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Qwen/Qwen3-0.6B on AX637.axllm runtime files.axllm binary, compiled text .axmodel files, tokenizer data, and runtime configs.prefill_len=128, kv_cache_len=1023, and prefill_max_token_num=768.axllm run and the OpenAI-compatible axllm serve API.TTFT stands for time to first token./no_think instruction so that the measured outputs reflect direct answers or direct generation rather than a variable-length reasoning preamble.Output tokens below are model-token counts observed in the board-side runtime log.| Scenario | Input tokens | Output tokens | Prefill chunks | TTFT | Decode |
|---|---|---|---|---|---|
Short-answer text request (/no_think + city-name answer) | 28 | 5 | 1 x 128 | 234.47 ms | 6.50 token/s avg |
Long-output text generation (/no_think + number sequence request) | 30 | 256 | 1 x 128 | 233.89 ms | 8.13 token/s avg |
prefill_len=128kv_cache_len=1023prefill_max_token_num=768| Item | Value |
|---|---|
Package flash total | 1.30 GiB |
Runtime CMM increment during board-side startup | 774 MB |
remain_cmm decreased from 2005 MB after the first text layer init to 1231 MB after post-model init.1.
2├── README.md
3├── bin/
4│ ├── axllm
5│ └── axllm.version.json
6├── config.json
7├── post_config.json
8├── qwen3_tokenizer.txt
9├── model.embed_tokens.weight.bfloat16.bin
10├── qwen3_p128_l0_together.axmodel
11├── ...
12├── qwen3_p128_l27_together.axmodel
13└── qwen3_post.axmodelaxllm binary lives under bin/, and the compiled text runtime files live at the repository root.axllm1mkdir -p AXERA-TECH/Qwen3-0.6B-AX637
2cd AXERA-TECH/Qwen3-0.6B-AX637
3hf download AXERA-TECH/Qwen3-0.6B-AX637 --local-dir .axllmchmod +x ./bin/axllmlibax_engine.so, add /opt/lib to LD_LIBRARY_PATH before launch.axllm from the public repository if you prefer a system-wide binary:1git clone -b axllm https://github.com/AXERA-TECH/ax-llm.git
2cd ax-llm
3./install.sh1chmod +x ./bin/axllm
2./bin/axllm serve . --port 8000AXERA-TECH/Qwen3-0.6B-AX6371curl http://127.0.0.1:8000/health
2curl http://127.0.0.1:8000/v1/models1{
2 "concurrency": 0,
3 "max_concurrency": 1,
4 "status": "healthy"
5}1{
2 "data": [
3 {
4 "id": "AXERA-TECH/Qwen3-0.6B-AX637",
5 "object": "model"
6 }
7 ],
8 "object": "list"
9}1chmod +x ./bin/axllm
2./bin/axllm run .1curl http://127.0.0.1:8000/v1/chat/completions \
2 -H 'Content-Type: application/json' \
3 -d '{
4 "model": "AXERA-TECH/Qwen3-0.6B-AX637",
5 "messages": [
6 {"role": "user", "content": "/no_think\nWhat is the capital of the United States? Answer with the city name only."}
7 ],
8 "max_tokens": 32,
9 "temperature": 0
10 }'1{
2 "choices": [
3 {
4 "message": {
5 "content": "Washington",
6 "role": "assistant"
7 }
8 }
9 ]
10}/no_think, as shown in the validated example above./no_think, keep enough max_tokens budget for both the reasoning span and the final answer.139953715