> For clean Markdown of any page, append .md to the page URL. > For a complete documentation index, see https://docs.empiriolabs.ai/llms.txt. > For AI client integration (Claude Code, Cursor, etc.), connect to the MCP server at https://docs.empiriolabs.ai/_mcp/server. # Qwen3.6 35B A3B > 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](https://media.empiriolabs.ai/model-logos/qwen.png) [Alibaba Cloud](/providers/alibaba) · Text Generation `POST /v1/chat/completions` Qwen3.6 35B A3B is a 256-expert mixture-of-experts reasoning model with 128K context, function tools, and strict structured JSON output. ## At a glance | Field | Value | | ------------------- | ----------------------------------------------------------------------------------------------------------------------------------------------------- | | Model id | `qwen3-6-35b-a3b` | | Model release date | 2026-04-16 | | Input modalities | Text | | Output modalities | Text | | Context window | 128K | | Weight precision | eschamoe W2: 2-bit weights + INT8 dense + FP16 KV | | Max output tokens | 16,384 | | Features | reasoning, function_calling, json_mode, cache | | Native inference | Yes | | New | No | | Structured output | JSON Schema | | Supported endpoints | `POST /v1/chat/completions`, `POST /v1/responses`, `POST /v1/messages`, `POST /v1/completions`, `POST /v1beta/models/qwen3-6-35b-a3b:generateContent` | | Alternate model ids | `qwen3.6-35b-a3b`, `qwen/qwen3.6-35b-a3b`, `EschaLabs/Qwen3.6-35B-A3B-Escha-W2` | ## Pricing | Charge | Spec | Rate | | ------------------- | -------------------------- | ------------------ | | Input | per 1M prompt tokens | ~~\$0.248~~ \$0.07 | | Output | per 1M generated tokens | ~~\$1.485~~ \$0.42 | | Implicit cache read | per 1M cached input tokens | \$0.035 | | Web Search (Linkup) | per call when invoked | \$0.013 | ## Example request ```bash 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":"Hello"}]}' ``` ## Parameters | Parameter | Type | Required | Default | Description | | -------------------- | ------- | -------- | ---------- | ----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | | `temperature` | number | no | `0.7` | Sampling temperature. 0 is deterministic and higher values are more random. · Min: 0 | | `top_p` | number | no | `0.95` | Nucleus sampling probability mass. Lower values make outputs more focused. · Range: 0.01 – 1 | | `max_tokens` | number | no | `16384` | Maximum output tokens. · Range: 1 – 16384 | | `stop` | string | no | - | Up to 4 strings where the model will stop generating further tokens. | | `enable_thinking` | boolean | no | true | Enable reasoning before answering. | | `reasoning_effort` | enum | no | `"medium"` | Reasoning effort. none disables thinking. Any other value enables it. · Allowed: `none`, `low`, `medium`, `high`, `max` | | `top_k` | number | no | `20` | Limit sampling to the top K candidate tokens when supported. · Min: 1 | | `min_p` | number | no | `0` | Minimum probability threshold for token sampling. · Range: 0 – 1 | | `frequency_penalty` | number | no | `0` | Penalty based on how often a token has already appeared. · Range: -2 – 2 | | `presence_penalty` | number | no | `0` | Penalty for tokens that already appeared in the generated text. · Range: -2 – 2 | | `seed` | number | no | - | Optional random seed for reproducible sampling. · Range: 0 – 2147483647 | | `response_format` | enum | no | - | Constrain the output to valid JSON. Use JSON mode for any JSON object, or supply a JSON Schema to force an exact response shape. · Allowed: `text`, `json_object`, `json_schema` | | `web_search_linkup` | boolean | no | 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. | | `disable_formatting` | boolean | no | false | Return the answer without the Sources list that web search adds. | ## Notes 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. --- *Machine-readable schema:* `GET https://api.empiriolabs.ai/v1/models/qwen3-6-35b-a3b`.