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Utilizabil 24 ore după înregistrare, până la 5 rulări pe zi și maximum 2 credite pe rulare. Alte metode de conectare încep fără credite. Suficient pentru 16 rulări ale acestui model.
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Despre Claude Haiku 4.5
Pe scurtDin 23 septembrie 2026
Claude Haiku 4.5 este un model de Anthropic din categoria Multimodal. Pe Railwail, Claude Haiku 4.5 costă 1,20 USD per 1M tokeni de intrare și 6,00 USD per 1M tokeni de ieșire. Fereastra de context conține 200.000 token-uri, iar un răspuns poate fi lung de până la 64.000 token-uri.
Claude Haiku 4.5 brings Sonnet-class reliability to the cost-and-latency tier. 200K context, full vision input, native tool use and extended thinking on demand. Designed for high-volume agents, real-time chat, classification, simple coding subagents, and consumer applications where p50 latency matters more than peak reasoning.
Fundal
Despre Anthropic
Fondat 2021 · San Francisco, USA
Anthropic was founded in 2021 by Dario and Daniela Amodei. The Claude model family launched in March 2023 with Haiku as the lightweight tier optimized for low latency and cost. Successive Haiku generations have steadily closed the gap to Sonnet: Haiku 3 (March 2024), Haiku 3.5 (October 2024), Haiku 4 (May 2025) and Haiku 4.5 (late 2025/early 2026). Anthropic is structured as a Public Benefit Corporation focused on AI safety, with total funding exceeding $20 billion and a 2026 valuation above $150 billion.
Claude Haiku 4.5 is the fastest and cheapest model in the Claude 4.x family. Architecturally it is a smaller decoder-only Transformer distilled from the Sonnet/Opus 4 training stack, optimized aggressively for inference latency and throughput while retaining the full Claude feature set (vision, extended thinking, tool use). It was trained on the same multi-trillion-token curated corpus as its larger siblings with a knowledge cutoff in early 2026. Post-training combined RLHF, Constitutional AI, RLAIF and distillation from larger teacher models. Despite its small size, Haiku 4.5 supports the same 200K context window and tool-use API as Sonnet 4.6 and Opus 4.7, making it a drop-in cheaper option for high-concurrency workloads.
Parametri
Undisclosed (estimated tens of billions of parameters)
Context
200.000 tokeni
Capabilități
Lowest p50 latency in the Claude 4.x family
200K token context window matching the larger Claude models
Vision input for images, PDFs and screenshots
Native tool use with parallel tool calling
Optional extended thinking mode for harder reasoning tasks
Sonnet-class reliability at one-third the cost
Strong instruction following and structured JSON output
Constitutional-AI alignment with low refusal rate
Available via Anthropic API, Bedrock and Vertex AI
Pretrained on the same curated multi-trillion-token mixture used by Sonnet and Opus 4.x. Post-training includes distillation from larger Anthropic models alongside RLHF, Constitutional AI and RLAIF. Knowledge cutoff in early 2026.
Licență: Proprietary commercial license via Anthropic API, Amazon Bedrock and Google Vertex AI.
Teste de siguranță: Same Responsible Scaling Policy ASL-3 safeguards as Sonnet and Opus, with constitutional classifiers and third-party evaluations.
Limitări cunoscute
Below Sonnet 4.6 on hard reasoning and agentic coding benchmarks
No native audio or video input
Knowledge cutoff in early 2026
Less depth on niche or long-tail topics than larger models
curl https://railwail.com/api/v1/chat/completions \
-H "Authorization: Bearer $RAILWAIL_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"model": "claude-haiku-4-5",
"messages": [
{
"role": "user",
"content": "Explain what a vector database is in two sentences."
}
],
"max_tokens": 1024
}'
import os
from openai import OpenAI
client = OpenAI(
api_key=os.environ["RAILWAIL_API_KEY"],
base_url="https://railwail.com/api/v1",
)
completion = client.chat.completions.create(
model="claude-haiku-4-5",
messages=[
{
"role": "user",
"content": "Explain what a vector database is in two sentences.",
},
],
max_tokens=1024,
)
print(completion.choices[0].message.content)
import OpenAI from "openai";
const client = new OpenAI({
apiKey: process.env.RAILWAIL_API_KEY,
baseURL: "https://railwail.com/api/v1",
});
const completion = await client.chat.completions.create({
model: "claude-haiku-4-5",
messages: [
{
role: "user",
content: "Explain what a vector database is in two sentences."
}
],
max_tokens: 1024
});
console.log(completion.choices[0].message.content);
// npm install railwail
import railwail from "railwail";
const rw = railwail(process.env.RAILWAIL_API_KEY);
const res = await rw.chat("claude-haiku-4-5", [
{ role: "user", content: "Explain what a vector database is in two sentences." },
], { max_tokens: 1024 });
console.log(res.choices[0].message.content);
Claude Haiku 4.5 este un model de Anthropic din categoria Multimodal. Pe Railwail îl poți apela cu o cheie API prin Railwail API.
Cât costă Claude Haiku 4.5 pe Railwail?
Pe Railwail, Claude Haiku 4.5 costă 1,20 USD per 1M tokeni de intrare și 6,00 USD per 1M tokeni de ieșire. Ți se percepe taxa pentru ceea ce fiecare cerere folosește efectiv. Utilizarea se plătește din credite prepay; 1 credit egal cu 0,01 USD.
Care este fereastra de context a Claude Haiku 4.5?
Fereastra de context a Claude Haiku 4.5 conține 200.000 token-uri. Un răspuns poate fi lung de până la 64.000 token-uri.
Cât de rapid este Claude Haiku 4.5?
Nu sunt suficiente rulări măsurate ale Claude Haiku 4.5 pe Railwail încă pentru a indica un timp de rulare. Depinde de intrare, de setări și de sarcina la furnizor.
Este Claude Haiku 4.5 mai bun decât BLIP?
Depinde de sarcină. Claude Haiku 4.5 (Anthropic) și BLIP (Salesforce) sunt ambele modele din categoria Multimodal. Pagina de comparație arată prețurile și specificațiile lor una lângă alta.
Da. Claude Haiku 4.5 acceptă imagini ca intrare, pe lângă text.
Cum folosesc Claude Haiku 4.5 prin API?
Creează o cheie Railwail API și trimite cererea cu ID-ul modelului claude-haiku-4-5. Exemple de cod pentru curl, Python și JavaScript sunt în secțiunea API a acestei pagini.
