Latest Qwen3 state of the art model, 32B model
Qwen3 32B can be customized with your data to improve responses. Fireworks uses LoRA to efficiently train and deploy your personalized model
On-demand deployments allow you to use Qwen3 32B on dedicated GPUs with Fireworks' high-performance serving stack with high reliability and no rate limits.
Qwen3 32B is a 32.8 billion parameter base language model developed by Qwen (Alibaba Group). It is part of the third-generation Qwen series, which introduces a dual-mode architecture (thinking vs. non-thinking) for improved performance in reasoning, coding, and dialogue tasks.
The model is optimized for:
It supports both general-purpose dialogue and complex logical tasks.
The model supports a native context length of 32,768 tokens, extendable to 131,072 tokens using YaRN (rope scaling).
Fireworks supports the full 131.1K token window on on-demand deployments.
Thinking mode uses temperature=0.6, top_p=0.95, and top_k=20.
Non-thinking mode uses temperature=0.7, top_p=0.8, and top_k=20.
Greedy decoding is discouraged to avoid repetition and degraded performance.
The recommended output length is up to 32,768 tokens, with a maximum of 38,912 tokens for complex benchmarks (e.g., code/math reasoning)
transformers < v4.51.0Yes. Fireworks supports LoRA-based fine-tuning on dedicated GPU deployments.
Qwen3 32B is released under the Apache 2.0 license, which permits unrestricted commercial use.