Head-to-Head Model Comparison

Grok-3 vs GPT-4o

Benchmarks, API Token Pricing, Context Window & Speed Comparison

Verificato dal team di ricerca di GetInfoUsUltima verifica: October 2026Politica editoriale

Cambia e Confronta Qualsiasi Modello

Select any AI models from our verified benchmark database to generate live side-by-side matrices.

Grok-3Profile

GPT-4oProfile

Multi-Model Arena Stack:

5-Model Matrix Workbench

Popular Matchups:

xAI

Grok-3

Motore di Ragionamento Profondo

Grok-3 di xAI è un modello di IA progettato per il ragionamento logico profondo, la matematica avanzata e l’analisi scientifica, con finestra di contesto da 1M, velocità di 95 token/s, indice di intelligenza di 54/100 e tariffa di $3/$15 pe

Intelligence Index54 / 100

Input Token:

$3.00 / 1M

Output Token:

$15.00 / 1M

Context Window:

1M tokens

SWE-bench Verified:

65.2%

OpenAI

GPT-4o

Modello Vocale e Audio Nativo

GPT-4o di OpenAI è un modello di IA progettato per la sintesi vocale naturale, l’elaborazione audio in tempo reale e la trascrizione, con finestra di contesto da 128K, velocità di 105 token/s, indice di intelligenza di 41/100 e tariffa di $

Intelligence Index41 / 100

Input Token:

$2.50 / 1M

Output Token:

$10.00 / 1M

Context Window:

128K tokens

SWE-bench Verified:

38.8%

Differenze Chiave a Colpo d’Occhio

GPT-4o is 1.3x cheaper for API usage (input + output tokens combined).
Grok-3 has a larger context window (1M vs 128K tokens).
GPT-4o is faster at 105 tok/s vs 95 tok/s.
Grok-3 leads on SWE-bench coding (65.2% vs 38.8%).

Need definitions for token pricing, context, or benchmarks?Explore AI Glossary →

Feature	Grok-3	GPT-4o
Intelligence Index Composite reasoning & knowledge score (0-100)	54	41
Provider	xAI	OpenAI
Input Price Cost per million input tokens	$3.00 / 1M	$2.50 / 1M
Output Price Cost per million output tokens	$15.00 / 1M	$10.00 / 1M
Blended Price Weighted 7:2:1 cache:input:output per 1M	$2.63 / 1M	$2.38 / 1M
Context Window Maximum input + output tokens	1M tokens~1,500 A4 pages of text	128K tokens~192 A4 pages of text
Max Output Tokens Per single request	33K	16K
Throughput Speed Tokens generated per second	95 tok/s	105 tok/s
SWE-bench Verified Real-world software engineering	65.2%	38.8%
GPQA Diamond Graduate-level reasoning	74%	53.6%
Cached Input Price Prompt caching discount per 1M tokens	$0.75 / 1M	$1.25 / 1M

Chi vince in ogni categoria?

At-a-glance decision framework

Coding

Grok-3

+26.4% SWE-bench lead

Cost

GPT-4o

1.3x cheaper monthly runtime

Speed

GPT-4o

+11% faster generation

Context

Grok-3

1M tokens window

Punteggi Benchmark Verificati

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

Grok-3GPT-4o

SWE-bench Verified (Autonomous Coding)

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

65.2%vs38.8%

GPQA Diamond (Doctorate-Level Science & Math)

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

74%vs53.6%

MMLU-Pro (Multi-task Language Understanding)

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

88.5%vs72.6%

LMSYS Chatbot Arena Elo

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

1342ptsvs1286pts

Humanity's Last Exam (Frontier Expert Knowledge)

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

10.2%vs4.1%

Terminal-Bench (Agentic Coding & Terminal Use)

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

41%vs18.5%

SciCode (Scientific Computing)

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

42.5%vs27.3%

LiveCodeBench (Competitive Coding)

Contamination-free competitive programming problems collected continuously over time.

70.8%vs43.9%

AIME (Advanced Math Competition)

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

82.5%vs29.7%

Long-Context Reasoning

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

78.5%vs58.2%

Generation Speed (Throughput)

Tokens emitted per second during active generation streaming.

95 tok/s vs105 tok/s

Latenza e Tempo di Risposta

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-31.10s

GPT-4o0.41s

Est. End-to-End Response (500 tokens)TTFT + generation time

Grok-36.36s

GPT-4o5.17s

Simulatore Interattivo dei Costi Token

Adjust sliders to calculate projected monthly cloud API spending with prompt caching discounts.

Daily Input Tokens100K / day

10K500K1M

Daily Output Tokens30K / day

5K150K300K

Prompt Cache Hit Ratio50% cached

0% (Cold)50%90% (Warm)

Grok-3 Monthly API Bill

$19.13 / month

$3/1M in · $15/1M out

GPT-4o Monthly API Bill

$14.63 / month

$2.5/1M in · $10/1M out

GPT-4o saves approximately $4.50 / month (24%) under this workload.1.3x Savings

Grok-3 · Strengths & Key Advantages

Finestra di contesto da 1M con capacità massima di output fino a 33K token (SWE-bench Verified 65.2% · GPQA Diamond 74%)
Throughput elevato di 95 token/secondo con latenza al primo token (TTFT) di soli 1100 ms
Economia API competitiva ($3/$15 per 1M di token) con supporto per prompt caching, tool calling e output JSON strutturati

Considerations & Trade-offs

Modello cloud proprietario chiuso; non consente il download locale dei pesi per l’esecuzione offline
Per volumi di traffico elevati in produzione si consiglia di attivare il prompt caching e la Batch API

GPT-4o · Strengths & Key Advantages

Finestra di contesto da 128K con capacità massima di output fino a 16K token (SWE-bench Verified 38.8% · GPQA Diamond 53.6%)
Throughput elevato di 105 token/secondo con latenza al primo token (TTFT) di soli 410 ms
Economia API competitiva ($2.5/$10 per 1M di token) con supporto per prompt caching, tool calling e output JSON strutturati

Considerations & Trade-offs

Modello cloud proprietario chiuso; non consente il download locale dei pesi per l’esecuzione offline
Per volumi di traffico elevati in produzione si consiglia di attivare il prompt caching e la Batch API

Token Use & Task Economics

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

Metric	Grok-3	GPT-4o
Cost per Task Estimated USD to finish one task	$0.20	$0.68
Output Tokens / Task Tokens generated per task	24K	24K
Reasoning Tokens / Task Thinking tokens burned per task	15K	0K

Specifiche Tecniche

Architecture, release timeline, capabilities, and modalities.

Feature	Grok-3	GPT-4o
Official API Model ID (SDK)	grok-3-latest	gpt-4o
API Protocol	xAI REST API (OpenAI-Compatible)	OpenAI Responses API & Chat Completions v1
Release Date	2025-02	2024-05
Knowledge Cutoff	Late 2024	October 2023
Architecture	Hybrid Reasoning Deep MoE	Omni-Multimodal Dense
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) · 800,000 – 2,000,000 TPM
Long-Context Tier (>128K/200K)	Flat rate ($3/1M in) across full 1000K window	Flat rate ($2.5/1M in) across full 128K window
Prompt Cache Policy & TTL	Cached input at $0.75/1M tokens	Automatic prefix caching at $1.25/1M (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) · Audio (~25–32 tokens/sec)
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, audio
Output Modalities	text	text, audio

Grok-3 vs GPT-4o: Risposte Rapide (FAQ)

Which is more intelligent, Grok-3 or GPT-4o?

Grok-3 is more intelligent. It scores 54 compared with 41 on the composite Intelligence Index.

Which model is faster?

GPT-4o is faster, generating 105 tokens per second compared with 95 tokens per second.

Which model is cheaper to run?

GPT-4o is cheaper at $2.38 per 1M tokens blended, compared with $2.63 (7:2:1 cache:input:output ratio).

Which model has lower latency?

GPT-4o has lower latency, with a time to first token of 0.41s compared with 1.10s.

Which model has a larger context window?

Grok-3 has a larger context window, supporting 1M tokens compared with 128K tokens.

Verdetto

Sia Grok-3 (Ideale per il ragionamento logico profondo, la matematica avanzata e l’analisi scientifica, sistemi RAG aziendali e integrazioni API scalabili.) sia GPT-4o (Ideale per la sintesi vocale naturale, l’elaborazione audio in tempo reale e la trascrizione, sistemi RAG aziendali e integrazioni API scalabili.) eccellono in produzione: Grok-3 guida nei benchmark di ragionamento e programmazione, GPT-4o garantisce una generazione più rapida e GPT-4o offre il miglior rapporto qualità-prezzo per carichi API elevati.

Domande Frequenti (FAQ)

Quale modello è migliore per coding e ragionamento, Grok-3 o GPT-4o?+

Nell’indice di intelligenza composito e nei benchmark di programmazione prevale Grok-3. Consulta i punteggi SWE-bench e GPQA qui sopra per tutti i dettagli.

Qual è la differenza di prezzo API tra Grok-3 e GPT-4o?+

Grok-3 costa $3.00 / $15.00 per milione di token di input/output, mentre GPT-4o costa $2.50 / $10.00. Nel costo combinato, GPT-4o risulta più economico.

Quale modello ha la finestra di contesto più ampia e la velocità maggiore?+

Grok-3 supporta 1M token di contesto contro 128K token di GPT-4o, mentre GPT-4o offre una velocità di generazione superiore.

AI Terminology & Guide

Explore Glossary →

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

Tokens & Pricing Context Window AI Benchmarks Reasoning Models Tool Calling Model Context Protocol (MCP)

Grok-3 vs GPT-4o

Cambia e Confronta Qualsiasi Modello

Grok-3

GPT-4o

Chi vince in ogni categoria?

Punteggi Benchmark Verificati

Latenza e Tempo di Risposta

Simulatore Interattivo dei Costi Token

Grok-3 · Strengths & Key Advantages

Considerations & Trade-offs

GPT-4o · Strengths & Key Advantages

Considerations & Trade-offs

Token Use & Task Economics

Specifiche Tecniche

Grok-3 vs GPT-4o: Risposte Rapide (FAQ)

Verdetto

Domande Frequenti (FAQ)

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