Qwen3-Instruct API
Open-source MoE for production — 262K context, fast instruction following, developer-first
Qwen3-235B-A22B-Instruct-2507 delivers Mixture-of-Experts (235B total / ~22B active) performance with a native 262K-token context, tuned for non-thinking instruction execution. Ideal for chat assistants, RAG pipelines, code help, and long-document synthesis — all under Apache-2.0.
To use the API for inference, please register an account first. You can view and manage your API token in the API Token dashboard.
All requests to the inference API require authentication via an API token. The token uniquely identifies your account and grants secure access to .
When calling the API, set the Authorization header to your API token, configure the request parameters as shown below, and send the request.
Why Qwen3-Instruct API?
- 235B total / ~22B active MoE — efficient expert routing for strong general performance.
- Native 262K context — load long contracts, papers or multi-file codebases in one call.
- Non-thinking (instruction-tuned) — no >think< block; faster, concise answers by default.
- Open-source Apache-2.0 — audit, self-host, fine-tune; no vendor lock-in.
- Developer-first — OpenAI-compatible endpoints, streaming, retries, observability.
- FP8/BF16 options — latency-aware inference with vLLM/SGLang + tensor parallel.
- Enterprise-ready — role-based access, data privacy, and EU residency options.
| Model | Architecture | Native Context | Open Source | Best For |
| Qwen3-235B-A22B-Instruct-2507 | MoE (235B / ~22B active), non-thinking | 262 K | Fast instruction following, long documents, RAG | |
| Qwen3-235B-A22B-Thinking-2507 | MoE (235B / ~22B active), explicit thinking | 262 K | Complex multi-step reasoning, math & code | |
| OpenAI o4-mini | Proprietary dense + thinking | 200 K → | General reasoning | |
| Claude 3.5 Sonnet | Proprietary | 200 K | Long-context assistance | |
| Gemini 2.5 Pro | Proprietary | 128 K | Multimodal tasks |
Popular Use Cases of Qwen3-Instruct API
High-throughput, low-latency assistants with guardrails, citations, and function calling.
Ingest 100–200+ page specs, contracts or literature and synthesize precise, cited summaries.
Combine vector search with the 262K window to reduce truncation and hallucinations.
Explain unfamiliar code paths, propose fixes, and generate tests across multi-file repos.
Robust English-Chinese performance for support, research and analytics.
Benchmark Highlights (July 2025)
- Arena-Hard v2: competitive head-to-head win rate for instruction following.
- LiveCodeBench v6: robust real-world code tasks under non-thinking decoding.
- MMLU-ProX / INCLUDE: strong multilingual and knowledge benchmarks.
- Long-context demos: 200K+ token inputs with stable recall and coherence.
Frequently Asked Questions of Qwen3-235B-A22B-Instruct-2507 API
Q What is the Qwen3-235B-A22B-Instruct-2507 API (open-source MoE LLM with 262K context)?
The Qwen3-Instruct API is an open-source Apache-2.0 Mixture-of-Experts LLM (235B total / ~22B active) with a native 262K-token context window. It’s designed for fast instruction following, RAG, long-document summarization, and OpenAI-compatible integrations.
Q Qwen3 Instruct vs Thinking — which API should I choose for reasoning and chain-of-thought?
Choose Instruct for concise, low-latency answers (no <think>). Choose Qwen3-Thinking-2507 for explicit chain-of-thought and multi-step reasoning. Many users search “Qwen3 Instruct vs Thinking”,“open-source reasoning LLM API”, or “chain-of-thought API”.
Q Does the Qwen 235B API support long documents (262k context LLM API for contracts, papers, codebases)?
Yes—this long-context LLM API supports 262,144 tokens. Typical use cases include contracts, research papers, and multi-file repos.
Q How do I integrate the Qwen3 235B API with OpenAI-compatible SDKs (Python/Node)?
The API is OpenAI-compatible.
Q Can I self-host Qwen3-235B-A22B with vLLM or SGLang (on-prem, private cloud)?
Yes. It’s Apache-2.0 and supports vLLM / SGLang with tensor parallel and streaming. Long-tail queries include“self-host Qwen3 235B”, “on-prem MoE LLM”, and“SGLang/vLLM setup for Qwen3”.
Q What benchmarks does the Qwen3 Instruct API perform well on (Arena-Hard, LiveCodeBench, MMLU-ProX)?
It shows strong results on Arena-Hard v2, LiveCodeBench, and MMLU-ProX, with robust multilingual performance. Benchmark-intent keywords: “Qwen3 235B benchmarks”,“Qwen vs Llama/Mixtral”, “open-source GPT-4 alternative”.
Q How does pricing, quotas and rate limits work for the Qwen3-235B-A22B Instruct API?
We provide a free tier and usage-based plans. Developers search“Qwen3 API pricing”, “Qwen 235B rate limits”, and“Qwen API quotas”.
Q Is the Qwen3-Instruct API suitable for enterprise (EU data residency, security, compliance)?
Yes. We offer enterprise plans with EU data residency, SSO, audit logs, and SLAs. Popular queries: “enterprise LLM API”,“EU data residency AI”, “Apache-2.0 commercial use”.
Q Qwen3-235B-A22B vs Llama/Mixtral — which long-context MoE LLM API should I pick?
The Qwen3 235B MoE API combines a 262K context window with competitive quality and open-source licensing.