
Qwen: Qwen3.6 35B A3B
3 providers live- 3 live providers
- 100% uptime
- 0.28 s first token
- 161 tok/s output
Qwen3.6-35B-A3B is an open-weight multimodal model from Alibaba Cloud with 35 billion total parameters and 3 billion active parameters per token. It uses a hybrid sparse mixture-of-experts architecture combining Gated DeltaNet linear attention with standard gated attention layers, enabling efficient inference at a fraction of the compute cost. The model supports a 262K token native context window (extensible to 1M via YaRN) and accepts text, image, and video inputs. It includes integrated thinking mode with reasoning traces preserved across multi-turn conversations, function calling, and structured output. Released under the Apache 2.0 license.
- Context
- 256K
- tokens
- Max output
- 64K
- tokens
- Input
- $0.25
- per million tokens
- Output
- $1.25
- per million tokens
Providers
Ranked by price and speed. Requests go to the best healthy provider, then fail over down the list.Benchmarks| Who answers now | Input per 1M | First token |
|---|---|---|
| $0.25 | 0.48 s | |
| $0.10 | 0.69 s | |
| $0.2881 | 0.28 s |
Prime Intellect answers now: first in the router's order.
First token is the 24-hour median. If the pick fails, the next one answers at its own price.
| # | Provider | Input | Output | Cache read | Latency | Throughput | Uptime (3d) |
|---|---|---|---|---|---|---|---|
| 1 | Data policy not declared | $0.25 | $1.25 | n/a | 0.48 s | 161 tok/s | 94.5% |
| 2 | Data policy not declared | $0.10 | $0.95 | n/a | 0.69 s | 78 tok/s | 100% |
| 3 | Data policy not declared | $0.2881 | $1.7286 | n/a | 0.28 s | 161 tok/s | 100% |
Price history
Input price since Oct 20, 2026, in USD per million tokens.
- DeepInfra
- Prime Intellect
- Scaleway
Data table
| Provider | From | Input | Output |
|---|---|---|---|
| DeepInfra | Oct 20, 2026 | $0.10 | $0.95 |
| Prime Intellect | Oct 21, 2026 | $0.25 | $1.25 |
| Scaleway | Oct 21, 2026 | $0.2888 | $1.7328 |
| Scaleway | Oct 22, 2026 | $0.2893 | $1.7357 |
| Scaleway | Oct 22, 2026 | $0.2886 | $1.7312 |
| Scaleway | Oct 23, 2026 | $0.2883 | $1.7294 |
| Scaleway | Oct 26, 2026 | $0.2881 | $1.7286 |
Performance
Last 24 hours, from llm.buzz's test requestsThroughput (tok/s)
- Prime Intellect161 tok/s
- DeepInfra78 tok/s
- Scaleway161 tok/s
Data table
| Provider | From (UTC) | p50 | p90 | p99 |
|---|---|---|---|---|
| Prime Intellect | Oct 26, 10:00 | 161 tok/s | 161 tok/s | 161 tok/s |
| Prime Intellect | Oct 26, 19:00 | 161 tok/s | 161 tok/s | 161 tok/s |
| Prime Intellect | Oct 27, 00:00 | 134 tok/s | 134 tok/s | 134 tok/s |
| Prime Intellect | Oct 27, 04:00 | 112 tok/s | 112 tok/s | 112 tok/s |
| Prime Intellect | Last 24 hours | 161 tok/s | 112 tok/s | 112 tok/s |
| DeepInfra | Oct 26, 08:00 | 161 tok/s | 161 tok/s | 161 tok/s |
| DeepInfra | Oct 26, 13:00 | 78 tok/s | 78 tok/s | 78 tok/s |
| DeepInfra | Oct 26, 18:00 | 65 tok/s | 65 tok/s | 65 tok/s |
| DeepInfra | Oct 26, 22:00 | 134 tok/s | 134 tok/s | 134 tok/s |
| DeepInfra | Oct 27, 03:00 | 26 tok/s | 26 tok/s | 26 tok/s |
| DeepInfra | Last 24 hours | 78 tok/s | 26 tok/s | 26 tok/s |
| Scaleway | Oct 26, 05:00 | 193 tok/s | 193 tok/s | 193 tok/s |
| Scaleway | Oct 26, 10:00 | 161 tok/s | 161 tok/s | 161 tok/s |
| Scaleway | Oct 26, 15:00 | 78 tok/s | 78 tok/s | 78 tok/s |
| Scaleway | Oct 26, 19:00 | 161 tok/s | 161 tok/s | 161 tok/s |
| Scaleway | Oct 26, 23:00 | 161 tok/s | 161 tok/s | 161 tok/s |
| Scaleway | Oct 27, 03:00 | 232 tok/s | 232 tok/s | 232 tok/s |
| Scaleway | Last 24 hours | 161 tok/s | 78 tok/s | 78 tok/s |
Latency (time to first token)
- Prime Intellect0.48 s
- DeepInfra0.69 s
- Scaleway0.28 s
Data table
| Provider | From (UTC) | p50 | p90 | p99 |
|---|---|---|---|---|
| Prime Intellect | Oct 26, 10:00 | 0.48 s | 0.48 s | 0.48 s |
| Prime Intellect | Oct 26, 19:00 | 0.58 s | 0.58 s | 0.58 s |
| Prime Intellect | Oct 27, 00:00 | 0.48 s | 0.48 s | 0.48 s |
| Prime Intellect | Oct 27, 04:00 | 1.00 s | 1.00 s | 1.00 s |
| Prime Intellect | Last 24 hours | 0.48 s | 1.00 s | 1.00 s |
| DeepInfra | Oct 26, 08:00 | 0.58 s | 0.58 s | 0.58 s |
| DeepInfra | Oct 26, 13:00 | 1.20 s | 1.20 s | 1.20 s |
| DeepInfra | Oct 26, 18:00 | 0.69 s | 0.69 s | 0.69 s |
| DeepInfra | Oct 26, 22:00 | 0.69 s | 0.69 s | 0.69 s |
| DeepInfra | Oct 27, 03:00 | 1.00 s | 1.00 s | 1.00 s |
| DeepInfra | Last 24 hours | 0.69 s | 1.20 s | 1.20 s |
| Scaleway | Oct 26, 05:00 | 0.23 s | 0.23 s | 0.23 s |
| Scaleway | Oct 26, 10:00 | 0.28 s | 0.28 s | 0.28 s |
| Scaleway | Oct 26, 15:00 | 0.28 s | 0.28 s | 0.28 s |
| Scaleway | Oct 26, 19:00 | 0.33 s | 0.33 s | 0.33 s |
| Scaleway | Oct 26, 23:00 | 0.23 s | 0.23 s | 0.23 s |
| Scaleway | Oct 27, 03:00 | 0.28 s | 0.28 s | 0.28 s |
| Scaleway | Last 24 hours | 0.28 s | 0.33 s | 0.33 s |
Uptime
Last 72 hours, by hour- Up: 95% or more served
- Degraded: 85% to 95%
- Down: below 85%
- No data
- From llm.buzz's test requests
Questions
How much does Qwen: Qwen3.6 35B A3B cost?
Qwen: Qwen3.6 35B A3B costs $0.25 per million input tokens and $1.25 per million output tokens at Prime Intellect, the provider requests go to first. Each provider sets its own price, and you pay the price of the provider that answered.
Do providers train on my prompts?
Each provider declares it, and the table above shows every declaration. You can limit a request to providers that keep nothing, or to providers in the EU.
Can I serve Qwen: Qwen3.6 35B A3B myself?
Yes. Apply as a provider, add your endpoint and list this model at your price. It goes live once the automated check passes.
Similar models
Call it
import os
from openai import OpenAI
client = OpenAI(
base_url="https://api.llm.buzz/api/v1",
api_key=os.environ["LLM_BUZZ_KEY"],
)
reply = client.chat.completions.create(
model="qwen/qwen3.6-35b-a3b",
messages=[{"role": "user", "content": "Hello"}],
)import OpenAI from "openai";
const client = new OpenAI({
baseURL: "https://api.llm.buzz/api/v1",
apiKey: process.env.LLM_BUZZ_KEY,
});
const reply = await client.chat.completions.create({
model: "qwen/qwen3.6-35b-a3b",
messages: [{ role: "user", content: "Hello" }],
});curl https://api.llm.buzz/api/v1/chat/completions \
-H "Authorization: Bearer $LLM_BUZZ_KEY" \
-H "Content-Type: application/json" \
-d '{"model": "qwen/qwen3.6-35b-a3b",
"messages": [{"role": "user", "content": "Hello"}]}'Endpoints
POST /api/v1/chat/completionsPOST /api/v1/responsesPOST /api/v1/messagesAuthentication
Send your llm.buzz key as a Bearer token: Authorization: Bearer $LLM_BUZZ_KEY. Create keys in the console. The same key calls every model; each request pays the price of the provider that answered it.
More in Authentication and the API reference.
README
Qwen3.6-35B-A3B is an open-weight multimodal model from Alibaba Cloud with 35 billion total parameters and 3 billion active parameters per token. It uses a hybrid sparse mixture-of-experts architecture combining Gated DeltaNet linear attention with standard gated attention layers, enabling efficient inference at a fraction of the compute cost. The model supports a 262K token native context window (extensible to 1M via YaRN) and accepts text, image, and video inputs. It includes integrated thinking mode with reasoning traces preserved across multi-turn conversations, function calling, and structured output. Released under the Apache 2.0 license.
- Model ID
- qwen/qwen3.6-35b-a3b
- Takes
- Text, image
- Answers
- Text
- Context
- 256K tokens
- Max output
- 64K tokens
- Capabilities
- Tools, Structured outputs
- Parameters
- max_tokens, response_format, structured_outputs, temperature, tool_choice, tools
- Weights
- Open weights
- On llm.buzz since
- Oct 20, 2026