Qwen3-4B-Thinking-2507
18 days ago
- #AI
- #Language Model
- #Qwen3
- Qwen3-4B-Thinking-2507 introduces significant improvements in reasoning tasks, including logical reasoning, mathematics, science, coding, and academic benchmarks.
- Enhanced general capabilities such as instruction following, tool usage, text generation, and alignment with human preferences.
- Supports 256K long-context understanding capabilities and has an increased thinking length for complex reasoning tasks.
- Model features include 4.0B parameters, 36 layers, 32 attention heads for Q and 8 for KV, and a native context length of 262,144.
- Performance benchmarks show improvements in knowledge, reasoning, coding, alignment, agent tasks, and multilingualism.
- Quickstart guide provided for using the model with Hugging Face transformers, including code snippets for text generation.
- Deployment options include sglang, vLLM, Ollama, LMStudio, MLX-LM, llama.cpp, and KTransformers.
- Agentic use is enhanced with Qwen-Agent, which simplifies tool-calling templates and parsers.
- Best practices include recommended sampling parameters, adequate output length, and standardized output formats for benchmarking.
- Citation information provided for referencing the Qwen3 Technical Report.