Head-to-Head Model Comparison

Grok 4.20 (Reasoning) vs o3

Benchmarks, API Token Pricing, Context Window & Speed Comparison

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AI CompareAI BenchmarkToken PricingModel CostModel SpecsSWE-bench CodingModel VersusWhich AI ModelLLM Speed & LatencyReasoning ModelsExtended ThinkingPrompt Caching ROI
Grok 4.20 (Reasoning) vs o3: Benchmarks, Pricing & Speed Comparison

Grok 4.20 (Reasoning) by xAI and o3 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, o3 holds a notable pricing advantage for token ingestion. On output generation, o3 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 4.20 (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.

Perbandingan Langsung (VS)

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Grok 4.20 (Reasoning)

Model Penalaran Mendalam

Grok 4.20 (Reasoning) dari xAI adalah model AI canggih dengan jendela konteks 1M token serta harga API $1.25/1M token input dan $2.5/1M token output untuk pemrograman, penalaran, dan otomasi bisnis.

Intelligence Index68 / 100
Input Token:

$3.00 / 1M

Output Token:

$15.00 / 1M

Context Window:

1M tokens

SWE-bench Verified:

68.2%

OpenAI

o3

Model Penalaran Mendalam

o3 dari OpenAI adalah model AI canggih dengan jendela konteks 200K token serta harga API $2/1M token input dan $8/1M token output untuk pemrograman, penalaran, dan otomasi bisnis.

Intelligence Index56 / 100
Input Token:

$2.00 / 1M

Output Token:

$8.00 / 1M

Context Window:

200K tokens

SWE-bench Verified:

69.1%

Perbedaan Utama Sekilas

  • o3 is 1.7x cheaper for API usage (input + output tokens combined).
  • Grok 4.20 (Reasoning) has a larger context window (1M vs 200K tokens).
  • Grok 4.20 (Reasoning) is faster at 95 tok/s vs 75 tok/s.
  • o3 leads on SWE-bench coding (69.1% vs 68.2%).
Need definitions for token pricing, context, or benchmarks?Explore AI Glossary →
FeatureGrok 4.20 (Reasoning)o3
Intelligence Index
Composite reasoning & knowledge score (0-100)
6856
Provider
xAIOpenAI
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 text200K tokens~300 A4 pages of text
Max Output Tokens
Per single request
66K100K
Throughput Speed
Tokens generated per second
95 tok/s75 tok/s
SWE-bench Verified
Real-world software engineering
68.2%69.1%
GPQA Diamond
Graduate-level reasoning
72.8%76.5%
Cached Input Price
Prompt caching discount per 1M tokens
$0.75 / 1M$0.50 / 1M

Siapa Unggul di Mana?

At-a-glance decision framework
Coding
o3
+0.9% SWE-bench lead
Cost
o3
1.7x cheaper monthly runtime
Speed
Grok 4.20 (Reasoning)
+27% faster generation
Context
Grok 4.20 (Reasoning)
1M tokens window

Skor Benchmark Terverifikasi

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

Grok 4.20 (Reasoning)o3
SWE-bench Verified (Autonomous Coding)

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

68.2%vs69.1%
GPQA Diamond (Doctorate-Level Science & Math)

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

72.8%vs76.5%
MMLU-Pro (Multi-task Language Understanding)

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

84.1%vs87%
LMSYS Chatbot Arena Elo

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

1395ptsvs1345pts
Humanity's Last Exam (Frontier Expert Knowledge)

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

11.8%vs12.9%
Terminal-Bench (Agentic Coding & Terminal Use)

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

44.5%vs42%
SciCode (Scientific Computing)

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

41.2%vs42.5%
LiveCodeBench (Competitive Coding)

Contamination-free competitive programming problems collected continuously over time.

66.5%vs70.5%
AIME (Advanced Math Competition)

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

86.4%vs91.6%
Long-Context Reasoning

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

89.2%vs78.5%
Generation Speed (Throughput)

Tokens emitted per second during active generation streaming.

95 tok/s vs75 tok/s

Latensi & Waktu Respons

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 4.20 (Reasoning)0.98s
o32.80s
Est. End-to-End Response (500 tokens)TTFT + generation time
Grok 4.20 (Reasoning)6.24s
o39.47s

Simulator Biaya Token Interaktif

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 4.20 (Reasoning) Monthly API Bill
$19.13 / month
$3/1M in · $15/1M out
o3 Monthly API Bill
$10.95 / month
$2/1M in · $8/1M out
o3 saves approximately $8.18 / month (43%) under this workload.1.7x Savings

Grok 4.20 (Reasoning) · Strengths & Key Advantages

  • Arsitektur Colossus-Scale Reasoning Sparse MoE mutakhir dari xAI dengan dukungan konteks 1M token
  • Efisiensi biaya API yang kompetitif ($1.25/1M input, $2.5/1M output) dan respons cepat
  • Performa andal dalam pembuatan kode, analisis logika, serta pemahaman multibahasa
Considerations & Trade-offs
  • Penggunaan konteks berukuran penuh memerlukan pengelolaan anggaran token yang cermat
  • Membutuhkan perancangan prompt yang tepat untuk kasus penggunaan industri spesifik

o3 · Strengths & Key Advantages

  • Arsitektur Reasoning transformer with adjustable thinking effort mutakhir dari OpenAI dengan dukungan konteks 200K token
  • Efisiensi biaya API yang kompetitif ($2/1M input, $8/1M output) dan respons cepat
  • Performa andal dalam pembuatan kode, analisis logika, serta pemahaman multibahasa
Considerations & Trade-offs
  • Penggunaan konteks berukuran penuh memerlukan pengelolaan anggaran token yang cermat
  • Membutuhkan perancangan prompt yang tepat untuk kasus penggunaan industri spesifik

Token Use & Task Economics

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

MetricGrok 4.20 (Reasoning)o3
Cost per Task
Estimated USD to finish one task
$1.45$1.35
Output Tokens / Task
Tokens generated per task
45K48K
Reasoning Tokens / Task
Thinking tokens burned per task
28K26K

Spesifikasi Teknis

Architecture, release timeline, capabilities, and modalities.

FeatureGrok 4.20 (Reasoning)o3
Official API Model ID (SDK)grok-4-20-reasoning-latesto3
API ProtocolxAI REST API (OpenAI-Compatible)OpenAI Responses API & Chat Completions v1
Release Date2026-032025-04
Knowledge CutoffNovember 2025June 2024
ArchitectureColossus-Scale Reasoning Sparse MoEReasoning transformer with adjustable thinking effort
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 ($3/1M in) across full 1000K windowFlat rate ($2/1M in) across full 200K window
Prompt Cache Policy & TTLCached input at $0.75/1M tokensAutomatic prefix caching at $0.5/1M (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 4.20 (Reasoning) vs o3: Jawaban Cepat (FAQ)

Which is more intelligent, Grok 4.20 (Reasoning) or o3?

Grok 4.20 (Reasoning) is more intelligent. It scores 68 compared with 56 on the composite Intelligence Index.

Which model is faster?

Grok 4.20 (Reasoning) is faster, generating 95 tokens per second compared with 75 tokens per second.

Which model is cheaper to run?

o3 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 (Reasoning) has lower latency, with a time to first token of 0.98s compared with 2.80s.

Which model has a larger context window?

Grok 4.20 (Reasoning) has a larger context window, supporting 1M tokens compared with 200K tokens.

Kesimpulan

Verdict & Model Selection Recommendation: Choose Grok 4.20 (Reasoning) if your priority is Deep document analysis, multi-stage enterprise research, and extensive tool-driven workflows. Its performance in demanding tasks justifies its operational token cost. Choose o3 if your workflow prioritizes Hard maths, science and agentic coding where accuracy beats latency. For large-scale batch processing or customer-facing conversational interfaces, its balance of speed and economics delivers superior ROI.

Pertanyaan Umum (FAQ)

How does Grok 4.20 (Reasoning) compare to o3 in API token pricing and cost per token?+

Grok 4.20 (Reasoning) costs $3.00 per 1M input tokens and $15.00 per 1M output tokens, whereas o3 costs $2.00 input and $8.00 output. Overall, o3 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 (Reasoning) or o3?+

Grok 4.20 (Reasoning) supports a context window of 1,000K tokens (~750k words), while o3 supports 200K tokens (~150k 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 4.20 (Reasoning) or o3?+

Grok 4.20 (Reasoning) scores 68.2% on SWE-bench Verified while o3 scores 69.1%. For autonomous software engineering and multi-file debugging, o3 holds the verified benchmark lead.

What is the difference in reasoning capability and extended thinking between Grok 4.20 (Reasoning) and o3?+

Grok 4.20 (Reasoning) features native chain-of-thought extended thinking mode with configurable reasoning effort. In contrast, o3 provides chain-of-thought reasoning depth for complex math and science.

How does inference speed (tokens per second) compare between Grok 4.20 (Reasoning) and o3?+

Grok 4.20 (Reasoning) generates approximately 95 tokens per second, while o3 delivers 75 tokens per second. In latency-sensitive production environments, Grok 4.20 (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 (Reasoning) and o3 to optimize costs?+

Yes! High-efficiency architectures route high-frequency routine classification and conversational tasks to o3 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.

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