o3-pro vs Grok 4.20 (Reasoning)
Benchmarks, API Token Pricing, Context Window & Speed Comparison
Related topics (12)
o3-pro di OpenAI e Grok 4.20 (Reasoning) di xAI sono due modelli di IA di riferimento. o3-pro offre una finestra di contesto di 200K token a $20.00/$80.00 per milione di token, mentre Grok 4.20 (Reasoning) mette a disposizione 1M token di contesto a $3.00/$15.00 per milione di token. Di seguito analizziamo benchmark, latenza e costi.
Cambia e Confronta Qualsiasi Modello
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o3-pro
Motore di Ragionamento Profondoo3-pro di OpenAI è un modello di IA progettato per il ragionamento logico profondo, la matematica avanzata e l’analisi scientifica, con finestra di contesto da 200K, velocità di 30 token/s, indice di intelligenza di 58/100 e tariffa di $20/
$20.00 / 1M
$80.00 / 1M
200K tokens
71.5%
Grok 4.20 (Reasoning)
Motore di Ragionamento ProfondoGrok 4.20 (Reasoning) 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 68/100 e tarif
$3.00 / 1M
$15.00 / 1M
1M tokens
68.2%
Differenze Chiave a Colpo d’Occhio
- Grok 4.20 (Reasoning) is 5.7x 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 30 tok/s.
- o3-pro leads on SWE-bench coding (71.5% vs 68.2%).
| Feature | o3-pro | Grok 4.20 (Reasoning) |
|---|---|---|
Intelligence Index Composite reasoning & knowledge score (0-100) | 58 | 68 |
Provider | OpenAI | xAI |
Input Price Cost per million input tokens | $20.00 / 1M | $3.00 / 1M |
Output Price Cost per million output tokens | $80.00 / 1M | $15.00 / 1M |
Blended Price Weighted 7:2:1 cache:input:output per 1M | $15.50 / 1M | $2.63 / 1M |
Context Window Maximum input + output tokens | 200K tokens~300 A4 pages of text | 1M tokens~1,500 A4 pages of text |
Max Output Tokens Per single request | 100K | 66K |
Throughput Speed Tokens generated per second | 30 tok/s | 95 tok/s |
SWE-bench Verified Real-world software engineering | 71.5% | 68.2% |
GPQA Diamond Graduate-level reasoning | 79.5% | 72.8% |
Cached Input Price Prompt caching discount per 1M tokens | $5.00 / 1M | $0.75 / 1M |
Chi vince in ogni categoria?
At-a-glance decision frameworkPunteggi Benchmark Verificati
Official evaluation metrics verified by independent third-party research labs.
Industry benchmark evaluating real-world GitHub issue resolution and multi-file debugging.
Challenging questions created by domain experts to test complex PhD-level reasoning.
Hardened reasoning and academic knowledge benchmark with reduced lucky-guess probability.
Crowdsourced human preference evaluation based on blind, head-to-head model battles.
Extremely difficult, closed-ended questions spanning the frontier of human expert knowledge.
Autonomous multi-step tasks executed inside a real command-line terminal environment.
Research-grade coding problems drawn from real scientific and numerical workloads.
Contamination-free competitive programming problems collected continuously over time.
American Invitational Mathematics Examination — multi-step Olympiad-level reasoning.
Accuracy when reasoning over very large inputs that fill the model context window.
Tokens emitted per second during active generation streaming.
Latenza e Tempo di Risposta
Time to first token (TTFT) and estimated end-to-end response time for a typical 500-token response.
Simulatore Interattivo dei Costi Token
Adjust sliders to calculate projected monthly cloud API spending with prompt caching discounts.
o3-pro · Strengths & Key Advantages
- Finestra di contesto da 200K con capacità massima di output fino a 100K token (SWE-bench Verified 71.5% · GPQA Diamond 79.5%)
- Throughput elevato di 30 token/secondo con latenza al primo token (TTFT) di soli 5200 ms
- Economia API competitiva ($20/$80 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
Grok 4.20 (Reasoning) · Strengths & Key Advantages
- Finestra di contesto da 1M con capacità massima di output fino a 66K token (SWE-bench Verified 68.2% · GPQA Diamond 72.8%)
- Throughput elevato di 95 token/secondo con latenza al primo token (TTFT) di soli 980 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
Token Use & Task Economics
Estimated cost and token consumption to complete one representative agentic task.
| Metric | o3-pro | Grok 4.20 (Reasoning) |
|---|---|---|
Cost per Task Estimated USD to finish one task | $11.68 | $1.45 |
Output Tokens / Task Tokens generated per task | 58K | 45K |
Reasoning Tokens / Task Thinking tokens burned per task | 38K | 28K |
Specifiche Tecniche
Architecture, release timeline, capabilities, and modalities.
| Feature | o3-pro | Grok 4.20 (Reasoning) |
|---|---|---|
| Official API Model ID (SDK) | o3-pro | grok-4-20-reasoning-latest |
| API Protocol | OpenAI Responses API & Chat Completions v1 | xAI REST API (OpenAI-Compatible) |
| Release Date | 2025-06 | 2026-03 |
| Knowledge Cutoff | June 2024 | November 2025 |
| Architecture | High-effort reasoning transformer | Colossus-Scale Reasoning Sparse MoE |
| Parameters | Confidential | Confidential |
| Enterprise Rate Limits (RPM / TPM) | 10,000 – 30,000 RPM (Tier 5 Enterprise) · 800,000 – 2,000,000 TPM | 5,000 – 15,000 RPM (Production Tier) · 4,000,000 – 10,000,000 TPM |
| Long-Context Tier (>128K/200K) | Flat rate ($20/1M in) across full 200K window | Flat rate ($3/1M in) across full 1000K window |
| Prompt Cache Policy & TTL | Automatic prefix caching at $5/1M (no extra cache-write fee) | Cached input at $0.75/1M tokens |
| Computer Use / GUI Agent | Supported (Screen coordinate grounding, browser & desktop GUI action loops) | API / CLI Tool-Use & DOM Agent ready (no raw pixel desktop click loop) |
| 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 | Native Web Search tool + Hosted Code Interpreter & File Search RAG | Real-time Web & X (Twitter) Search Grounding + Code Execution |
| Official Fine-Tuning Support | Supervised Fine-Tuning (SFT), Direct Preference (DPO) & Reinforcement Fine-Tuning (RFT) | API Prompt Engineering & RAG Distillation |
| 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) |
| 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 | OpenAI Preparedness Framework Audited & System Card Published | xAI Production Safety & Alignment Verified |
| 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 |
| Output Modalities | text | text |
o3-pro vs Grok 4.20 (Reasoning): Risposte Rapide (FAQ)
Which is more intelligent, o3-pro or Grok 4.20 (Reasoning)?
Grok 4.20 (Reasoning) is more intelligent. It scores 68 compared with 58 on the composite Intelligence Index.
Which model is faster?
Grok 4.20 (Reasoning) is faster, generating 95 tokens per second compared with 30 tokens per second.
Which model is cheaper to run?
Grok 4.20 (Reasoning) is cheaper at $2.63 per 1M tokens blended, compared with $15.50 (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 5.20s.
Which model has a larger context window?
Grok 4.20 (Reasoning) has a larger context window, supporting 1M tokens compared with 200K tokens.
Verdetto
Sia o3-pro (Ideale per il ragionamento logico profondo, la matematica avanzata e l’analisi scientifica, sistemi RAG aziendali e integrazioni API scalabili.) sia Grok 4.20 (Reasoning) (Ideale per il ragionamento logico profondo, la matematica avanzata e l’analisi scientifica, sistemi RAG aziendali e integrazioni API scalabili.) eccellono in produzione: Grok 4.20 (Reasoning) guida nei benchmark di ragionamento e programmazione, Grok 4.20 (Reasoning) garantisce una generazione più rapida e Grok 4.20 (Reasoning) offre il miglior rapporto qualità-prezzo per carichi API elevati.
Domande Frequenti (FAQ)
Quale modello è migliore per coding e ragionamento, o3-pro o Grok 4.20 (Reasoning)?+
Nell’indice di intelligenza composito e nei benchmark di programmazione prevale Grok 4.20 (Reasoning). Consulta i punteggi SWE-bench e GPQA qui sopra per tutti i dettagli.
Qual è la differenza di prezzo API tra o3-pro e Grok 4.20 (Reasoning)?+
o3-pro costa $20.00 / $80.00 per milione di token di input/output, mentre Grok 4.20 (Reasoning) costa $3.00 / $15.00. Nel costo combinato, Grok 4.20 (Reasoning) risulta più economico.
Quale modello ha la finestra di contesto più ampia e la velocità maggiore?+
o3-pro supporta 200K token di contesto contro 1M token di Grok 4.20 (Reasoning), mentre Grok 4.20 (Reasoning) offre una velocità di generazione superiore.
Understand key metrics like context window, token pricing, reasoning mode, and SWE-bench scores in our comprehensive AI glossary.
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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.
Fonti ufficiali: Documentazione API ufficiale di OpenAI e xAI, schede di sistema e benchmark indipendenti (2026).