Grok 4.20 (Non-Reasoning) vs GPT-4.1
Benchmarks, API Token Pricing, Context Window & Speed Comparison
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Grok 4.20 (Non-Reasoning) by xAI and GPT-4.1 by OpenAI 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, GPT-4.1 holds a notable pricing advantage for token ingestion. On output generation, GPT-4.1 is more economical per million generated tokens. In data-heavy architectures requiring extensive repository or document analysis, GPT-4.1 provides an expanded memory horizon with 1,048K tokens. In latency-sensitive production environments, Grok 4.20 (Non-Reasoning) 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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Grok 4.20 (Non-Reasoning)
플래그십 프론티어 모델xAI의 Grok 4.20 (Non-Reasoning) 모델은 1M 토큰 컨텍스트 윈도우와 입력 $1.25/1M 토큰, 출력 $2.5/1M 토큰의 합리적인 API 요금을 제공하며 코딩, 추론 및 엔터프라이즈 자동화에 최적화되어 있습니다.
$3.00 / 1M
$15.00 / 1M
1M tokens
61.5%
GPT-4.1
플래그십 프론티어 모델OpenAI의 GPT-4.1 모델은 1.0M 토큰 컨텍스트 윈도우와 입력 $2/1M 토큰, 출력 $8/1M 토큰의 합리적인 API 요금을 제공하며 코딩, 추론 및 엔터프라이즈 자동화에 최적화되어 있습니다.
$2.00 / 1M
$8.00 / 1M
1.05M tokens
54.6%
한눈에 보는 핵심 차이점
- GPT-4.1 is 1.7x cheaper for API usage (input + output tokens combined).
- GPT-4.1 has a larger context window (1M vs 1M tokens).
- Grok 4.20 (Non-Reasoning) is faster at 135 tok/s vs 110 tok/s.
- Grok 4.20 (Non-Reasoning) leads on SWE-bench coding (61.5% vs 54.6%).
| Feature | Grok 4.20 (Non-Reasoning) | GPT-4.1 |
|---|---|---|
Intelligence Index Composite reasoning & knowledge score (0-100) | 62 | 48 |
Provider | xAI | OpenAI |
Input Price Cost per million input tokens | $3.00 / 1M | $2.00 / 1M |
Output Price Cost per million output tokens | $15.00 / 1M | $8.00 / 1M |
Blended Price Weighted 7:2:1 cache:input:output per 1M | $2.63 / 1M | $1.55 / 1M |
Context Window Maximum input + output tokens | 1M tokens~1,500 A4 pages of text | 1.05M tokens~1,571 A4 pages of text |
Max Output Tokens Per single request | 66K | 33K |
Throughput Speed Tokens generated per second | 135 tok/s | 110 tok/s |
SWE-bench Verified Real-world software engineering | 61.5% | 54.6% |
GPQA Diamond Graduate-level reasoning | 65.4% | 65% |
Cached Input Price Prompt caching discount per 1M tokens | $0.75 / 1M | $0.50 / 1M |
부문별 우위 모델
At-a-glance decision framework검증된 벤치마크 점수 비교
Official evaluation metrics verified by independent third-party research labs.
Industry benchmark evaluating real-world GitHub issue resolution and multi-file debugging.
Challenging questions created by domain experts to test complex PhD-level reasoning.
Hardened reasoning and academic knowledge benchmark with reduced lucky-guess probability.
Crowdsourced human preference evaluation based on blind, head-to-head model battles.
Extremely difficult, closed-ended questions spanning the frontier of human expert knowledge.
Autonomous multi-step tasks executed inside a real command-line terminal environment.
Research-grade coding problems drawn from real scientific and numerical workloads.
Contamination-free competitive programming problems collected continuously over time.
American Invitational Mathematics Examination — multi-step Olympiad-level reasoning.
Accuracy when reasoning over very large inputs that fill the model context window.
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.
Grok 4.20 (Non-Reasoning) · Strengths & Key Advantages
- xAI의 첨단 Colossus-Scale Sparse MoE 아키텍처와 최대 1M 토큰 컨텍스트 지원
- 경쟁력 있는 API 가격(입력 $1.25/1M, 출력 $2.5/1M)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
GPT-4.1 · Strengths & Key Advantages
- OpenAI의 첨단 Dense multimodal transformer 아키텍처와 최대 1.0M 토큰 컨텍스트 지원
- 경쟁력 있는 API 가격(입력 $2/1M, 출력 $8/1M)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 | Grok 4.20 (Non-Reasoning) | GPT-4.1 |
|---|---|---|
Cost per Task Estimated USD to finish one task | $0.88 | $0.72 |
Output Tokens / Task Tokens generated per task | 35K | 52K |
Reasoning Tokens / Task Thinking tokens burned per task | 0K | 0K |
기술 사양 (Specifications)
Architecture, release timeline, capabilities, and modalities.
| Feature | Grok 4.20 (Non-Reasoning) | GPT-4.1 |
|---|---|---|
| Official API Model ID (SDK) | grok-4-20-non-reasoning-latest | gpt-4-1 |
| API Protocol | xAI REST API (OpenAI-Compatible) | OpenAI Responses API & Chat Completions v1 |
| Release Date | 2026-03 | 2025-04 |
| Knowledge Cutoff | November 2025 | June 2024 |
| Architecture | Colossus-Scale Sparse MoE | Dense multimodal transformer |
| Parameters | Confidential | Confidential |
| Enterprise Rate Limits (RPM / TPM) | 5,000 – 15,000 RPM (Production Tier) · 4,000,000 – 10,000,000 TPM | 10,000 – 30,000 RPM (Tier 5 Enterprise) · 4,000,000 – 10,000,000 TPM |
| Long-Context Tier (>128K/200K) | Flat rate ($3/1M in) across full 1000K window | Flat rate ($2/1M in) across full 1048K window |
| Prompt Cache Policy & TTL | Cached input at $0.75/1M tokens | Automatic prefix caching at $0.5/1M (no extra cache-write fee) |
| Computer Use / GUI Agent | API / CLI Tool-Use & DOM Agent ready (no raw pixel desktop click loop) | Supported (Screen coordinate grounding, browser & desktop GUI action loops) |
| MCP & Parallel Tool Calling | Native MCP Client/Server ready · Parallel function calling · 100% Strict JSON Schema | Native MCP Client/Server ready · Parallel function calling · 100% Strict JSON Schema |
| Web Search Grounding & Sandbox | Real-time Web & X (Twitter) Search Grounding + Code Execution | Native Web Search tool + Hosted Code Interpreter & File Search RAG |
| Official Fine-Tuning Support | API Prompt Engineering & RAG Distillation | Supervised Fine-Tuning (SFT), Direct Preference (DPO) & Reinforcement Fine-Tuning (RFT) |
| 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 | xAI Production Safety & Alignment Verified | OpenAI Preparedness Framework Audited & System Card Published |
| 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 | text | text |
Grok 4.20 (Non-Reasoning) vs GPT-4.1: 핵심 요약 문답 (FAQ)
Which is more intelligent, Grok 4.20 (Non-Reasoning) or GPT-4.1?
Grok 4.20 (Non-Reasoning) is more intelligent. It scores 62 compared with 48 on the composite Intelligence Index.
Which model is faster?
Grok 4.20 (Non-Reasoning) is faster, generating 135 tokens per second compared with 110 tokens per second.
Which model is cheaper to run?
GPT-4.1 is cheaper at $1.55 per 1M tokens blended, compared with $2.63 (7:2:1 cache:input:output ratio).
Which model has lower latency?
Grok 4.20 (Non-Reasoning) has lower latency, with a time to first token of 0.42s compared with 0.48s.
Which model has a larger context window?
GPT-4.1 has a larger context window, supporting 1.05M tokens compared with 1M tokens.
종합 평가
Verdict & Model Selection Recommendation: Choose Grok 4.20 (Non-Reasoning) if your priority is Fast agentic tool pipelines, real-time interactive chat, and high-throughput document extraction. Its performance in demanding tasks justifies its operational token cost. Choose GPT-4.1 if your workflow prioritizes Long-document analysis, large-codebase review and structured extraction. 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 Grok 4.20 (Non-Reasoning) compare to GPT-4.1 in API token pricing and cost per token?+
Grok 4.20 (Non-Reasoning) costs $3.00 per 1M input tokens and $15.00 per 1M output tokens, whereas GPT-4.1 costs $2.00 input and $8.00 output. Overall, GPT-4.1 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: Grok 4.20 (Non-Reasoning) or GPT-4.1?+
Grok 4.20 (Non-Reasoning) supports a context window of 1,000K tokens (~750k words), while GPT-4.1 supports 1,048K tokens (~786k words). Therefore, GPT-4.1 can process more textual data and document context in a single prompt.
Which AI model is better for software engineering and coding: Grok 4.20 (Non-Reasoning) or GPT-4.1?+
Grok 4.20 (Non-Reasoning) scores 61.5% on SWE-bench Verified while GPT-4.1 scores 54.6%. For autonomous software engineering and multi-file debugging, Grok 4.20 (Non-Reasoning) holds the verified benchmark lead.
What is the difference in reasoning capability and extended thinking between Grok 4.20 (Non-Reasoning) and GPT-4.1?+
Grok 4.20 (Non-Reasoning) is optimized for low-latency direct generation. In contrast, GPT-4.1 focuses on standard fast inference.
How does inference speed (tokens per second) compare between Grok 4.20 (Non-Reasoning) and GPT-4.1?+
Grok 4.20 (Non-Reasoning) generates approximately 135 tokens per second, while GPT-4.1 delivers 110 tokens per second. In latency-sensitive production environments, Grok 4.20 (Non-Reasoning) provides faster time-to-first-token (TTFT) and higher streaming response velocity.
Can you implement a tiered LLM routing setup combining Grok 4.20 (Non-Reasoning) and GPT-4.1 to optimize costs?+
Yes! High-efficiency architectures route high-frequency routine classification and conversational tasks to GPT-4.1 to save operational costs, and dynamically escalate complex architectural queries or reasoning tasks to Grok 4.20 (Non-Reasoning). 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.
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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.
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