
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.
Auch bekannt als 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-W2Live Pay-as-you-go-Preise aus dem EmpirioLabs-Katalog. Du zahlst nur für das, was du nutzt, ohne monatliches Minimum.
Qwen3.6 35B A3B bedient die OpenAI-kompatible Chat Completions API. Richte ein beliebiges OpenAI SDK mit deinem EmpirioLabs API-Schlüssel auf https://api.empiriolabs.ai/v1 und verwende die Modell-ID qwen3-6-35b-a3b. Hol dir einen API-Schlüssel im EmpirioLabs Dashboard.
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)Request-Parameter, die die Qwen3.6 35B A3B API auf EmpirioLabs unterstützt. Standardwerte gelten, wenn ein Feld weggelassen wird.
| Parameter | Typ | Standard | Bereich / Werte | Beschreibung |
|---|---|---|---|---|
| temperature | number | 0.7 | 0 bis 2 | Sampling temperature. 0 is deterministic and 2 is maximum randomness. |
| top_p | number | 0.95 | 0 bis 1 | Nucleus sampling probability mass. Lower values make outputs more focused. |
| max_tokens | number | 4096 | 1 bis 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 bis 200 | Limit sampling to the top K candidate tokens. |
| min_p | number | 0 | 0 bis 1 | Minimum probability threshold for token sampling. |
| presence_penalty | number | 0 | -2 bis 2 | Penalize tokens that have already appeared, increasing topic diversity. |
| frequency_penalty | number | 0 | -2 bis 2 | Penalize tokens in proportion to how often they have appeared. |
| seed | number | - | 0 bis 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.
Auf EmpirioLabs wird Qwen3.6 35B A3B nach Verbrauch abgerechnet. Die Live-Preistabelle auf dieser Seite entspricht immer dem, was die API berechnet.
Qwen3.6 35B A3B unterstützt ein Kontextfenster von 128K Token mit bis zu 16.384 Ausgabe-Token pro Antwort.
Ja. Qwen3.6 35B A3B bedient die OpenAI-kompatible Chat Completions API. Bestehende OpenAI SDKs funktionieren, indem du base_url auf https://api.empiriolabs.ai/v1 setzt und als Modell-ID qwen3-6-35b-a3b verwendest.
Ja. Der EmpirioLabs Playground führt Qwen3.6 35B A3B im Browser mit denselben Parametern aus, die die API bietet. So kannst du Prompts testen, bevor du Code schreibst.
Erstelle ein EmpirioLabs-Konto und generiere dann einen Schlüssel unter API Keys im Dashboard. Die Abrechnung erfolgt über Pay-as-you-go-Guthaben, du zahlst also nur für deine Requests.
Schauen Sie sich unsere Preise an oder kontaktieren Sie uns, wenn Sie Ihr eigenes Modell auf unserem Stack implementieren möchten.