Claude 3.5 Sonnet vs GPT-4o
Benchmarks, API Token Pricing, Context Window & Speed Comparison
Related topics (12)
Claude 3.5 Sonnet di Anthropic e GPT-4o di OpenAI sono due modelli di IA di riferimento. Claude 3.5 Sonnet offre una finestra di contesto di 200K token a $3.00/$15.00 per milione di token, mentre GPT-4o mette a disposizione 128K token di contesto a $2.50/$10.00 per milione di token. Di seguito analizziamo benchmark, latenza e costi.
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Claude 3.5 Sonnet
Leader in Programmazione e CodiceClaude 3.5 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 80 token/s, indice di intelligenza di 50/100 e
$3.00 / 1M
$15.00 / 1M
200K tokens
65%
GPT-4o
Modello Vocale e Audio NativoGPT-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 $
$2.50 / 1M
$10.00 / 1M
128K tokens
38.8%
Differenze Chiave a Colpo d’Occhio
- GPT-4o is 1.3x cheaper for API usage (input + output tokens combined).
- Claude 3.5 Sonnet has a larger context window (200K vs 128K tokens).
- GPT-4o is faster at 105 tok/s vs 80 tok/s.
- Claude 3.5 Sonnet leads on SWE-bench coding (65.0% vs 38.8%).
| Feature | Claude 3.5 Sonnet | GPT-4o |
|---|---|---|
Intelligence Index Composite reasoning & knowledge score (0-100) | 50 | 41 |
Provider | Anthropic | 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 | $2.31 / 1M | $2.38 / 1M |
Context Window Maximum input + output tokens | 200K tokens~300 A4 pages of text | 128K tokens~192 A4 pages of text |
Max Output Tokens Per single request | 8K | 16K |
Throughput Speed Tokens generated per second | 80 tok/s | 105 tok/s |
SWE-bench Verified Real-world software engineering | 65% | 38.8% |
GPQA Diamond Graduate-level reasoning | 59.4% | 53.6% |
Cached Input Price Prompt caching discount per 1M tokens | $0.30 / 1M | $1.25 / 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.
Claude 3.5 Sonnet · Strengths & Key Advantages
- Finestra di contesto da 200K con capacità massima di output fino a 8K token (SWE-bench Verified 65% · GPQA Diamond 59.4%)
- Throughput elevato di 80 token/secondo con latenza al primo token (TTFT) di soli 480 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 | Claude 3.5 Sonnet | 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 | 0K | 0K |
Specifiche Tecniche
Architecture, release timeline, capabilities, and modalities.
| Feature | Claude 3.5 Sonnet | GPT-4o |
|---|---|---|
| Official API Model ID (SDK) | claude-3-5-sonnet-20240601 | gpt-4o |
| API Protocol | Anthropic Messages API + AWS Bedrock + Vertex AI | OpenAI Responses API & Chat Completions v1 |
| Release Date | 2024-06 | 2024-05 |
| Knowledge Cutoff | April 2024 | October 2023 |
| Architecture | Next-Gen Multimodal Hybrid Transformer | Omni-Multimodal Dense |
| Parameters | Confidential | Confidential |
| Enterprise Rate Limits (RPM / TPM) | 4,000 – 10,000 RPM (Tier 4 + Priority Tier) · 800,000 – 2,000,000 TPM | 10,000 – 30,000 RPM (Tier 5 Enterprise) · 800,000 – 2,000,000 TPM |
| Long-Context Tier (>128K/200K) | Standard rate up to 200K tokens; 2x input/output tier above 200K tokens | Flat rate ($2.5/1M in) across full 128K window |
| Prompt Cache Policy & TTL | $0.3/1M cached read (90% off); 5-min default & 1-hour extended TTL | Automatic prefix caching at $1.25/1M (no extra cache-write fee) |
| Computer Use / GUI Agent | Supported (Screen coordinate grounding, browser & desktop GUI action loops) | 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 | Native Web Search Citations + Code Execution Tool + MCP Connectors | Native Web Search tool + Hosted Code Interpreter & File Search RAG |
| Official Fine-Tuning Support | Custom Model Tuning via Amazon Bedrock & Prompt 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 | Anthropic RSP ASL-2 / ASL-3 Constitutional Safety Evaluated | 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 |
Claude 3.5 Sonnet vs GPT-4o: Risposte Rapide (FAQ)
Which is more intelligent, Claude 3.5 Sonnet or GPT-4o?
Claude 3.5 Sonnet is more intelligent. It scores 50 compared with 41 on the composite Intelligence Index.
Which model is faster?
GPT-4o is faster, generating 105 tokens per second compared with 80 tokens per second.
Which model is cheaper to run?
Claude 3.5 Sonnet is cheaper at $2.31 per 1M tokens blended, compared with $2.38 (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 0.48s.
Which model has a larger context window?
Claude 3.5 Sonnet has a larger context window, supporting 200K tokens compared with 128K tokens.
Verdetto
Sia Claude 3.5 Sonnet (Ideale per l’ingegneria del software autonoma, il refactoring multi-file e il debug avanzato, 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: Claude 3.5 Sonnet guida nei benchmark di ragionamento e programmazione, GPT-4o garantisce una generazione più rapida e Claude 3.5 Sonnet offre il miglior rapporto qualità-prezzo per carichi API elevati.
Domande Frequenti (FAQ)
Quale modello è migliore per coding e ragionamento, Claude 3.5 Sonnet o GPT-4o?+
Nell’indice di intelligenza composito e nei benchmark di programmazione prevale Claude 3.5 Sonnet. Consulta i punteggi SWE-bench e GPQA qui sopra per tutti i dettagli.
Qual è la differenza di prezzo API tra Claude 3.5 Sonnet e GPT-4o?+
Claude 3.5 Sonnet costa $3.00 / $15.00 per milione di token di input/output, mentre GPT-4o costa $2.50 / $10.00. Nel costo combinato, Claude 3.5 Sonnet risulta più economico.
Quale modello ha la finestra di contesto più ampia e la velocità maggiore?+
Claude 3.5 Sonnet supporta 200K token di contesto contro 128K token di GPT-4o, mentre GPT-4o 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
- Claude 3.5 Sonnet vs Claude 3 Opus: Confronto Benchmark, Prezzi API e Velocità (2026)Confronta
- Claude 3.7 Sonnet vs GPT-4o: Confronto Benchmark, Prezzi API e Velocità (2026)Confronta
- DeepSeek V3 vs GPT-4o: Confronto Benchmark, Prezzi API e Velocità (2026)Confronta
- GPT-4o vs Gemini 1.5 Pro: Confronto Benchmark, Prezzi API e Velocità (2026)Confronta
- GPT-4o vs GPT-4 Turbo: Confronto Benchmark, Prezzi API e Velocità (2026)Confronta
- Grok 2 vs GPT-4o: 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 Anthropic e OpenAI, schede di sistema e benchmark indipendenti (2026).