Head-to-Head Model Comparison

Grok 4.1 vs GPT-5.1

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
Grok 4.1 vs GPT-5.1: Benchmarks, Pricing & Speed Comparison

Grok 4.1 by xAI and GPT-5.1 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, Grok 4.1 holds a notable pricing advantage for token ingestion. On output generation, Grok 4.1 is more economical per million generated tokens. In data-heavy architectures requiring extensive repository or document analysis, Grok 4.1 provides an expanded memory horizon with 2,000K tokens. In latency-sensitive production environments, Grok 4.1 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.

模型直接对比 (VS)

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xAI

Grok 4.1

深度推理模型

xAI 推出的 Grok 4.1 人工智能模型,具备 2M 上下文窗口,输入价格为 $0.2/百万 Token,输出价格为 $1/百万 Token,专为高质量生产环境、推理与自动化工作流打造。

Intelligence Index51 / 100
Input Token:

$0.20 / 1M

Output Token:

$1.00 / 1M

Context Window:

2M tokens

SWE-bench Verified:

66.4%

OpenAI

GPT-5.1

深度推理模型

OpenAI 推出的 GPT-5.1 人工智能模型,具备 400K 上下文窗口,输入价格为 $1.25/百万 Token,输出价格为 $10/百万 Token,专为高质量生产环境、推理与自动化工作流打造。

Intelligence Index60 / 100
Input Token:

$1.25 / 1M

Output Token:

$10.00 / 1M

Context Window:

400K tokens

SWE-bench Verified:

74.9%

核心差异一览

  • Grok 4.1 is 8.7x cheaper for API usage (input + output tokens combined).
  • Grok 4.1 has a larger context window (2M vs 400K tokens).
  • Grok 4.1 is faster at 142 tok/s vs 130 tok/s.
  • GPT-5.1 leads on SWE-bench coding (74.9% vs 66.4%).
Need definitions for token pricing, context, or benchmarks?Explore AI Glossary →
FeatureGrok 4.1GPT-5.1
Intelligence Index
Composite reasoning & knowledge score (0-100)
5160
Provider
xAIOpenAI
Input Price
Cost per million input tokens
$0.20 / 1M$1.25 / 1M
Output Price
Cost per million output tokens
$1.00 / 1M$10.00 / 1M
Blended Price
Weighted 7:2:1 cache:input:output per 1M
$0.17 / 1M$1.34 / 1M
Context Window
Maximum input + output tokens
2M tokens~3,000 A4 pages of text400K tokens~600 A4 pages of text
Max Output Tokens
Per single request
66K128K
Throughput Speed
Tokens generated per second
142 tok/s130 tok/s
SWE-bench Verified
Real-world software engineering
66.4%74.9%
GPQA Diamond
Graduate-level reasoning
63.8%72.1%
Cached Input Price
Prompt caching discount per 1M tokens
$0.05 / 1M$0.13 / 1M

各项指标谁更胜一筹?

At-a-glance decision framework
Coding
GPT-5.1
+8.5% SWE-bench lead
Cost
Grok 4.1
8.7x cheaper monthly runtime
Speed
Grok 4.1
+9% faster generation
Context
Grok 4.1
2M tokens window

权威基准测试得分对比

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

Grok 4.1GPT-5.1
SWE-bench Verified (Autonomous Coding)

Industry benchmark evaluating real-world GitHub issue resolution and multi-file debugging.

66.4%vs74.9%
GPQA Diamond (Doctorate-Level Science & Math)

Challenging questions created by domain experts to test complex PhD-level reasoning.

63.8%vs72.1%
MMLU-Pro (Multi-task Language Understanding)

Hardened reasoning and academic knowledge benchmark with reduced lucky-guess probability.

80.1%vs86.1%
LMSYS Chatbot Arena Elo

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

1298ptsvs1368pts
Humanity's Last Exam (Frontier Expert Knowledge)

Extremely difficult, closed-ended questions spanning the frontier of human expert knowledge.

8.2%vs12.1%
Terminal-Bench (Agentic Coding & Terminal Use)

Autonomous multi-step tasks executed inside a real command-line terminal environment.

38.5%vs46.7%
SciCode (Scientific Computing)

Research-grade coding problems drawn from real scientific and numerical workloads.

37.4%vs43.2%
LiveCodeBench (Competitive Coding)

Contamination-free competitive programming problems collected continuously over time.

64.9%vs71.8%
AIME (Advanced Math Competition)

American Invitational Mathematics Examination — multi-step Olympiad-level reasoning.

79.3%vs91.2%
Long-Context Reasoning

Accuracy when reasoning over very large inputs that fill the model context window.

76.2%vs77.9%
Generation Speed (Throughput)

Tokens emitted per second during active generation streaming.

142 tok/s vs130 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
Grok 4.11.50s
GPT-5.11.20s
Est. End-to-End Response (500 tokens)TTFT + generation time
Grok 4.15.02s
GPT-5.15.05s

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)
Grok 4.1 Monthly API Bill
$1.28 / month
$0.2/1M in · $1/1M out
GPT-5.1 Monthly API Bill
$11.06 / month
$1.25/1M in · $10/1M out
Grok 4.1 saves approximately $9.79 / month (88%) under this workload.8.7x Savings

Grok 4.1 · Strengths & Key Advantages

  • 由 xAI 研发的高精度 Sparse MoE 架构,支持 2M 上下文窗口
  • 极具竞争力的 API 定价(输入 $0.2/1M,输出 $1/1M),支持高速推理与工具调用
  • 在代码生成、逻辑推理与多语言处理基准测试中表现出色
Considerations & Trade-offs
  • 超长上下文请求需要规划 Token 成本与并发配额
  • 针对特定垂直领域任务建议结合系统提示词与检索增强(RAG)以获得最佳效果

GPT-5.1 · Strengths & Key Advantages

  • 由 OpenAI 研发的高精度 Unified Reasoning (Instant & Thinking) 架构,支持 400K 上下文窗口
  • 极具竞争力的 API 定价(输入 $1.25/1M,输出 $10/1M),支持高速推理与工具调用
  • 在代码生成、逻辑推理与多语言处理基准测试中表现出色
Considerations & Trade-offs
  • 超长上下文请求需要规划 Token 成本与并发配额
  • 针对特定垂直领域任务建议结合系统提示词与检索增强(RAG)以获得最佳效果

Token Use & Task Economics

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

MetricGrok 4.1GPT-5.1
Cost per Task
Estimated USD to finish one task
$0.28$1.45
Output Tokens / Task
Tokens generated per task
40K52K
Reasoning Tokens / Task
Thinking tokens burned per task
21K28K

技术规格参数

Architecture, release timeline, capabilities, and modalities.

FeatureGrok 4.1GPT-5.1
Official API Model ID (SDK)grok-4-1-latestgpt-5-1
API ProtocolxAI REST API (OpenAI-Compatible)OpenAI Responses API & Chat Completions v1
Release Date2025-112025-11
Knowledge Cutoff2025October 2024
ArchitectureSparse MoEUnified Reasoning (Instant & Thinking)
ParametersConfidentialConfidential
Enterprise Rate Limits (RPM / TPM)5,000 – 15,000 RPM (Production Tier) · 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)Flat rate ($0.2/1M in) across full 2000K windowFlat rate ($1.25/1M in) across full 400K window
Prompt Cache Policy & TTLCached input at $0.05/1M tokensAutomatic prefix caching at $0.125/1M (no extra cache-write fee)
Computer Use / GUI AgentAPI / CLI Tool-Use & DOM Agent ready (no raw pixel desktop click loop)Supported (Screen coordinate grounding, browser & desktop GUI action loops)
MCP & Parallel Tool CallingNative MCP Client/Server ready · Parallel function calling · 100% Strict JSON SchemaNative MCP Client/Server ready · Parallel function calling · 100% Strict JSON Schema
Web Search Grounding & SandboxReal-time Web & X (Twitter) Search Grounding + Code ExecutionNative Web Search tool + Hosted Code Interpreter & File Search RAG
Official Fine-Tuning SupportAPI Prompt Engineering & RAG DistillationSupervised Fine-Tuning (SFT), Direct Preference (DPO) & Reinforcement Fine-Tuning (RFT)
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 ClassificationxAI Production Safety & Alignment VerifiedOpenAI Preparedness Framework Audited & System Card Published
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 Modalitiestexttext

Grok 4.1 vs GPT-5.1: 常见问题解答 (FAQ)

Which is more intelligent, Grok 4.1 or GPT-5.1?

GPT-5.1 is more intelligent. It scores 60 compared with 51 on the composite Intelligence Index.

Which model is faster?

Grok 4.1 is faster, generating 142 tokens per second compared with 130 tokens per second.

Which model is cheaper to run?

Grok 4.1 is cheaper at $0.17 per 1M tokens blended, compared with $1.34 (7:2:1 cache:input:output ratio).

Which model has lower latency?

GPT-5.1 has lower latency, with a time to first token of 1.20s compared with 1.50s.

Which model has a larger context window?

Grok 4.1 has a larger context window, supporting 2M tokens compared with 400K tokens.

综合结论

Verdict & Model Selection Recommendation: Choose Grok 4.1 if your priority is High-volume applications, budget-constrained projects, data extraction, and large-scale prototyping. Its performance in demanding tasks justifies its operational token cost. Choose GPT-5.1 if your workflow prioritizes General-purpose production APIs and teams needing balanced quality, speed, and cost. For large-scale batch processing or customer-facing conversational interfaces, its balance of speed and economics delivers superior ROI.

常见问题 (FAQ)

How does Grok 4.1 compare to GPT-5.1 in API token pricing and cost per token?+

Grok 4.1 costs $0.20 per 1M input tokens and $1.00 per 1M output tokens, whereas GPT-5.1 costs $1.25 input and $10.00 output. Overall, Grok 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 4.1 or GPT-5.1?+

Grok 4.1 supports a context window of 2,000K tokens (~1,500k words), while GPT-5.1 supports 400K tokens (~300k words). Therefore, Grok 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 4.1 or GPT-5.1?+

Grok 4.1 scores 66.4% on SWE-bench Verified while GPT-5.1 scores 74.9%. For autonomous software engineering and multi-file debugging, GPT-5.1 holds the verified benchmark lead.

What is the difference in reasoning capability and extended thinking between Grok 4.1 and GPT-5.1?+

Grok 4.1 features native chain-of-thought extended thinking mode with configurable reasoning effort. In contrast, GPT-5.1 provides chain-of-thought reasoning depth for complex math and science.

How does inference speed (tokens per second) compare between Grok 4.1 and GPT-5.1?+

Grok 4.1 generates approximately 142 tokens per second, while GPT-5.1 delivers 130 tokens per second. In latency-sensitive production environments, Grok 4.1 provides faster time-to-first-token (TTFT) and higher streaming response velocity.

Can you implement a tiered LLM routing setup combining Grok 4.1 and GPT-5.1 to optimize costs?+

Yes! High-efficiency architectures route high-frequency routine classification and conversational tasks to Grok 4.1 to save operational costs, and dynamically escalate complex architectural queries or reasoning tasks to GPT-5.1. This tiered routing pattern cuts overall API bills by up to 70%.

AI Terminology & Guide
Explore Glossary →

Understand key metrics like context window, token pricing, reasoning mode, and SWE-bench scores in our comprehensive AI glossary.

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: GetInfoUs Independent AI Benchmarks & Official API Specs