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Head-to-Head Model Comparison

Claude Sonnet 4 vs Claude 3.7 Sonnet

Benchmarks, API Token Pricing, Context Window & Speed Comparison

Verificato dal team di ricerca di GetInfoUsUltima verifica: October 2026Politica editoriale
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AI CompareAI BenchmarkToken PricingModel CostModel SpecsSWE-bench CodingModel VersusWhich AI ModelLLM Speed & LatencyReasoning ModelsExtended ThinkingPrompt Caching ROI
Claude Sonnet 4 vs Claude 3.7 Sonnet: Benchmarks, Pricing & Speed Comparison

Claude Sonnet 4 di Anthropic e Claude 3.7 Sonnet di Anthropic sono due modelli di IA di riferimento. Claude Sonnet 4 offre una finestra di contesto di 200K 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.

Confronto Diretto (VS)

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Anthropic

Claude Sonnet 4

IA Agentica e Strumenti Autonomi

Claude Sonnet 4 di Anthropic è un modello di IA progettato per i workflow agentici autonomi, il tool calling e l’automazione multi-step, con finestra di contesto da 200K, velocità di 85 token/s, indice di intelligenza di 58/100 e tariffa di

Intelligence Index58 / 100
Input Token:

$3.00 / 1M

Output Token:

$15.00 / 1M

Context Window:

200K tokens

SWE-bench Verified:

72.7%

Anthropic

Claude 3.7 Sonnet

Leader in Programmazione e Codice

Claude 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

Intelligence Index48 / 100
Input Token:

$3.00 / 1M

Output Token:

$15.00 / 1M

Context Window:

200K tokens

SWE-bench Verified:

70.3%

Differenze Chiave a Colpo d’Occhio

  • Both models cost the same under this workload — choose on capability, not price.
  • Claude Sonnet 4 is faster at 85 tok/s vs 72 tok/s.
  • Claude Sonnet 4 leads on SWE-bench coding (72.7% vs 70.3%).
Need definitions for token pricing, context, or benchmarks?Explore AI Glossary →
FeatureClaude Sonnet 4Claude 3.7 Sonnet
Intelligence Index
Composite reasoning & knowledge score (0-100)
5848
Provider
AnthropicAnthropic
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
$2.31 / 1M$2.31 / 1M
Context Window
Maximum input + output tokens
200K tokens~300 A4 pages of text200K tokens~300 A4 pages of text
Max Output Tokens
Per single request
64K64K
Throughput Speed
Tokens generated per second
85 tok/s72 tok/s
SWE-bench Verified
Real-world software engineering
72.7%70.3%
GPQA Diamond
Graduate-level reasoning
71.2%65%
Cached Input Price
Prompt caching discount per 1M tokens
$0.30 / 1M$0.30 / 1M

Chi vince in ogni categoria?

At-a-glance decision framework
Coding
Claude Sonnet 4
+2.4% SWE-bench lead
Cost
Tied
Identical monthly runtime cost
Speed
Claude Sonnet 4
+18% faster generation
Context
Tied
200K tokens window

Punteggi Benchmark Verificati

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

Claude Sonnet 4Claude 3.7 Sonnet
SWE-bench Verified (Autonomous Coding)

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

72.7%vs70.3%
GPQA Diamond (Doctorate-Level Science & Math)

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

71.2%vs65%
MMLU-Pro (Multi-task Language Understanding)

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

84.5%vs78.2%
LMSYS Chatbot Arena Elo

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

1362ptsvs1335pts
Humanity's Last Exam (Frontier Expert Knowledge)

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

N/Avs8.9%
Terminal-Bench (Agentic Coding & Terminal Use)

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

42.1%vs35.2%
SciCode (Scientific Computing)

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

N/Avs40.1%
LiveCodeBench (Competitive Coding)

Contamination-free competitive programming problems collected continuously over time.

N/Avs64.8%
AIME (Advanced Math Competition)

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

N/Avs61.3%
Long-Context Reasoning

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

N/Avs71.5%
Generation Speed (Throughput)

Tokens emitted per second during active generation streaming.

85 tok/s vs72 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
Claude Sonnet 40.52s
Claude 3.7 Sonnet0.52s
Est. End-to-End Response (500 tokens)TTFT + generation time
Claude Sonnet 46.40s
Claude 3.7 Sonnet7.46s

Simulatore Interattivo dei Costi Token

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)
Claude Sonnet 4 Monthly API Bill
$18.45 / month
$3/1M in · $15/1M out
Claude 3.7 Sonnet Monthly API Bill
$18.45 / month
$3/1M in · $15/1M out
These models cost the same under this workload — no savings either way.Break-even

Claude Sonnet 4 · Strengths & Key Advantages

  • Finestra di contesto da 200K con capacità massima di output fino a 64K token (SWE-bench Verified 72.7% · GPQA Diamond 71.2%)
  • Throughput elevato di 85 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

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.

MetricClaude Sonnet 4Claude 3.7 Sonnet
Cost per Task
Estimated USD to finish one task
$3.29$1.42
Output Tokens / Task
Tokens generated per task
72K41K
Reasoning Tokens / Task
Thinking tokens burned per task
37K22K

Specifiche Tecniche

Architecture, release timeline, capabilities, and modalities.

FeatureClaude Sonnet 4Claude 3.7 Sonnet
Official API Model ID (SDK)claude-sonnet-4-20250501claude-3-7-sonnet-20250201
API ProtocolAnthropic Messages API + AWS Bedrock + Vertex AIAnthropic Messages API + AWS Bedrock + Vertex AI
Release Date2025-052025-02
Knowledge CutoffMarch 2025November 2024
ArchitectureHybrid Multimodal Reasoning TransformerHybrid Reasoning MoE
ParametersConfidentialConfidential
Enterprise Rate Limits (RPM / TPM)4,000 – 10,000 RPM (Tier 4 + Priority Tier) · 800,000 – 2,000,000 TPM4,000 – 10,000 RPM (Tier 4 + Priority Tier) · 800,000 – 2,000,000 TPM
Long-Context Tier (>128K/200K)Standard rate up to 200K tokens; 2x input/output tier above 200K tokensStandard rate up to 200K tokens; 2x input/output tier above 200K tokens
Prompt Cache Policy & TTL$0.3/1M cached read (90% off); 5-min default & 1-hour extended TTL$0.3/1M cached read (90% off); 5-min default & 1-hour extended TTL
Computer Use / GUI AgentSupported (Screen coordinate grounding, browser & desktop GUI action loops)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 & SandboxNative Web Search Citations + Code Execution Tool + MCP ConnectorsNative Web Search Citations + Code Execution Tool + MCP Connectors
Official Fine-Tuning SupportCustom Model Tuning via Amazon Bedrock & Prompt DistillationCustom Model Tuning via Amazon Bedrock & Prompt Distillation
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 ClassificationAnthropic RSP ASL-2 / ASL-3 Constitutional Safety EvaluatedAnthropic 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 TierSOC2 Type II · GDPR · Zero Data Retention (ZDR) & HIPAA BAA Available on Enterprise Tier
Input Modalitiestext, visiontext, vision
Output Modalitiestexttext

Claude Sonnet 4 vs Claude 3.7 Sonnet: Risposte Rapide (FAQ)

Which is more intelligent, Claude Sonnet 4 or Claude 3.7 Sonnet?

Claude Sonnet 4 is more intelligent. It scores 58 compared with 48 on the composite Intelligence Index.

Which model is faster?

Claude Sonnet 4 is faster, generating 85 tokens per second compared with 72 tokens per second.

Verdetto

Sia Claude Sonnet 4 (Ideale per i workflow agentici autonomi, il tool calling e l’automazione multi-step, 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: Claude Sonnet 4 guida nei benchmark di ragionamento e programmazione, Claude Sonnet 4 garantisce una generazione più rapida e Claude Sonnet 4 offre il miglior rapporto qualità-prezzo per carichi API elevati.

Domande Frequenti (FAQ)

Quale modello è migliore per coding e ragionamento, Claude Sonnet 4 o Claude 3.7 Sonnet?+

Nell’indice di intelligenza composito e nei benchmark di programmazione prevale Claude Sonnet 4. Consulta i punteggi SWE-bench e GPQA qui sopra per tutti i dettagli.

Qual è la differenza di prezzo API tra Claude Sonnet 4 e Claude 3.7 Sonnet?+

Claude Sonnet 4 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 Sonnet 4 risulta più economico.

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

Claude Sonnet 4 supporta 200K token di contesto contro 200K token di Claude 3.7 Sonnet, mentre Claude Sonnet 4 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 & PricingContext WindowAI BenchmarksReasoning ModelsTool CallingModel Context Protocol (MCP)

Related reading

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 Anthropic, schede di sistema e benchmark indipendenti (2026).