Grok-3 vs Claude 3.7 Sonnet
Benchmarks, API Token Pricing, Context Window & Speed Comparison
Related topics (12)
Grok-3 di xAI e Claude 3.7 Sonnet di Anthropic sono due modelli di IA di riferimento. Grok-3 offre una finestra di contesto di 1M token a $3.00/$15.00 per milione di token, mentre Claude 3.7 Sonnet mette a disposizione 200K 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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Grok-3
Motore di Ragionamento ProfondoGrok-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
$3.00 / 1M
$15.00 / 1M
1M tokens
65.2%
Claude 3.7 Sonnet
Leader in Programmazione e CodiceClaude 3.7 Sonnet di Anthropic è un modello di IA progettato per l’ingegneria del software autonoma, il refactoring multi-file e il debug avanzato, con finestra di contesto da 200K, velocità di 72 token/s, indice di intelligenza di 48/100 e
$3.00 / 1M
$15.00 / 1M
200K tokens
70.3%
Differenze Chiave a Colpo d’Occhio
- Claude 3.7 Sonnet is 1.0x cheaper for API usage (input + output tokens combined).
- Grok-3 has a larger context window (1M vs 200K tokens).
- Grok-3 is faster at 95 tok/s vs 72 tok/s.
- Claude 3.7 Sonnet leads on SWE-bench coding (70.3% vs 65.2%).
| Feature | Grok-3 | Claude 3.7 Sonnet |
|---|---|---|
Intelligence Index Composite reasoning & knowledge score (0-100) | 54 | 48 |
Provider | xAI | Anthropic |
Input Price Cost per million input tokens | $3.00 / 1M | $3.00 / 1M |
Output Price Cost per million output tokens | $15.00 / 1M | $15.00 / 1M |
Blended Price Weighted 7:2:1 cache:input:output per 1M | $2.63 / 1M | $2.31 / 1M |
Context Window Maximum input + output tokens | 1M tokens~1,500 A4 pages of text | 200K tokens~300 A4 pages of text |
Max Output Tokens Per single request | 33K | 64K |
Throughput Speed Tokens generated per second | 95 tok/s | 72 tok/s |
SWE-bench Verified Real-world software engineering | 65.2% | 70.3% |
GPQA Diamond Graduate-level reasoning | 74% | 65% |
Cached Input Price Prompt caching discount per 1M tokens | $0.75 / 1M | $0.30 / 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.
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
Claude 3.7 Sonnet · Strengths & Key Advantages
- Finestra di contesto da 200K con capacità massima di output fino a 64K token (SWE-bench Verified 70.3% · GPQA Diamond 65%)
- Throughput elevato di 72 token/secondo con latenza al primo token (TTFT) di soli 520 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 | Grok-3 | Claude 3.7 Sonnet |
|---|---|---|
Cost per Task Estimated USD to finish one task | $0.20 | $1.42 |
Output Tokens / Task Tokens generated per task | 24K | 41K |
Reasoning Tokens / Task Thinking tokens burned per task | 15K | 22K |
Specifiche Tecniche
Architecture, release timeline, capabilities, and modalities.
| Feature | Grok-3 | Claude 3.7 Sonnet |
|---|---|---|
| Official API Model ID (SDK) | grok-3-latest | claude-3-7-sonnet-20250201 |
| API Protocol | xAI REST API (OpenAI-Compatible) | Anthropic Messages API + AWS Bedrock + Vertex AI |
| Release Date | 2025-02 | 2025-02 |
| Knowledge Cutoff | Late 2024 | November 2024 |
| Architecture | Hybrid Reasoning Deep MoE | Hybrid Reasoning MoE |
| Parameters | Confidential | Confidential |
| Enterprise Rate Limits (RPM / TPM) | 5,000 – 15,000 RPM (Production Tier) · 4,000,000 – 10,000,000 TPM | 4,000 – 10,000 RPM (Tier 4 + Priority Tier) · 800,000 – 2,000,000 TPM |
| Long-Context Tier (>128K/200K) | Flat rate ($3/1M in) across full 1000K window | Standard rate up to 200K tokens; 2x input/output tier above 200K tokens |
| Prompt Cache Policy & TTL | Cached input at $0.75/1M tokens | $0.3/1M cached read (90% off); 5-min default & 1-hour extended TTL |
| 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 Citations + Code Execution Tool + MCP Connectors |
| Official Fine-Tuning Support | API Prompt Engineering & RAG Distillation | Custom Model Tuning via Amazon Bedrock & Prompt 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 | xAI Production Safety & Alignment Verified | Anthropic 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 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 |
Grok-3 vs Claude 3.7 Sonnet: Risposte Rapide (FAQ)
Which is more intelligent, Grok-3 or Claude 3.7 Sonnet?
Grok-3 is more intelligent. It scores 54 compared with 48 on the composite Intelligence Index.
Which model is faster?
Grok-3 is faster, generating 95 tokens per second compared with 72 tokens per second.
Which model is cheaper to run?
Claude 3.7 Sonnet is cheaper at $2.31 per 1M tokens blended, compared with $2.63 (7:2:1 cache:input:output ratio).
Which model has lower latency?
Claude 3.7 Sonnet has lower latency, with a time to first token of 0.52s compared with 1.10s.
Which model has a larger context window?
Grok-3 has a larger context window, supporting 1M tokens compared with 200K 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 Claude 3.7 Sonnet (Ideale per l’ingegneria del software autonoma, il refactoring multi-file e il debug avanzato, sistemi RAG aziendali e integrazioni API scalabili.) eccellono in produzione: Grok-3 guida nei benchmark di ragionamento e programmazione, Grok-3 garantisce una generazione più rapida e Claude 3.7 Sonnet offre il miglior rapporto qualità-prezzo per carichi API elevati.
Domande Frequenti (FAQ)
Quale modello è migliore per coding e ragionamento, Grok-3 o Claude 3.7 Sonnet?+
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 Claude 3.7 Sonnet?+
Grok-3 costa $3.00 / $15.00 per milione di token di input/output, mentre Claude 3.7 Sonnet costa $3.00 / $15.00. Nel costo combinato, Claude 3.7 Sonnet risulta più economico.
Quale modello ha la finestra di contesto più ampia e la velocità maggiore?+
Grok-3 supporta 1M token di contesto contro 200K token di Claude 3.7 Sonnet, mentre Grok-3 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.
Related reading
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- Claude Sonnet 4 vs Claude 3.7 Sonnet: Confronto Benchmark, Prezzi API e Velocità (2026)Confronta
- Gemini 2.0 Pro vs Claude 3.7 Sonnet: Confronto Benchmark, Prezzi API e Velocità (2026)Confronta
- Grok 3 Mini vs Claude 3.7 Sonnet: Confronto Benchmark, Prezzi API e Velocità (2026)Confronta
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 xAI e Anthropic, schede di sistema e benchmark indipendenti (2026).