LangMart: Qwen: Qwen3 235B A22B
Model Overview
| Property | Value |
|---|---|
| Model ID | openrouter/qwen/qwen3-235b-a22b |
| Name | Qwen: Qwen3 235B A22B |
| Provider | qwen |
| Released | 2025-04-28 |
Description
Qwen3-235B-A22B is a 235B parameter mixture-of-experts (MoE) model developed by Qwen, activating 22B parameters per forward pass. It supports seamless switching between a "thinking" mode for complex reasoning, math, and code tasks, and a "non-thinking" mode for general conversational efficiency. The model demonstrates strong reasoning ability, multilingual support (100+ languages and dialects), advanced instruction-following, and agent tool-calling capabilities. It natively handles a 32K token context window and extends up to 131K tokens using YaRN-based scaling.
Description
LangMart: Qwen: Qwen3 235B A22B is a language model provided by qwen. This model offers advanced capabilities for natural language processing tasks.
Provider
qwen
Specifications
| Spec | Value |
|---|---|
| Context Window | 40,960 tokens |
| Modalities | text->text |
| Input Modalities | text |
| Output Modalities | text |
Pricing
| Type | Price |
|---|---|
| Input | $0.18 per 1M tokens |
| Output | $0.54 per 1M tokens |
Capabilities
- Frequency penalty
- Include reasoning
- Logit bias
- Logprobs
- Max tokens
- Min p
- Presence penalty
- Reasoning
- Repetition penalty
- Response format
- Seed
- Stop
- Structured outputs
- Temperature
- Tool choice
- Tools
- Top k
- Top logprobs
- Top p
Detailed Analysis
Qwen3-235B-A22B is the flagship Mixture-of-Experts language model in the Qwen 3 series, representing state-of-the-art capabilities with efficient sparse activation. Released April 2025. Key characteristics: (1) Architecture: 235B total parameters with ~22B activated per forward pass (A22B), achieving ~83% compute reduction versus hypothetical dense 235B model while maintaining frontier performance; uses Qwen 3 MoE design with global-batch load balancing excluding shared experts, trained on 36T tokens; (2) Performance: Achieves results competitive with or exceeding GPT-4, Claude 3 Opus, and Gemini 1.5 Pro on major benchmarks; excels at complex reasoning, advanced mathematics, sophisticated code generation, and long-context understanding; (3) Use Cases: Applications requiring maximum language model capability, complex research and analysis, advanced code generation with architectural design, sophisticated content creation, high-stakes reasoning tasks, enterprise AI requiring frontier performance; (4) Context Window: 131K tokens supporting extensive document processing; (5) Pricing: Based on 22B activated parameters rather than 235B total, offering frontier capability at fraction of cost versus equivalent dense model; (6) Trade-offs: Highest capability in Qwen 3 lineup; MoE architecture provides remarkable efficiency. Best for applications requiring absolute maximum capability while optimizing inference costs - demonstrates that sparse activation can achieve frontier performance at significantly reduced computational cost.