Qwen3.6 Flash
Qwen3.6 Flash is Alibaba Cloud's open-weight sparse MoE (35B total / 3B active) that excels at agentic coding, with 262K context. Access it through Velokey's unified endpoint with below-list pricing.
Use cases
Agentic coding & multi-file dev · Terminal & tool-driven automation
Input
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Output
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Billing
Per token
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Pricing details
Transparent usage-based pricing with no hidden fees.
Detailed Pricing
Tiered pricingUsage-based pricing breakdown
| Spec | Price | Official | Savings |
|---|---|---|---|
| Input/1M tokens | 0.2 Credits≈$0.2 | 0.25 Credits | -20% |
| Output/1M tokens | 1.2 Credits≈$1.2 | 1.5 Credits | -20% |
| Cache Read/1M tokens | 0.02 Credits≈$0.02 | 0.025 Credits | -20% |
| Cache Write/1M tokens | 0.25 Credits≈$0.25 | 0.3125 Credits | -20% |
| Spec | Price | Official | Savings |
|---|---|---|---|
| Input/1M tokens | 0.8 Credits≈$0.8 | 1 Credits | -20% |
| Output/1M tokens | 3.2 Credits≈$3.2 | 4 Credits | -20% |
| Cache Read/1M tokens | 0.08 Credits≈$0.08 | 0.1 Credits | -20% |
| Cache Write/1M tokens | 1 Credits≈$1 | 1.25 Credits | -20% |
Billing Rules
- Output price varies by model, resolution, quality, duration, or token usage.
- Uploaded reference files may be charged separately when supported.
- Add-on capabilities such as web search or image search may be billed per request.
- Token-based models are billed by input and output tokens.
- If the primary route is unavailable, Velokey may automatically switch to a stable fallback route when possible.
- Usage is pay-as-you-go with transparent credit deduction.
* Final cost depends on the generated result.
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Affordable Qwen3.6 Flash API
Access Alibaba Cloud's Qwen3.6 Flash on Velokey — efficient sparse MoE, outstanding agentic coding, a native 262K context, and thinking preserved across flows, with a unified endpoint and below-list pricing for production apps.
Meet Qwen3.6 Flash and its API access
Qwen3.6 Flash (Qwen3.6-35B-A3B) is Alibaba Cloud's open model released on April 14, 2026, using a sparse Mixture-of-Experts architecture: 35B total parameters with only 3B active. It combines Gated DeltaNet linear attention with standard Gated Attention and a sparse MoE (256 experts, 8 routed + 1 shared active), surpassing Qwen3.5-35B-A3B on agentic coding by a wide margin and rivaling much larger dense models. Weights are open under Apache 2.0 on Hugging Face and ModelScope, with a native 262K context extendable to 1M tokens using YaRN. Velokey provides an affordable, easy-to-integrate Qwen3.6 Flash API: a unified chat endpoint, a clear request flow, and below-list pricing for production systems, agent pipelines, and automation tools.
Outstanding agentic coding
Surpasses Qwen3.5-35B-A3B on agentic coding by a wide margin and rivals much larger dense models — 73.4% SWE-bench Verified and 51.5% Terminal-Bench 2.0 — fit for multi-file agentic development.
View Documentation →
Efficient 35B/3B sparse MoE
35B total parameters with only 3B active, combining Gated DeltaNet linear attention with a 256-expert sparse MoE (8 routed + 1 shared active) for efficient, low-cost inference while preserving quality.
View Documentation →
Native 262K long context
Native 262K context, extendable to 1M tokens with YaRN — fit for entire codebases, very long documents, and long-horizon agentic workflows.
View Documentation →
Thinking preserved across agent flows
Thinking-mode preservation maintains full reasoning context across extended agentic workflows, so the reasoning chain is not lost between multiple tool steps, staying coherent and stable.
View Documentation →
How to deploy the Qwen3.6 Flash API on Velokey
Get started with just a few steps.
Sign up and get an API Key
Sign in to the Velokey console to generate an API Key that authenticates every request sent to Qwen3.6 Flash.
Configure request parameters
Set model to qwen-3-6-flash and submit messages. Enable YaRN to extend context to 1M for very long inputs; turn on thinking mode to preserve full reasoning across long agentic flows.
Integrate and start calling
Send requests to Velokey's unified /v1/chat/completions endpoint to power assistants, agents, and automation, with usage managed in one console.
Real-world use cases for Qwen3.6 Flash
From agentic coding to long-document reasoning, covering many high-autonomy scenarios.
Agentic coding & multi-file dev
With 73.4% SWE-bench Verified and linear-attention efficiency, fit for multi-file agentic development, refactoring, and bug fixing.
Terminal & tool-driven automation
51.5% on Terminal-Bench 2.0 — fit for terminal operations, tool calling, and long-horizon automation tasks.
Whole-repo & long-doc reasoning
Native 262K (1M with YaRN) context — fit for retrieval, synthesis, and QA across entire codebases and long documents.
Efficient, low-cost deployment
The 35B/3B sparse MoE activates only 3B parameters — fit for cost- and throughput-sensitive deployments at scale.
Long-horizon agent workflows
Thinking-mode preservation keeps full reasoning context — fit for long-horizon agent orchestration across many tool steps.
Open-weight self-hosting & customization
Apache 2.0 open weights (Hugging Face / ModelScope) — fit for self-hosting, fine-tuning, and downstream customization.
Why choose Velokey for Qwen3.6 Flash
Discount on list price
Call Qwen3.6 Flash at a lower price on Velokey — pay-as-you-go with no forced subscription, reducing upfront cost.
Unified API interface
One API Key accesses Qwen3.6 Flash and other models — no juggling multiple accounts and keys, simplifying integration.
Complete docs and migration guidance
Endpoint references, parameter details, and migration examples help you integrate quickly and adopt long context and thinking mode.
Stable and highly available
Automatic failover and stable fallback routes maintain availability when the primary route is down, keeping production reliable.
API Reference
Complete API call examples and parameter descriptions
Endpoint
https://api.velokey.ai/v1/chat/completionsAuthentication
Bearer YOUR_API_KEYRequest Example
curl https://api.velokey.ai/v1/chat/completions \
-X POST \
-H "Authorization: Bearer YOUR_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"model": "qwen3.6-flash",
"messages": [{"role": "user", "content": "Hello!"}],
"temperature": 0.7
}'Response Example
{
"id": "req_abc123",
"model": "qwen3.6-flash",
"created": 1234567890,
"data": { ... }
}Qwen3.6 Flash API FAQ
What is Qwen3.6 Flash?
It is Alibaba Cloud's open model Qwen3.6-35B-A3B released on April 14, 2026 (served via the Model Studio API as qwen3.6-flash). It uses a sparse MoE architecture with 35B total and 3B active parameters, with weights open under Apache 2.0 on Hugging Face and ModelScope.
What is special about its architecture?
It uses a novel architecture combining Gated DeltaNet linear attention with standard Gated Attention and a sparse MoE (256 experts, 8 routed + 1 shared active), achieving efficient inference at just 3B active parameters while preserving quality.
How large is the context window?
Native context is 262K, extendable to 1M tokens with YaRN — fit for entire codebases, very long documents, and long-horizon agentic workflows.
How good is its agentic coding?
It surpasses Qwen3.5-35B-A3B on agentic coding by a wide margin and rivals much larger dense models, scoring 73.4% on SWE-bench Verified and 51.5% on Terminal-Bench 2.0, while preserving full thinking context across long flows.
How is it billed on Velokey?
This page's pricing area shows the current Velokey price, billed by input and output tokens with a discount on list price and no forced subscription.
Start building with Qwen3.6 Flash today
Use one API key to access low-cost, stable AI models through Velokey.