LangMart: Qwen: Qwen-Max
Model Overview
| Property | Value |
|---|---|
| Model ID | openrouter/qwen/qwen-max |
| Name | Qwen: Qwen-Max |
| Provider | qwen |
| Released | 2025-02-01 |
Description
Qwen-Max, based on Qwen2.5, provides the best inference performance among Qwen models, especially for complex multi-step tasks. It's a large-scale MoE model that has been pretrained on over 20 trillion tokens and further post-trained with curated Supervised Fine-Tuning (SFT) and Reinforcement Learning from Human Feedback (RLHF) methodologies. The parameter count is unknown.
Description
LangMart: Qwen: Qwen-Max is a language model provided by qwen. This model offers advanced capabilities for natural language processing tasks.
Provider
qwen
Specifications
| Spec | Value |
|---|---|
| Context Window | 32,768 tokens |
| Modalities | text->text |
| Input Modalities | text |
| Output Modalities | text |
Pricing
| Type | Price |
|---|---|
| Input | $1.60 per 1M tokens |
| Output | $6.40 per 1M tokens |
Capabilities
- Max tokens
- Presence penalty
- Response format
- Seed
- Temperature
- Tool choice
- Tools
- Top p
Detailed Analysis
Qwen-Max is the flagship commercial model in Alibaba Cloud's Qwen series, representing the most powerful and capable model for complex, multi-step tasks. Key characteristics: (1) Architecture: Dense transformer with largest parameter count in the Qwen API lineup, optimized for reasoning depth over speed; (2) Performance: Achieves competitive results with GPT-4 and Claude on complex reasoning, multi-step planning, and long-form generation tasks; (3) Use Cases: Ideal for research applications, complex document analysis, multi-turn conversations requiring deep context understanding, creative writing with nuanced requirements, and advanced code generation with architectural planning; (4) Context Window: Extended context support (exact window varies by version, typically 8K-32K tokens); (5) Pricing: Premium tier at $1.60/1M input tokens, $6.40/1M output tokens, reflecting its position as the highest-capability model; (6) Trade-offs: Higher latency compared to Qwen-Plus/Turbo, higher cost per request, but superior accuracy on complex tasks. Best suited for applications where quality and capability are prioritized over speed and cost.