1M Token Context
Process massive documents and codebases with high recall and efficient memory management.
Claude Sonnet 4 (Build 20250514)
Claude Sonnet 4 API offers 1M token context and advanced reasoning. While it excels at coding and context management, users note its concise style and penchant for em-dashes. Perfect for technical tasks needing Opus-level depth and speed.
Esempi di utilizzo dell’API
curl --request POST "https://gptproto.com/v1/chat/completions" \
--header "Authorization: Bearer $GPTPROTO_API_KEY" \
--header "Content-Type: application/json" \
--data '{
"model": "claude-sonnet-4-20250514",
"messages": [
{
"role": "user",
"content": "Hello"
}
]
}'Prezzi Claude Sonnet 4 20250514
Chat, agenti di coding e lavoro sui documenti. Prezzi per 1M di token: input, input memorizzato nella cache e output vengono fatturati separatamente. GPTProto costa il 10% in meno rispetto alle tariffe ufficiali.
| Scenario | Listino ufficiale Claude | OpenRouter | GPTProto | Risparmi al mese |
|---|---|---|---|---|
| Personale10M token/mese (4.8M nella cache) | $41.04 | $43.30 | $36.94 | −$4.10≈ $49.25 / anno |
| Team100M token/mese (48M nella cache) | $410.40 | $432.97 | $369.36 | −$41.04≈ $492.48 / anno |
| Aziendale500M token/mese (240M nella cache) | $2052.00 | $2164.86 | $1846.80 | −$205.20≈ $2462.40 / anno |
Risparmia $0.00 / mese
Risparmio annuale ≈ $0.00 · pagamento a consumo
Modelli correlati
Tutti i modelli
Claude Sonnet 4 (Build 20250514)Attuale
Claude · 200K context · $2.7/M input · $13.5/M output
Bytedance · 262K context · $0.0971/M input · $0.9714/M output
Bytedance · 262K context · $0.0971/M input · $0.9714/M output
Modello
Prezzo: GPTProto
vs ufficiale
vs OpenRouter
Contesto
Stabilità
Claude Sonnet 4 (Build 20250514)Attuale
Claude
$2.70 / $13.50per 1M di token
-10%
-15%
200K
Claude Sonnet 4 API Advanced Features
Discover the technical capabilities that set the Claude Sonnet 4 API apart, from its massive context window to its integrated tools for web searching and code execution.
Adaptive Thinking
Control reasoning depth with the effort parameter to balance speed and intelligence.
Code Execution
Run Python code in a sandboxed environment for advanced data analysis and math.
Prompt Caching
Reduce latency and costs by caching frequent background data and recurring instructions.
Claude Sonnet 4 API: Common User Questions
Get expert answers on Claude Sonnet 4 API performance, writing style, and technical capabilities based on real developer experiences and official documentation.
Is Claude Sonnet 4 API good for coding tasks?
Yes, many developers find Claude Sonnet 4 API highly effective for coding, with some calling its code generation the best in its class. However, feedback is mixed; some users feel it occasionally takes shortcuts or skips instructions. To get the best results, break complex coding tasks into atomic, verifiable steps. This helps Claude maintain accuracy and ensures every line of code meets your specific technical requirements.
How does Claude handle long context windows?
This Claude API supports a context window of up to 1 million tokens. This makes it exceptionally strong at remembering details across long conversations or analyzing massive codebases. Its context management features, like compaction and automatic prompt caching, help keep long-running sessions efficient. It performs similarly to the high-end Opus model for many deep-reasoning use cases involving large documents and data sets.
Why does the Claude Sonnet 4 API use em-dashes?
Some users have observed that newer Claude models tend to overuse em-dashes and colons, which can sometimes make the prose feel unnatural or AI-written. If you find this distracting, you can mitigate the habit by using custom instructions. Simply tell the model in your prompt to avoid specific punctuation marks, and it will generally follow those stylistic constraints to produce more human-like creative writing and professional prose.
Can I use Claude Sonnet 4 API for batch processing?
Absolutely. The Claude API offers asynchronous batch processing for large volumes of requests. This is a cost-effective choice for tasks that do not require immediate real-time responses, as Batch API calls typically cost 50% less than standard requests. It is ideal for large-scale data classification, content moderation, or any workflow where you need to process a high volume of tokens while managing your budget effectively.
What is adaptive thinking in Claude Sonnet 4?
Adaptive thinking allows Claude to dynamically decide how much reasoning effort is needed for a specific prompt. By using the effort parameter, you can control whether the model provides a quick response or deep, extended thinking. This transparency into the model's step-by-step thought process is particularly useful for complex logic problems, investment theory tasks, or nuanced creative writing where depth is essential for success.
Does the API support structured JSON outputs?
Yes, the Claude Sonnet 4 API guarantees schema conformance through structured outputs. You can choose between two main approaches: direct JSON outputs for data-heavy responses or strict tool use for validated inputs. This ensures that the model's responses integrate seamlessly into your existing software infrastructure, making it a reliable choice for developers building agentic workflows or automated data pipelines.
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