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Cataloged from furiosa-ai/Qwen3-30B-A3B-Thinking-2507-FP8
All models by furiosa-ai →This repository contains Qwen/Qwen3-30B-A3B-Thinking-2507-FP8 together with a Furiosa Executable Bundle (FXB) for running it on FuriosaAI RNGD with Furiosa-LLM. The same model also runs on other frameworks (such as vLLM, SGLang, and Transformers); for usage with those, see the upstream Qwen/Qwen3-30B-A3B-Thinking-2507-FP8 model card.
Qwen3-30B-A3B-Thinking-2507 is the updated (2507) thinking variant of Qwen3-30B-A3B, an auto-regressive Mixture-of-Experts (MoE) transformer with 30.5B total parameters of which about 3.3B are activated per token. It operates in thinking mode only — it produces an internal chain of thought before its final answer — and offers strong reasoning over text, instruction following, multilingual coverage, and tool usage. Its intended use is the same as the upstream Qwen/Qwen3-30B-A3B-Thinking-2507-FP8, and it is released under the Apache 2.0 License.
Weights are quantized to FP8 (static), following the upstream FP8 release, and activations use dynamic FP8 quantization at runtime (per-token / per-block). The KV cache stays in 16-bit precision.
qwen3 reasoning parser to have Furiosa-LLM parse the reasoning into a separate field (see Basic Usage below).hermes tool-call parser, the parser used by the Qwen3 series.On RNGD, Qwen3-30B-A3B-Thinking-2507-FP8 runs with a tensor-parallel size of 32 PEs, which maps to four RNGD cards (8 PEs per card).
To run this model with Furiosa-LLM, follow the example commands below after installing Furiosa-LLM and its prerequisites.
Qwen3-30B-A3B-Thinking-2507-FP8 always reasons. Serve it with the qwen3
reasoning parser so the chain of thought is returned in a separate field:
To also enable tool (function) calling, add the hermes tool-call parser (the
parser used by the Qwen3 series):
When the server is ready, you will see:
The server exposes an OpenAI-compatible API. You can send a request with curl:
Qwen3-30B-A3B-Thinking-2507-FP8 returns its reasoning separately from the final
answer:
response.choices[].message.reasoning (non-streaming)response.choices[].delta.reasoning (streaming)Note: The
reasoningfield is not part of the OpenAI API specification but is a widely followed convention (the OpenAI Agents SDK, vLLM, and others). It appears only in responses that contain reasoning content; accessing it otherwise raises anAttributeError.
Tool calling. With the server launched using
--enable-auto-tool-choice --tool-call-parser hermes (see
Launch the server), pass tools in the request and let the
model decide when to call them. See the
Tool Calling guide
for a complete client example and details on tool-choice options.
furiosa-llm serve) — full OpenAI-compatible API reference and serving optionsfuriosa-llm serve furiosa-ai/Qwen3-30B-A3B-Thinking-2507-FP8 \ --reasoning-parser qwen3furiosa-llm serve furiosa-ai/Qwen3-30B-A3B-Thinking-2507-FP8 \ --reasoning-parser qwen3 \ --enable-auto-tool-choice \ --tool-call-parser hermesINFO: Started server process [27507]INFO: Waiting for application startup.INFO: Application startup complete.INFO: Uvicorn running on http://0.0.0.0:8000 (Press CTRL+C to quit)curl http://localhost:8000/v1/chat/completions \ -H "Content-Type: application/json" \ -d '{ "model": "furiosa-ai/Qwen3-30B-A3B-Thinking-2507-FP8", "messages": [{"role": "user", "content": "What is the capital of France?"}] }' \ | python -m json.toolfrom openai import OpenAI
client = OpenAI(base_url="http://localhost:8000/v1", api_key="EMPTY")
response = client.chat.completions.create( model="furiosa-ai/Qwen3-30B-A3B-Thinking-2507-FP8", messages=[{"role": "user", "content": "How many r's are in 'strawberry'?"}],)
print("Reasoning:", response.choices[0].message.reasoning)print("Answer:", response.choices[0].message.content)