Qwen3 0.6B

Qwen3 0.6B API Features

Fine-tuning Docs	Qwen3 0.6B can be customized with your data to improve responses. Fireworks uses LoRA to efficiently train and deploy your personalized model
On-demand Deployment Docs	On-demand deployments give you dedicated GPUs for Qwen3 0.6B using Fireworks' reliable, high-performance system with no rate limits.

Qwen3 0.6B FAQs

What is Qwen3 0.6B and who developed it?

Qwen3 0.6B is a compact language model developed by the Qwen team at Alibaba Cloud. It is part of the Qwen3 family of models optimized for both reasoning ("thinking mode") and fast response generation ("non-thinking mode"). The model supports multilingual dialogue and general-purpose instruction following.

What applications and use cases does Qwen3 0.6B excel at?

This model is designed for:

Multilingual conversational AI
Instruction following and summarization
Agentic reasoning and lightweight tool use
Compact deployment scenarios (e.g., edge inference)

What is the maximum context length for Qwen3 0.6B?

The maximum context length for Qwen3 0.6B is 41,000 tokens.

What are known failure modes of Qwen3 0.6B?

Endless repetition if greedy decoding is used in thinking mode
Reduced efficiency in non-thinking mode when not configured properly
Language mixing with high presence penalty values

Does Qwen3 0.6B support function-calling schemas?

Yes, this model supports function calling.

Is fine-tuning supported for Qwen3 0.6B?

Yes. Fireworks supports LoRA-based fine-tuning for this model.

What rate limits apply on the shared endpoint?

On-demand deployments are supported with no rate limits.

What license governs commercial use of Qwen3 0.6B?

Qwen3 0.6B is licensed under Apache 2.0, which permits commercial use and modification.

Qwen3 0.6B

Qwen3 0.6B API Features

Fine-tuning

On-demand Deployment

Qwen3 0.6B FAQs

Metadata

Specification

Supported Functionality