Powered by Qwen
Qwen3 Max
- Instruction Following
Qwen3 Max is Qwen’s flagship trillion-parameter large language model, offered as a high-end proprietary API model. It is designed to deliver state-of-the-art performance across reasoning, coding, and multilingual tasks within the Qwen3 family.
About the model
What is Qwen3 Max?
Qwen3 Max is a proprietary large language model from Qwen with over one trillion parameters, accessible via API for advanced text generation and reasoning tasks. It is mainly used for building high-end chatbots and AI assistants that require strong general reasoning, instruction following, and multilingual capabilities. It is also applied to demanding workloads such as software engineering assistance, scientific and mathematical problem solving, and complex agentic or tool-using applications. Qwen3 Max belongs to the Qwen3 model family, which extends earlier Qwen/Tongyi Qianwen models with larger-scale dense and Mixture-of-Experts variants and specialized derivatives like Qwen3-Max-Thinking.
Model capabilities
5 Core Capabilities
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Advanced Chat
Supports rich, multi-turn conversational AI with strong instruction following, open-ended dialogue, and aligned responses across diverse domains and tasks.
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Long-Context Reasoning
Handles ultra-long inputs and complex documents while maintaining coherence, enabling deep reasoning, analysis, summarization, and multi-step problem-solving.
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Code Generation
Generates, explains, and debugs code for multiple programming languages, solving complex software tasks and real-world programming challenges reliably.
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Multilingual Translation
Understands and generates text in over 100 languages, providing high-quality translation and cross-lingual communication for global use cases.
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Tool-Using Agents
Optimized for tool calling and agentic workflows, orchestrating APIs, retrieval systems, and external tools to complete complex tasks autonomously.
Use cases
6 Most Valuable Use Cases
- Advanced Code Generation
- Complex Research Q&A
- Enterprise Knowledge Search
- Legal & Policy Drafting
- Business Process Automation
- Long-Form Document Summaries
Transparent pricing
Cost Comparison
LLM API offers the lowest cost and latency for Qwen3 Max–class models.
| Provider | Region | Latency | Throughput | Uptime | Input ($/1M) | Output ($/1M) | Context |
|---|---|---|---|---|---|---|---|
| LLM API BEST | Global | 120ms | 120 tps | 99.99% | $0.20 | $0.60 | 200K |
| Qwen | Global | ~220ms | ~70 tps | ~99.9% | ~$0.25 | ~$0.75 | 128K |
| Alibaba Cloud | APAC | ~260ms | ~55 tps | ~99.9% | ~$0.28 | ~$0.80 | 128K |
| Together AI | US East | ~240ms | ~65 tps | ~99.9% | ~$0.30 | ~$0.90 | 128K |
| Fireworks AI | US West | ~230ms | ~60 tps | ~99.9% | ~$0.32 | ~$0.95 | 128K |
Performance benchmarks
Technical Specifications
| Metric | Qwen3 Max | GPT-4.1 | Claude 3.5 Sonnet |
|---|---|---|---|
| Avg Latency | ~180ms | ~220ms | ~250ms |
| Context Window | 128K | 128K | 200K |
| Input Price ($/1M) | $0.40 | $5.00 | $3.00 |
| Output Price ($/1M) | $1.20 | $15.00 | $15.00 |
| Max Output Tokens | 8K | 4K | 4K |
| Throughput | 60 tps | 40 tps | 35 tps |
| Uptime | 99.9% | 99.9% | 99.9% |
30-day usage via LLM API
- 11.4B
- Prompt tokens processed (30 days)
- 420M
- Completion tokens generated (30 days)
- 5.6M
- API requests served (30 days)
- 99.8%
- Avg uptime over last 30 days
Architecture & Integration
Why Build on LLM.API?
One unified API. Every major model. Built-in reliability, cost control, and observability.
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Intelligent Model Routing
Dynamically route each request to the best-fit model across providers based on latency, capability, or custom rules—without changing client code or redeploying.
One endpoint, any model. -
Cost-Aware Orchestration
Automatically balance quality and price with per-request policies, tiered model selection, and spend controls so you ship faster without surprise bills.
Optimize quality per dollar. -
Resilient Fallback Flows
Define multi-provider fallback chains that seamlessly retry on timeouts, rate limits, or errors—keeping your AI features online even when vendors fail.
Never fail on first try. -
End-to-End Observability
Trace every request across models with logs, metrics, and latency breakdowns so you can debug prompts, tune policies, and prove SLAs in production.
See every token, everywhere. -
Task-Level Abstractions
Call high-level tasks like chat, tools, and embeddings instead of provider-specific APIs, freeing you to swap models without rewriting integrations.
Think tasks, not vendors. -
High-Throughput Batch Jobs
Process millions of requests in parallel with batch APIs that handle retries, chunking, and backoff so large-scale workloads stay fast and cost-efficient.
Scale from 10 to millions.
Decision guide
When to Use — When NOT to Use
Use it if...
- You need a strong general-purpose model for chatbots, agents, and productivity tools.
- You need robust English and Chinese capabilities for multilingual applications or global products.
- Your use case involves complex code generation, debugging, or explaining codebases across languages.
- You need long-context understanding for analyzing extended documents, logs, or conversations together.
- Your use case involves knowledge-intensive question answering and detailed, well-structured writing outputs.
- You need competitive frontier-model quality without relying on US-based foundation model providers.
Avoid if...
- You need guaranteed, contract-backed SLAs, compliance attestations, and enterprise support in specific jurisdictions.
- Your workload requires tight integration with a proprietary ecosystem like Azure OpenAI or Vertex.
- You need a heavily distilled small model for ultra-low-latency, on-device inference scenarios.
- Your workload requires strict data residency in regions not covered by Qwen infrastructure.
- You need proven performance on highly specialized domains requiring vetted domain-specific fine-tuning.
- Your workload requires long-term model version stability and regulatory audits already adopted at scale.
FAQ
Frequently Asked Questions
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What is Qwen3 Max?
Qwen3 Max is a high‑capacity Qwen large language model suitable for complex reasoning, coding assistance, and multi-turn conversational applications.
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What is the context window of Qwen3 Max?
Qwen3 Max supports long-context inputs; check the LLM.API model card for the exact maximum token window currently configured.
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How much does it cost to use Qwen3 Max through LLM.API?
Pricing for Qwen3 Max on LLM.API is usage-based per 1,000 tokens; see the LLM.API pricing page for current rates.
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What modalities does Qwen3 Max support on LLM.API?
Qwen3 Max supports text input and output, with modality extensions such as image input depending on the configuration exposed by LLM.API.
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How fast is Qwen3 Max in terms of latency?
Qwen3 Max typically returns first tokens within a few hundred milliseconds to a couple of seconds, depending on prompt length and traffic.
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How do I call Qwen3 Max via the LLM.API?
Use the LLM.API chat or completion endpoint, specifying the model name "qwen3-max" and passing your prompt and parameters in the JSON payload.
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What is Qwen3 Max best suited for?
Qwen3 Max is best for complex code generation, in-depth data analysis, multi-step reasoning, and robust multilingual dialogue.
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How does Qwen3 Max compare to similar large models?
Qwen3 Max targets competitive reasoning and coding quality at a lower cost than many frontier models, with strong performance on multilingual and long-context tasks.
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What limitations should I be aware of when using Qwen3 Max?
Qwen3 Max can hallucinate facts, misinterpret ambiguous instructions, and should not be solely relied on for safety-critical or legally binding decisions.
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Does Qwen3 Max support streaming responses on LLM.API?
Yes, you can enable streaming in LLM.API requests to receive Qwen3 Max tokens incrementally as they are generated.