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10 bezmaksas kredīti (0,10 $), reģistrējies ar Google
Pieejams 24 stundas pēc reģistrācijas, līdz 5 palaišanas gadījumi dienā un maksimāli 2 kredīti uz palaišanas gadījumu. Citas pierakstīšanās metodes sākas bez kredītiem. Pietiek 62 šī modeļa palaišanām.
02
Par GPT-5.4 Nano
ĪsumāUz 2026. gada 23. septembris
GPT-5.4 Nano ir OpenAI modelis kategorijā Multimodāls. Railwail platformā GPT-5.4 Nano maksā 0,24 $ par 1M ievades tokeniem un 1,50 $ par 1M izvades tokeniem. Konteksta logs satur 400 000 žetonus, un viena atbilde var būt līdz 32 000 žetonu gara.
GPT-5.4 nano is the lightest member of the GPT-5.4 family, released alongside Mini in March 2026. 400K context window, vision input, optimized for classification, data extraction, ranking and coding subagents that handle simpler supporting tasks. A major upgrade over GPT-5 nano, designed for the subagent era of agentic workflows where orchestrator models delegate to many cheap workers.
Fons
Par OpenAI
Dibināts 2015 · San Francisco, USA
OpenAI is the AI research lab founded in December 2015 by Sam Altman, Elon Musk, Greg Brockman, Ilya Sutskever and others. The company shipped GPT-1 through GPT-5 and the unified GPT-5.x line (2025-2026). GPT-5.4 nano was released alongside GPT-5.4 mini on March 17, 2026 as the smallest, cheapest variant of the GPT-5.4 generation, aimed at the 'subagent era' of agentic workflows. OpenAI is backed by Microsoft and other major investors with a 2026 valuation above $300 billion.
Unified Transformer (small, optimized for high-throughput subagent workloads)
GPT-5.4 nano is the lightest member of the GPT-5.4 family, released March 17, 2026 as OpenAI's smallest and cheapest reasoning-capable model. It is heavily distilled from larger GPT-5.4 teacher models and trained to excel at classification, extraction, ranking and coding subagent tasks. Architecturally it retains the unified GPT-5.4 design: native text + image input, integrated 'Thinking' tier on demand, and full tool-use API including parallel tool calls. The 400K context window is unusually large for a nano-class model and supports long-document subagent work. Post-training emphasized reliability on structured outputs, JSON schema adherence and function calling, since nano-class models are typically deployed in deterministic pipelines.
Integrated 'Thinking' tier for occasional harder tasks
Strong on classification, extraction, ranking and coding subagent tasks
Native tool use, function calling and parallel tool calls
Reliable structured JSON output and schema adherence
Edge-grade latency suitable for real-time pipelines
Major upgrade over GPT-5 nano on every measured benchmark
Available in ChatGPT (free tier) and the OpenAI API
Best for: classification, data extraction, ranking, coding subagents under an orchestrator.
Apmācība un licence
Heavily distilled from larger GPT-5.4 teacher models. Pretraining uses a multi-trillion-token mixture; post-training combines supervised fine-tuning, RLHF and RL against verifiable rewards with a strong emphasis on structured-output reliability. Knowledge cutoff approximately late 2025.
Licence: Proprietary commercial license via OpenAI API and Azure OpenAI.
Drošības pārbaudes: Evaluated under OpenAI's Preparedness Framework with internal and external red-teaming.
Zināmi ierobežojumi
Below GPT-5.4 mini on hard reasoning and agentic coding benchmarks
Limited depth on niche or long-tail topics
No native audio or video input
Knowledge cutoff in late 2025
Thinking mode is available but slow relative to model size
curl https://railwail.com/api/v1/chat/completions \
-H "Authorization: Bearer $RAILWAIL_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"model": "gpt-5-4-nano",
"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="gpt-5-4-nano",
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: "gpt-5-4-nano",
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("gpt-5-4-nano", [
{ role: "user", content: "Explain what a vector database is in two sentences." },
], { max_tokens: 1024 });
console.log(res.choices[0].message.content);
GPT-5.4 Nano ir OpenAI izstrādāts modelis Multimodāls kategorijā. Railwail platformā varat to izsaukt ar API atslēgu, izmantojot Railwail API.
Cik maksā GPT-5.4 Nano Railwail?
Railwail platformā GPT-5.4 Nano maksā 0,24 $ par 1M ievades tokeniem un 1,50 $ par 1M izvades tokeniem. Jums tiek ņemta maksa par to, ko katra pieprasījuma izpilde faktiski izmanto. Izmantošana tiek apmaksāta no iepriekš nopirkto kredītu; 1 kredīts = 0,01 $.
Kāds ir GPT-5.4 Nano konteksta logs?
GPT-5.4 Nano konteksta logs satur 400 000 žetonus. Viena atbilde var būt līdz 32 000 žetonu gara.
Cik ātrs ir GPT-5.4 Nano?
Railwail platformā GPT-5.4 Nano vēl nav pietiekami daudz izmērītu izpilžu, lai norādītu izpildes laiku. Tas ir atkarīgs no ievades, iestatījumiem un sniedzēja slodzes.
Vai GPT-5.4 Nano ir labāks par BLIP?
Tas ir atkarīgs no uzdevuma. GPT-5.4 Nano (OpenAI) un BLIP (Salesforce) ir abi modeļi Multimodāls kategorijā. Salīdzināšanas lapā to cenas un specifikācijas ir parādītas blakus.
Jā. GPT-5.4 Nano pieņem attēlus kā ievadi papildus tekstam.
Kā es varu izmantot GPT-5.4 Nano caur API?
Izveidojiet Railwail API atslēgu un nosūtiet savu pieprasījumu ar modeļa ID gpt-5-4-nano. Koda piemēri curl, Python un JavaScript ir šīs lapas API sadaļā.
