
Qwen3.6 35B A3B is a 256-expert mixture-of-experts reasoning model with 128K context, function tools, and strict structured JSON output.
Qwen3.6 35B A3B is a 256-expert mixture-of-experts reasoning model with 128K context, function tools, and strict structured JSON output.
Text-only. This build does not accept image or video input, unlike the base Qwen3.6 35B A3B. Weights Served from the 2-bit eschamoe W2 build published by Escha Labs (eschalabs.com) as EschaLabs/Qwen3.6-35B-A3B-Escha-W2 on Hugging Face, under Apache-2.0. The experts are quantized to 2 bits, mixed per projection (gate_up_proj at 2-bit and down_proj at 3-bit), the dense layers are int8, and the KV cache is FP16. Escha Labs publishes the quality comparison against an FP8 baseline of the same model: parity or better on math, graduate science, tool use and long context, about 2 percent lower on broad knowledge, and about 7 percent lower on long-horizon code generation, which is the one clear gap. See the model card for the full benchmark table and protocol. Behavior Supports streaming, function tools, structured JSON output including strict schemas, and thinking mode on by default. Set enable_thinking=false for direct answers. With thinking on, the reasoning arrives in reasoning_content and the answer in content, so read both. A low max_tokens with thinking on can be spent entirely on reasoning, so allow room for the answer. Caching Automatic prefix cache reads are billed at the cached-input rate when reported. Explicit cache controls are not supported. Cancelling a streaming request mid-generation bills only the tokens produced up to that point.
Também conhecido como Alibaba Cloud Qwen3.6 35B A3B, Qwen3.6-35B-A3B, qwen3-6-35b-a3b
qwen3-6-35b-a3b/v1/chat/completionsPOST/v1/responsesPOST/v1/messagesPOST/v1/completionsPOST/v1beta/models/qwen3-6-35b-a3b:generateContentqwen3.6-35b-a3bqwen/qwen3.6-35b-a3bEschaLabs/Qwen3.6-35B-A3B-Escha-W2Tarifas pay-as-you-go ao vivo do catálogo EmpirioLabs. Você paga só pelo que usa, sem mínimo mensal.
Qwen3.6 35B A3B atende a API Chat Completions compatível com OpenAI. Aponte qualquer SDK OpenAI para https://api.empiriolabs.ai/v1 com sua chave de API EmpirioLabs e use o id de modelo qwen3-6-35b-a3b. Obtenha uma chave de API no painel EmpirioLabs.
curl https://api.empiriolabs.ai/v1/chat/completions \
-H "Authorization: Bearer $EMPIRIOLABS_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"model": "qwen3-6-35b-a3b",
"messages": [
{"role": "user", "content": "Write a haiku about the ocean."}
]
}'from openai import OpenAI
client = OpenAI(
base_url="https://api.empiriolabs.ai/v1",
api_key="YOUR_EMPIRIOLABS_API_KEY",
)
response = client.chat.completions.create(
model="qwen3-6-35b-a3b",
messages=[{"role": "user", "content": "Write a haiku about the ocean."}],
)
print(response.choices[0].message.content)Parâmetros de requisição suportados pela API Qwen3.6 35B A3B na EmpirioLabs. Os padrões valem quando um campo é omitido.
| Parâmetro | Tipo | Padrão | Intervalo / valores | Descrição |
|---|---|---|---|---|
| temperature | number | 0.7 | 0 a 2 | Sampling temperature. 0 is deterministic and 2 is maximum randomness. |
| top_p | number | 0.95 | 0 a 1 | Nucleus sampling probability mass. Lower values make outputs more focused. |
| max_tokens | number | 4096 | 1 a 16384 | Maximum output tokens. With thinking on, leave room for the answer as well as the reasoning. |
| stop | string | - | - | Up to 4 strings where the model will stop generating further tokens. |
| enable_thinking | boolean | true | - | Enable the model reasoning channel before final output. Reasoning is returned in reasoning_content and bills as output tokens. |
| reasoning_effort | enum | medium | none, low, medium, high, max | Reasoning effort. none disables thinking. Any other value enables it. |
| top_k | number | 20 | 1 a 200 | Limit sampling to the top K candidate tokens. |
| min_p | number | 0 | 0 a 1 | Minimum probability threshold for token sampling. |
| presence_penalty | number | 0 | -2 a 2 | Penalize tokens that have already appeared, increasing topic diversity. |
| frequency_penalty | number | 0 | -2 a 2 | Penalize tokens in proportion to how often they have appeared. |
| seed | number | - | 0 a 2147483647 | Best-effort determinism. Output is not bit-reproducible across requests because batch composition changes accumulation order. |
| response_format | enum | - | text, json_object, json_schema | Structured output. json_object returns valid JSON. json_schema enforces your schema exactly. |
| web_search_linkup | boolean | false | - | Optional web search powered by Linkup. When enabled, recent web sources are retrieved using your latest user message as the query and provided to the model as additional context. Adds $0.013 per call when invoked on top of the model's normal token cost. Disabled by default. |
Text-only. This build does not accept image or video input, unlike the base Qwen3.6 35B A3B.
Served from the 2-bit eschamoe W2 build published by Escha Labs (eschalabs.com) as EschaLabs/Qwen3.6-35B-A3B-Escha-W2 on Hugging Face, under Apache-2.0. The experts are quantized to 2 bits, mixed per projection (gate_up_proj at 2-bit and down_proj at 3-bit), the dense layers are int8, and the KV cache is FP16. Escha Labs publishes the quality comparison against an FP8 baseline of the same model: parity or better on math, graduate science, tool use and long context, about 2 percent lower on broad knowledge, and about 7 percent lower on long-horizon code generation, which is the one clear gap. See the model card for the full benchmark table and protocol.
Supports streaming, function tools, structured JSON output including strict schemas, and thinking mode on by default. Set enable_thinking=false for direct answers. With thinking on, the reasoning arrives in reasoning_content and the answer in content, so read both. A low max_tokens with thinking on can be spent entirely on reasoning, so allow room for the answer.
Automatic prefix cache reads are billed at the cached-input rate when reported. Explicit cache controls are not supported. Cancelling a streaming request mid-generation bills only the tokens produced up to that point.
Na EmpirioLabs, Qwen3.6 35B A3B é cobrado por uso. A tabela de tarifas ao vivo desta página sempre corresponde ao que a API cobra.
Qwen3.6 35B A3B suporta uma janela de contexto de 128K tokens com até 16.384 tokens de saída por resposta.
Sim. Qwen3.6 35B A3B atende a API Chat Completions compatível com OpenAI, então SDKs OpenAI existentes funcionam apontando base_url para https://api.empiriolabs.ai/v1 e definindo o id de modelo qwen3-6-35b-a3b.
Sim. O playground da EmpirioLabs executa Qwen3.6 35B A3B no navegador com os mesmos parâmetros que a API expõe, para você testar prompts antes de escrever código.
Crie uma conta EmpirioLabs e gere uma chave em API Keys no painel. A cobrança usa créditos pay-as-you-go, então você paga apenas pelas requisições que faz.
Confira nossos preços ou entre em contato se quiser que seu próprio modelo seja implementado em nossa pilha.