ollama-multirun: qwen3:0.6b

ollama-multirun: hi: qwen3:0.6b: 20250713-163234

Prompt: (raw) (yaml) words:1 bytes:3
hi

Thinking: qwen3:0.6b (raw)
Okay, the user just said "hi" and I'm a language model. First, I need to acknowledge their greeting. I should respond politely and keep the conversation friendly. Maybe say something like, "Hello! How can I assist you today?" That's a good start. Then, I can ask a question to engage them further, like asking how I can help them with their needs. I should make sure to keep the tone friendly and approachable. Let me check for any errors and ensure the response is clear and helpful.

Output: qwen3:0.6b (raw)
Hello! How can I assist you today? 😊

Stats (raw)
Words	8
Bytes	41
Total duration	1.292759042s
Load duration	28.554ms
Prompt eval count	11 token(s)
Prompt eval duration	90.813917ms
Prompt eval rate	121.13 tokens/s
Eval count	123 token(s)
Eval duration	1.172873167s
Eval rate	104.87 tokens/s

Model (raw)
Name	qwen3:0.6b
Architecture	qwen3
Size	2.3 GB
Parameters	751.63M
Context length	40960
Embedding length	1024
Quantization	Q4_K_M
Capabilities	completion tools thinking

System
Ollama proc	100% GPU
Ollama context	8192
Ollama version	0.9.7-rc0
Multirun timeout	300 seconds
Sys arch	arm64
Sys processor	arm
sys memory	8673M + 531M
Sys OS	Darwin 24.5.0