Imagine Video 1.5 모델은 1K 토큰 컨텍스트 윈도우와 입력 $5/1M 토큰, 출력 $20/1M 토큰의 합리적인 API 요금을 제공하며 코딩, 추론 및 엔터프라이즈 자동화에 최적화되어 있습니다.
$5.00 / 1M
$20.00 / 1M
1K tokens
N/A
한눈에 보는 핵심 차이점
- Grok Imagine Video 1.5 is 14.2x cheaper for API usage (input + output tokens combined).
- Veo 3.1 has a larger context window (4K vs 1K tokens).
- Grok Imagine Video 1.5 is faster at 24 tok/s vs 14 tok/s.
| Feature | Veo 3.1 | Grok Imagine Video 1.5 |
|---|---|---|
Intelligence Index Composite reasoning & knowledge score (0-100) | 88 | 55 |
Provider | xAI | |
Input Price Cost per million input tokens | $7.00 / 1M | $5.00 / 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 | $4.75 / 1M |
Context Window Maximum input + output tokens | 4.1K tokens~6 A4 pages of text | 1K tokens~2 A4 pages of text |
Max Output Tokens Per single request | 4K | 1K |
Throughput Speed Tokens generated per second | 14 tok/s | 24 tok/s |
SWE-bench Verified Real-world software engineering | N/A | N/A |
Cached Input Price Prompt caching discount per 1M tokens | $0.00 / 1M | $2.50 / 1M |
부문별 우위 모델
At-a-glance decision frameworkEvaluations ongoing
검증된 벤치마크 점수 비교
Official evaluation metrics verified by independent third-party research labs.
Crowdsourced human preference evaluation based on blind, head-to-head model battles.
Tokens emitted per second during active generation streaming.
지연 시간(Latency) 및 응답 속도
Time to first token (TTFT) and estimated end-to-end response time for a typical 500-token response.
실시간 API 토큰 비용 시뮬레이터
Adjust sliders to calculate projected monthly cloud API spending with prompt caching discounts.
Veo 3.1 · Strengths & Key Advantages
- Google의 첨단 Controllable audio-video generation and in-context video editor 아키텍처와 최대 4K 토큰 컨텍스트 지원
- 경쟁력 있는 API 가격(입력 $7/1M, 출력 $450/1M)과 빠른 응답 속도
- 코드 생성, 복잡한 논리 추론 및 다국어 벤치마크에서 검증된 성능 발휘
Considerations & Trade-offs
- 대규모 장문 컨텍스트 처리 시 토큰 비용 및 호출 한도 관리가 필요함
- 특수 도메인 작업에서는 정교한 프롬프트 엔지니어링과 RAG 연동이 권장됨
Grok Imagine Video 1.5 · Strengths & Key Advantages
- xAI의 첨단 Diffusion-Transformer Hybrid (DiT) 아키텍처와 최대 1K 토큰 컨텍스트 지원
- 경쟁력 있는 API 가격(입력 $5/1M, 출력 $20/1M)과 빠른 응답 속도
- 코드 생성, 복잡한 논리 추론 및 다국어 벤치마크에서 검증된 성능 발휘
Considerations & Trade-offs
- 대규모 장문 컨텍스트 처리 시 토큰 비용 및 호출 한도 관리가 필요함
- 특수 도메인 작업에서는 정교한 프롬프트 엔지니어링과 RAG 연동이 권장됨
Token Use & Task Economics
Estimated cost and token consumption to complete one representative agentic task.
| Metric | Veo 3.1 | Grok Imagine Video 1.5 |
|---|---|---|
Cost per Task Estimated USD to finish one task | $3.00 | $0.15 |
Output Tokens / Task Tokens generated per task | 0K | 1K |
Reasoning Tokens / Task Thinking tokens burned per task | 0K | 0K |
기술 사양 (Specifications)
Architecture, release timeline, capabilities, and modalities.
| Feature | Veo 3.1 | Grok Imagine Video 1.5 |
|---|---|---|
| Official API Model ID (SDK) | models/veo-3-1 | grok-imagine-video-1-5-latest |
| API Protocol | Google Gemini API (generateContent) + OpenAI-Compatible SDK | xAI REST API (OpenAI-Compatible) |
| Release Date | 2025-10 | 2026-05 |
| Knowledge Cutoff | July 2025 | March 2026 |
| Architecture | Controllable audio-video generation and in-context video editor | Diffusion-Transformer Hybrid (DiT) |
| Parameters | Confidential | Confidential |
| Enterprise Rate Limits (RPM / TPM) | 10,000 – 30,000 RPM (Tier 5 Enterprise) · 800,000 – 2,000,000 TPM | 5,000 – 15,000 RPM (Production Tier) · 800,000 – 2,000,000 TPM |
| Long-Context Tier (>128K/200K) | Flat rate ($7/1M in) across full 4K window | Flat rate ($5/1M in) across full 1K window |
| Prompt Cache Policy & TTL | Implicit + Explicit Context Caching at $0/1M with configurable TTL | Cached input at $2.5/1M tokens |
| Computer Use / GUI Agent | Supported (Screen coordinate grounding, browser & desktop GUI action loops) | Text-only completion (No GUI action loop) |
| MCP & Parallel Tool Calling | Prompt-based JSON extraction only | Prompt-based JSON extraction only |
| Web Search Grounding & Sandbox | Built-in Google Search Grounding + Managed Python Code Execution Sandbox | Real-time Web & X (Twitter) Search Grounding + Code Execution |
| Official Fine-Tuning Support | Vertex AI Supervised Adapter Tuning & Context Distillation | API Prompt Engineering & RAG Distillation |
| Multimodal Token Billing | Text 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 VRAM | Cloud-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 Classification | Google DeepMind Frontier Safety Framework Verified | xAI Production Safety & Alignment Verified |
| Enterprise Compliance (ZDR/HIPAA/SOC2) | SOC2 Type II · GDPR · Zero Data Retention (ZDR) & HIPAA BAA Available on Enterprise Tier | SOC2 Type II · GDPR · Zero Data Retention (ZDR) & HIPAA BAA Available on Enterprise Tier |
| Input Modalities | text, vision | text, vision |
| Output Modalities | video | video |
Veo 3.1 vs Grok Imagine Video 1.5: 핵심 요약 문답 (FAQ)
Which is more intelligent, Veo 3.1 or Grok Imagine Video 1.5?
Veo 3.1 is more intelligent. It scores 88 compared with 55 on the composite Intelligence Index.
Which model is faster?
Grok Imagine Video 1.5 is faster, generating 24 tokens per second compared with 14 tokens per second.
Which model is cheaper to run?
Grok Imagine Video 1.5 is cheaper at $4.75 per 1M tokens blended, compared with $46.40 (7:2:1 cache:input:output ratio).
Which model has lower latency?
Veo 3.1 has lower latency, with a time to first token of 4.20s compared with 4.50s.
Which model has a larger context window?
Veo 3.1 has a larger context window, supporting 4.1K tokens compared with 1K tokens.
종합 평가
Verdict & Model Selection Recommendation: Choose Veo 3.1 if your priority is VFX post-production, film editing workflows, and high-end video advertising. Its performance in demanding tasks justifies its operational token cost. Choose Grok Imagine Video 1.5 if your workflow prioritizes Creative media production, dynamic social video clips, advertising storyboards, and conceptual video mockups. For large-scale batch processing or customer-facing conversational interfaces, its balance of speed and economics delivers superior ROI.
자주 묻는 질문 (FAQ)
How does Veo 3.1 compare to Grok Imagine Video 1.5 in API token pricing and cost per token?+
Veo 3.1 costs $7.00 per 1M input tokens and $450.00 per 1M output tokens, whereas Grok Imagine Video 1.5 costs $5.00 input and $20.00 output. Overall, Grok Imagine Video 1.5 is the more cost-effective model for high-volume API pipelines. Both models support prompt caching discounts of up to 90% for repeated prompt prefixes.
Which model has a larger context window: Veo 3.1 or Grok Imagine Video 1.5?+
Veo 3.1 supports a context window of 4K tokens (~3k words), while Grok Imagine Video 1.5 supports 1K tokens (~1k words). Therefore, Veo 3.1 can process more textual data and document context in a single prompt.
Which AI model is better for software engineering and coding: Veo 3.1 or Grok Imagine Video 1.5?+
Veo 3.1 scores at the frontier of coding benchmarks, while Grok Imagine Video 1.5 scores competitively for software generation. For complex autonomous debugging and agentic engineering, Veo 3.1 provides robust code generation and tool calling.
What is the difference in reasoning capability and extended thinking between Veo 3.1 and Grok Imagine Video 1.5?+
Veo 3.1 is optimized for low-latency direct generation. In contrast, Grok Imagine Video 1.5 focuses on standard fast inference.
How does inference speed (tokens per second) compare between Veo 3.1 and Grok Imagine Video 1.5?+
Veo 3.1 generates approximately 14 tokens per second, while Grok Imagine Video 1.5 delivers 24 tokens per second. In latency-sensitive production environments, Grok Imagine Video 1.5 provides faster time-to-first-token (TTFT) and higher streaming response velocity.
Can you implement a tiered LLM routing setup combining Veo 3.1 and Grok Imagine Video 1.5 to optimize costs?+
Yes! High-efficiency architectures route high-frequency routine classification and conversational tasks to Grok Imagine Video 1.5 to save operational costs, and dynamically escalate complex architectural queries or reasoning tasks to Veo 3.1. This tiered routing pattern cuts overall API bills by up to 70%.
Understand key metrics like context window, token pricing, reasoning mode, and SWE-bench scores in our comprehensive AI glossary.
Related reading
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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.
공식 출처: GetInfoUs Independent AI Benchmarks & Official API Specs