Head-to-Head Model Comparison

Grok 3 Mini vs Claude 3.7 Sonnet

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 3 Mini vs Claude 3.7 Sonnet: Benchmarks, Pricing & Speed Comparison

xAI 的 Grok 3 Mini 与 Anthropic 的 Claude 3.7 Sonnet 是当前备受关注的两款主力 AI 模型。Grok 3 Mini 提供 131.1K Token 上下文窗口,API 定价为每百万 Token 输入 $0.30 / 输出 $1.20;而 Claude 3.7 Sonnet 提供 200K Token 上下文窗口,定价为每百万 Token 输入 $3.00 / 输出 $15.00。以下为两者的基准测试、延迟与成本全面对比。

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Grok 3 Mini

深度逻辑推理引擎

xAI 推出的 Grok 3 Mini 是一款专为博士级数理逻辑、科学推导与多步思维链 (CoT) 设计的深度推理大模型,具备 131K 上下文窗口、90 Token/秒生成速度与 47/100 综合智能指数(每百万 Token $0.3 输入 / $1.2 输出)。

Intelligence Index47 / 100
Input Token:

$0.30 / 1M

Output Token:

$1.20 / 1M

Context Window:

131.1K tokens

SWE-bench Verified:

56.4%

Anthropic

Claude 3.7 Sonnet

顶级编程与软件工程

Anthropic 推出的 Claude 3.7 Sonnet 是一款专为自主软件工程、跨文件代码重构与复杂调试打造的旗舰编程大模型,具备 200K 上下文窗口、72 Token/秒生成速度与 48/100 综合智能指数(每百万 Token $3 输入 / $15 输出)。

Intelligence Index48 / 100
Input Token:

$3.00 / 1M

Output Token:

$15.00 / 1M

Context Window:

200K tokens

SWE-bench Verified:

70.3%

核心差异一览

  • Grok 3 Mini is 11.2x cheaper for API usage (input + output tokens combined).
  • Claude 3.7 Sonnet has a larger context window (200K vs 131K tokens).
  • Grok 3 Mini is faster at 90 tok/s vs 72 tok/s.
  • Claude 3.7 Sonnet leads on SWE-bench coding (70.3% vs 56.4%).
Need definitions for token pricing, context, or benchmarks?Explore AI Glossary →
FeatureGrok 3 MiniClaude 3.7 Sonnet
Intelligence Index
Composite reasoning & knowledge score (0-100)
4748
Provider
xAIAnthropic
Input Price
Cost per million input tokens
$0.30 / 1M$3.00 / 1M
Output Price
Cost per million output tokens
$1.20 / 1M$15.00 / 1M
Blended Price
Weighted 7:2:1 cache:input:output per 1M
$0.23 / 1M$2.31 / 1M
Context Window
Maximum input + output tokens
131.1K tokens~197 A4 pages of text200K tokens~300 A4 pages of text
Max Output Tokens
Per single request
16K64K
Throughput Speed
Tokens generated per second
90 tok/s72 tok/s
SWE-bench Verified
Real-world software engineering
56.4%70.3%
GPQA Diamond
Graduate-level reasoning
68.4%65%
Cached Input Price
Prompt caching discount per 1M tokens
$0.07 / 1M$0.30 / 1M

各项指标谁更胜一筹?

At-a-glance decision framework
Coding
Claude 3.7 Sonnet
+13.9% SWE-bench lead
Cost
Grok 3 Mini
11.2x cheaper monthly runtime
Speed
Grok 3 Mini
+25% faster generation
Context
Claude 3.7 Sonnet
200K tokens window

权威基准测试得分对比

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

Grok 3 MiniClaude 3.7 Sonnet
SWE-bench Verified (Autonomous Coding)

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

56.4%vs70.3%
GPQA Diamond (Doctorate-Level Science & Math)

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

68.4%vs65%
MMLU-Pro (Multi-task Language Understanding)

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

77.5%vs78.2%
LMSYS Chatbot Arena Elo

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

1324ptsvs1335pts
Humanity's Last Exam (Frontier Expert Knowledge)

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

10.5%vs8.9%
Terminal-Bench (Agentic Coding & Terminal Use)

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

33.8%vs35.2%
SciCode (Scientific Computing)

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

38.5%vs40.1%
LiveCodeBench (Competitive Coding)

Contamination-free competitive programming problems collected continuously over time.

62.1%vs64.8%
AIME (Advanced Math Competition)

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

74.2%vs61.3%
Long-Context Reasoning

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

69.4%vs71.5%
Generation Speed (Throughput)

Tokens emitted per second during active generation streaming.

90 tok/s vs72 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 3 Mini0.51s
Claude 3.7 Sonnet0.52s
Est. End-to-End Response (500 tokens)TTFT + generation time
Grok 3 Mini6.07s
Claude 3.7 Sonnet7.46s

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 3 Mini Monthly API Bill
$1.64 / month
$0.3/1M in · $1.2/1M out
Claude 3.7 Sonnet Monthly API Bill
$18.45 / month
$3/1M in · $15/1M out
Grok 3 Mini saves approximately $16.81 / month (91%) under this workload.11.2x Savings

Grok 3 Mini · Strengths & Key Advantages

  • 提供 131K 上下文窗口与最高 16K 输出容量,核心基准表现优异(SWE-bench Verified 56.4% · GPQA Diamond 68.4%)
  • 高达 90 Token/秒的生成吞吐量,首字延迟 (TTFT) 仅约 510 毫秒
  • 极具竞争力的 API 定价(每百万 Token $0.3 输入 / $1.2 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
  • 在超长链路的前沿科研推导任务上,深度略逊于顶配重型旗舰推理模型

Claude 3.7 Sonnet · Strengths & Key Advantages

  • 提供 200K 上下文窗口与最高 64K 输出容量,核心基准表现优异(SWE-bench Verified 70.3% · GPQA Diamond 65%)
  • 高达 72 Token/秒的生成吞吐量,首字延迟 (TTFT) 仅约 520 毫秒
  • 极具竞争力的 API 定价(每百万 Token $3 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

Token Use & Task Economics

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

MetricGrok 3 MiniClaude 3.7 Sonnet
Cost per Task
Estimated USD to finish one task
$0.32$1.42
Output Tokens / Task
Tokens generated per task
26K41K
Reasoning Tokens / Task
Thinking tokens burned per task
18K22K

技术规格参数

Architecture, release timeline, capabilities, and modalities.

FeatureGrok 3 MiniClaude 3.7 Sonnet
Official API Model ID (SDK)grok-3-mini-latestclaude-3-7-sonnet-20250201
API ProtocolxAI REST API (OpenAI-Compatible)Anthropic Messages API + AWS Bedrock + Vertex AI
Release Date2025-022025-02
Knowledge CutoffNovember 2024November 2024
ArchitectureReasoning Optimized Hybrid TransformerHybrid Reasoning MoE
ParametersConfidentialConfidential
Enterprise Rate Limits (RPM / TPM)5,000 – 15,000 RPM (Production Tier) · 800,000 – 2,000,000 TPM4,000 – 10,000 RPM (Tier 4 + Priority Tier) · 800,000 – 2,000,000 TPM
Long-Context Tier (>128K/200K)Flat rate ($0.3/1M in) across full 131K windowStandard rate up to 200K tokens; 2x input/output tier above 200K tokens
Prompt Cache Policy & TTLCached input at $0.075/1M tokens$0.3/1M cached read (90% off); 5-min default & 1-hour extended TTL
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 Citations + Code Execution Tool + MCP Connectors
Official Fine-Tuning SupportAPI Prompt Engineering & RAG DistillationCustom Model Tuning via Amazon Bedrock & Prompt Distillation
Multimodal Token BillingText BPE (~4 chars/token)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 VerifiedAnthropic RSP ASL-2 / ASL-3 Constitutional Safety Evaluated
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 Modalitiestexttext, vision
Output Modalitiestexttext

Grok 3 Mini vs Claude 3.7 Sonnet: 常见问题解答 (FAQ)

Which is more intelligent, Grok 3 Mini or Claude 3.7 Sonnet?

Claude 3.7 Sonnet is more intelligent. It scores 48 compared with 47 on the composite Intelligence Index.

Which model is faster?

Grok 3 Mini is faster, generating 90 tokens per second compared with 72 tokens per second.

Which model is cheaper to run?

Grok 3 Mini is cheaper at $0.23 per 1M tokens blended, compared with $2.31 (7:2:1 cache:input:output ratio).

Which model has lower latency?

Grok 3 Mini has lower latency, with a time to first token of 0.51s compared with 0.52s.

Which model has a larger context window?

Claude 3.7 Sonnet has a larger context window, supporting 200K tokens compared with 131.1K tokens.

综合结论

综合来看,Grok 3 Mini(适合:专为博士级数理逻辑、科学推导与多步思维链 (CoT) 设计的深度推理任务、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 Claude 3.7 Sonnet(适合:专为自主软件工程、跨文件代码重构与复杂调试打造的旗舰编程任务、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:Claude 3.7 Sonnet 在综合智能与编程基准测试中表现更强,Grok 3 Mini 拥有更快的 Token 生成速度,而 Grok 3 Mini 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,Grok 3 Mini 和 Claude 3.7 Sonnet 哪个更强?+

在综合智能指数与编程基准评测中,Claude 3.7 Sonnet 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。

Grok 3 Mini 与 Claude 3.7 Sonnet 的 API 价格哪个更便宜?+

Grok 3 Mini 的 API 价格为输入 $0.30 / 输出 $1.20(每百万 Token),Claude 3.7 Sonnet 为输入 $3.00 / 输出 $15.00。综合混合成本来看,Grok 3 Mini 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?+

Grok 3 Mini 支持 131.1K Token 上下文窗口,而 Claude 3.7 Sonnet 支持 200K Token。在流式生成速度方面,Grok 3 Mini 的吞吐表现更快。

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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.

数据来源: xAI 与 Anthropic 官方 API 文档、模型发布说明及独立基准测试报告 (2026)。