nousresearch/hermes-4-405b
131,072 context · $1.00/M input tokens · $3.00/M output tokens
Hermes 4 is a large-scale reasoning model built on Meta-Llama-3.1-405B and released by Nous Research. It introduces a hybrid reasoning mode, where the model can choose to deliberate internally with...
Pagamento por uso
Sem custo inicial, pague apenas pelo que usar
Use os exemplos de código abaixo para integrar com nossa API:
from openai import OpenAI
client = OpenAI(
api_key="YOUR_API_KEY",
base_url="https://llm.wavespeed.ai/v1"
)
response = client.chat.completions.create(
model="nousresearch/hermes-4-405b",
messages=[
{"role": "user", "content": "Hello!"}
]
)
print(response.choices[0].message.content)Hermes 4 is a large-scale reasoning model built on Meta-Llama-3
Hermes 4 is a large-scale reasoning model built on Meta-Llama-3.1-405B and released by Nous Research. It introduces a hybrid reasoning mode, where the model can choose to deliberate internally with <think>...</think> traces or respond directly, offering flexibility between speed and depth. Users can control the reasoning behaviour with the reasoning enabled boolean. Learn more in our docs
The model is instruction-tuned with an expanded post-training corpus (~60B tokens) emphasizing reasoning traces, improving performance in math, code, STEM, and logical reasoning, while retaining broad assistant utility. It also supports structured outputs, including JSON mode, schema adherence, function calling, and tool use. Hermes 4 is trained for steerability, lower refusal rates, and alignment toward neutral, user-directed behavior.
| Specification | Value |
|---|---|
| Provider | Nousresearch |
| Model Type | Large Language Model (LLM) |
| Architecture | N/A |
| Context Window | 131072 tokens |
| Max Output | tokens |
| Input | Text |
| Output | Text |
| Vision | Supported |
| Function Calling | Supported |
| Token Type | Cost per Million Tokens |
|---|---|
| Input | $1.1 |
| Output | $3.3 |
Base URL: https://llm.wavespeed.ai/v1 API Endpoint: chat/completions Model ID: nousresearch/hermes-4-405b
from openai import OpenAI
client = OpenAI(
api_key="YOUR_API_KEY",
base_url="https://llm.wavespeed.ai/v1"
)
response = client.chat.completions.create(
model="nousresearch/hermes-4-405b",
messages=[
{"role": "user", "content": "Hello!"}
]
)
print(response.choices[0].message.content)curl https://llm.wavespeed.ai/v1/chat/completions \
-H "Content-Type: application/json" \
-H "Authorization: Bearer YOUR_API_KEY" \
-d '{
"model": "nousresearch/hermes-4-405b",
"messages": [{"role": "user", "content": "Hello!"}]
}'nousresearch/hermes-4-405b
Hermes 4 is a large-scale reasoning model built on Meta-Llama-3.1-405B and released by Nous Research. It introduces a hybrid reasoning mode, where the model can choose to deliberate internally with...
Entrada
$1 /M
Saída
$3 /M
Contexto
131K
Acesse Hermes 4 405b através da nossa API unificada — compatível com OpenAI, sem inicializações a frio, preços transparentes.
Preços no WaveSpeedAI: $1.00 por milhão de tokens de entrada e $3.00 por milhão de tokens de saída. Prompt caching e batch processing são cobrados separadamente e reduzem o custo efetivo em cargas longas e repetitivas.
Hermes 4 405b suporta até 131K tokens de contexto e até — tokens de saída por requisição.
Sim. O WaveSpeedAI expõe o Hermes 4 405b através de um endpoint compatível com OpenAI em https://llm.wavespeed.ai/v1. Aponte o SDK oficial da OpenAI para esta base URL com sua chave API do WaveSpeedAI — sem outras alterações no código.
Entre no WaveSpeedAI, crie uma chave API em Access Keys, então envie uma requisição para https://llm.wavespeed.ai/v1/chat/completions com o model id mostrado acima. Contas novas recebem créditos grátis para avaliar o Hermes 4 405b.