Head-to-Head Model Comparison

Grok Build 0.1 vs Grok 4.20 (Reasoning)

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 Build 0.1 vs Grok 4.20 (Reasoning): Benchmarks, Pricing & Speed Comparison

Grok Build 0.1 by xAI and Grok 4.20 (Reasoning) 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 Build 0.1 holds a notable pricing advantage for token ingestion. On output generation, Grok Build 0.1 is more economical per million generated tokens. In data-heavy architectures requiring extensive repository or document analysis, Grok 4.20 (Reasoning) provides an expanded memory horizon with 1,000K tokens. In latency-sensitive production environments, Grok Build 0.1 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 Build 0.1

深度推理模型

xAI 推出的 Grok Build 0.1 人工智能模型,具备 256K 上下文窗口,输入价格为 $1.0/百万 Token,输出价格为 $2.0/百万 Token,专为高质量生产环境、推理与自动化工作流打造。

Intelligence Index65 / 100
Input Token:

$1.00 / 1M

Output Token:

$2.00 / 1M

Context Window:

256K tokens

SWE-bench Verified:

69.8%

xAI

Grok 4.20 (Reasoning)

深度推理模型

xAI 推出的 Grok 4.20 (Reasoning) 人工智能模型,具备 1M 上下文窗口,输入价格为 $1.25/百万 Token,输出价格为 $2.5/百万 Token,专为高质量生产环境、推理与自动化工作流打造。

Intelligence Index68 / 100
Input Token:

$3.00 / 1M

Output Token:

$15.00 / 1M

Context Window:

1M tokens

SWE-bench Verified:

68.2%

核心差异一览

  • Grok Build 0.1 is 5.2x cheaper for API usage (input + output tokens combined).
  • Grok 4.20 (Reasoning) has a larger context window (1M vs 256K tokens).
  • Grok Build 0.1 is faster at 120 tok/s vs 95 tok/s.
  • Grok Build 0.1 leads on SWE-bench coding (69.8% vs 68.2%).
Need definitions for token pricing, context, or benchmarks?Explore AI Glossary →
FeatureGrok Build 0.1Grok 4.20 (Reasoning)
Intelligence Index
Composite reasoning & knowledge score (0-100)
6568
Provider
xAIxAI
Input Price
Cost per million input tokens
$1.00 / 1M$3.00 / 1M
Output Price
Cost per million output tokens
$2.00 / 1M$15.00 / 1M
Blended Price
Weighted 7:2:1 cache:input:output per 1M
$0.57 / 1M$2.63 / 1M
Context Window
Maximum input + output tokens
256K tokens~384 A4 pages of text1M tokens~1,500 A4 pages of text
Max Output Tokens
Per single request
66K66K
Throughput Speed
Tokens generated per second
120 tok/s95 tok/s
SWE-bench Verified
Real-world software engineering
69.8%68.2%
GPQA Diamond
Graduate-level reasoning
68.2%72.8%
Cached Input Price
Prompt caching discount per 1M tokens
$0.25 / 1M$0.75 / 1M

各项指标谁更胜一筹?

At-a-glance decision framework
Coding
Grok Build 0.1
+1.6% SWE-bench lead
Cost
Grok Build 0.1
5.2x cheaper monthly runtime
Speed
Grok Build 0.1
+26% faster generation
Context
Grok 4.20 (Reasoning)
1M tokens window

权威基准测试得分对比

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

Grok Build 0.1Grok 4.20 (Reasoning)
SWE-bench Verified (Autonomous Coding)

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

69.8%vs68.2%
GPQA Diamond (Doctorate-Level Science & Math)

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

68.2%vs72.8%
MMLU-Pro (Multi-task Language Understanding)

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

82.5%vs84.1%
LMSYS Chatbot Arena Elo

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

1375ptsvs1395pts
Humanity's Last Exam (Frontier Expert Knowledge)

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

10.5%vs11.8%
Terminal-Bench (Agentic Coding & Terminal Use)

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

46.2%vs44.5%
SciCode (Scientific Computing)

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

42%vs41.2%
LiveCodeBench (Competitive Coding)

Contamination-free competitive programming problems collected continuously over time.

68.5%vs66.5%
AIME (Advanced Math Competition)

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

82.1%vs86.4%
Long-Context Reasoning

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

80.4%vs89.2%
Generation Speed (Throughput)

Tokens emitted per second during active generation streaming.

120 tok/s vs95 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 Build 0.10.55s
Grok 4.20 (Reasoning)0.98s
Est. End-to-End Response (500 tokens)TTFT + generation time
Grok Build 0.14.72s
Grok 4.20 (Reasoning)6.24s

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 Build 0.1 Monthly API Bill
$3.67 / month
$1/1M in · $2/1M out
Grok 4.20 (Reasoning) Monthly API Bill
$19.13 / month
$3/1M in · $15/1M out
Grok Build 0.1 saves approximately $15.45 / month (81%) under this workload.5.2x Savings

Grok Build 0.1 · Strengths & Key Advantages

  • 由 xAI 研发的高精度 Code-Specialized Autoregressive Transformer 架构,支持 256K 上下文窗口
  • 极具竞争力的 API 定价(输入 $1.0/1M,输出 $2.0/1M),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

Grok 4.20 (Reasoning) · Strengths & Key Advantages

  • 由 xAI 研发的高精度 Colossus-Scale Reasoning Sparse MoE 架构,支持 1M 上下文窗口
  • 极具竞争力的 API 定价(输入 $1.25/1M,输出 $2.5/1M),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 Build 0.1Grok 4.20 (Reasoning)
Cost per Task
Estimated USD to finish one task
$0.95$1.45
Output Tokens / Task
Tokens generated per task
42K45K
Reasoning Tokens / Task
Thinking tokens burned per task
18K28K

技术规格参数

Architecture, release timeline, capabilities, and modalities.

FeatureGrok Build 0.1Grok 4.20 (Reasoning)
Official API Model ID (SDK)grok-build-0-1-latestgrok-4-20-reasoning-latest
API ProtocolxAI REST API (OpenAI-Compatible)xAI REST API (OpenAI-Compatible)
Release Date2026-042026-03
Knowledge CutoffJanuary 2026November 2025
ArchitectureCode-Specialized Autoregressive TransformerColossus-Scale Reasoning Sparse MoE
ParametersConfidentialConfidential
Enterprise Rate Limits (RPM / TPM)5,000 – 15,000 RPM (Production Tier) · 800,000 – 2,000,000 TPM5,000 – 15,000 RPM (Production Tier) · 4,000,000 – 10,000,000 TPM
Long-Context Tier (>128K/200K)Flat rate ($1/1M in) across full 256K windowFlat rate ($3/1M in) across full 1000K window
Prompt Cache Policy & TTLCached input at $0.25/1M tokensCached input at $0.75/1M tokens
Computer Use / GUI AgentAPI / CLI Tool-Use & DOM Agent ready (no raw pixel desktop click loop)API / CLI Tool-Use & DOM Agent ready (no raw pixel desktop click loop)
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 ExecutionReal-time Web & X (Twitter) Search Grounding + Code Execution
Official Fine-Tuning SupportAPI Prompt Engineering & RAG DistillationAPI Prompt Engineering & RAG 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 ClassificationxAI Production Safety & Alignment VerifiedxAI Production Safety & Alignment 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 Modalitiestexttext

Grok Build 0.1 vs Grok 4.20 (Reasoning): 常见问题解答 (FAQ)

Which is more intelligent, Grok Build 0.1 or Grok 4.20 (Reasoning)?

Grok 4.20 (Reasoning) is more intelligent. It scores 68 compared with 65 on the composite Intelligence Index.

Which model is faster?

Grok Build 0.1 is faster, generating 120 tokens per second compared with 95 tokens per second.

Which model is cheaper to run?

Grok Build 0.1 is cheaper at $0.57 per 1M tokens blended, compared with $2.63 (7:2:1 cache:input:output ratio).

Which model has lower latency?

Grok Build 0.1 has lower latency, with a time to first token of 0.55s compared with 0.98s.

Which model has a larger context window?

Grok 4.20 (Reasoning) has a larger context window, supporting 1M tokens compared with 256K tokens.

综合结论

Verdict & Model Selection Recommendation: Choose Grok Build 0.1 if your priority is IDE copilots, automated PR review agents, and rapid iterative software prototyping. Its performance in demanding tasks justifies its operational token cost. Choose Grok 4.20 (Reasoning) if your workflow prioritizes Deep document analysis, multi-stage enterprise research, and extensive tool-driven workflows. 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 Build 0.1 compare to Grok 4.20 (Reasoning) in API token pricing and cost per token?+

Grok Build 0.1 costs $1.00 per 1M input tokens and $2.00 per 1M output tokens, whereas Grok 4.20 (Reasoning) costs $3.00 input and $15.00 output. Overall, Grok Build 0.1 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 Build 0.1 or Grok 4.20 (Reasoning)?+

Grok Build 0.1 supports a context window of 256K tokens (~192k words), while Grok 4.20 (Reasoning) supports 1,000K tokens (~750k words). Therefore, Grok 4.20 (Reasoning) can process more textual data and document context in a single prompt.

Which AI model is better for software engineering and coding: Grok Build 0.1 or Grok 4.20 (Reasoning)?+

Grok Build 0.1 scores 69.8% on SWE-bench Verified while Grok 4.20 (Reasoning) scores 68.2%. For autonomous software engineering and multi-file debugging, Grok Build 0.1 holds the verified benchmark lead.

What is the difference in reasoning capability and extended thinking between Grok Build 0.1 and Grok 4.20 (Reasoning)?+

Grok Build 0.1 features native chain-of-thought extended thinking mode with configurable reasoning effort. In contrast, Grok 4.20 (Reasoning) provides chain-of-thought reasoning depth for complex math and science.

How does inference speed (tokens per second) compare between Grok Build 0.1 and Grok 4.20 (Reasoning)?+

Grok Build 0.1 generates approximately 120 tokens per second, while Grok 4.20 (Reasoning) delivers 95 tokens per second. In latency-sensitive production environments, Grok Build 0.1 provides faster time-to-first-token (TTFT) and higher streaming response velocity.

Can you implement a tiered LLM routing setup combining Grok Build 0.1 and Grok 4.20 (Reasoning) to optimize costs?+

Yes! High-efficiency architectures route high-frequency routine classification and conversational tasks to Grok Build 0.1 to save operational costs, and dynamically escalate complex architectural queries or reasoning tasks to Grok 4.20 (Reasoning). 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