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Qwen3 Coder 30B A3B Instruct FP8

This repository contains Qwen/Qwen3-Coder-30B-A3B-Instruct-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...

TypeText modelModèle de baseQwen/Qwen3-Coder-30B-A3B-Instruct-FP8VersionRevision 09fe163BClasse

Source du modèle

Type
Text model
Taille du fichier
Pas encore enregistré
Modèle de base
Qwen/Qwen3-Coder-30B-A3B-Instruct-FP8
Version
vRevision 09fe163
Mis à jour
3 oct. 2026
Téléchargements
1,4 k
Tâches
Génération de texte
Source
Hugging Face

Description de la source

Qwen3-Coder-30B-A3B-Instruct-FP8

This repository contains Qwen/Qwen3-Coder-30B-A3B-Instruct-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-Coder-30B-A3B-Instruct-FP8 model card.

Overview

Qwen3-Coder-30B-A3B-Instruct is the streamlined coding variant of the Qwen3-Coder series, an auto-regressive Mixture-of-Experts (MoE) transformer with 30.5B total parameters of which about 3.3B are activated per token. It is optimized for agentic coding and code-related tasks — code generation, repository-scale understanding, and tool use — and operates in non-thinking mode only. Its intended use is the same as the upstream Qwen/Qwen3-Coder-30B-A3B-Instruct-FP8, and it is released under the Apache 2.0 License.

  • Architecture: Qwen3-MoE (Mixture-of-Experts)
  • Input / Output: Text / Text
  • Supported Inference Engine: Furiosa LLM
  • Supported Hardware: FuriosaAI RNGD

Quantization

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.

Features

  • Tool calling. The model supports tool (function) calling through the hermes tool-call parser, the parser used by the Qwen3 series.

Parallelism Strategy

On RNGD, Qwen3-Coder-30B-A3B-Instruct-FP8 runs with a tensor-parallel size of 32 PEs, which maps to four RNGD cards (8 PEs per card).

Usage

To run this model with Furiosa-LLM, follow the example commands below after installing Furiosa-LLM and its prerequisites.

Launch the server

The simplest way to serve the model is:

furiosa-llm serve furiosa-ai/Qwen3-Coder-30B-A3B-Instruct-FP8

To enable tool (function) calling, add the hermes tool-call parser (the parser used by the Qwen3 series):

furiosa-llm serve furiosa-ai/Qwen3-Coder-30B-A3B-Instruct-FP8 \
  --enable-auto-tool-choice \
  --tool-call-parser hermes

When the server is ready, you will see:

INFO:     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)

Basic Usage

The server exposes an OpenAI-compatible API. You can send a request with curl:

curl http://localhost:8000/v1/chat/completions \
    -H "Content-Type: application/json" \
    -d '{
    "model": "furiosa-ai/Qwen3-Coder-30B-A3B-Instruct-FP8",
    "messages": [{"role": "user", "content": "Write a Python function that returns the nth Fibonacci number."}]
    }' \
    | python -m json.tool

Advanced Usage

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.

Learn more

Sources

1 source
Hugging FacePrincipalVersion 09fe16335c8b0bc5e5be234b96457b1f0759c38f
huggingface.co/furiosa-ai/Qwen3-Coder-30B-A3B-Instruct-FP8/tree/09fe16335c8b0bc5e5be234b96457b1f0759c38f

Vérifié 3 oct.

Extraits de sources

3 extraits

--- base_model: Qwen/Qwen3-Coder-30B-A3B-Instruct-FP8 license: apache-2.0 license_link: https://huggingface.co/Qwen/Qwen3-Coder-30B-A3B-Instruct-FP8/blob/main/LICENSE pipeline_tag: text-generation library_name: furiosa-llm tags: - furiosa-ai - qwen3 - qwen3_moe - fp8 --- # Qwen3-Coder-30B-A3B-Instruct-FP8 This repository contains [Qwen/Qwen3-Coder-30B-A3B-Instruct-FP8](https://huggingface.co/Qwen/Qwen3-Coder-30B-A3B-Instruct-FP8) together with a Furiosa Executable Bundle (FXB) for running it on [FuriosaAI RNGD](https://furiosa.ai) with [Furiosa-LLM](https://developer.furiosa.ai/latest/en/furiosa_llm/intro.html). The same model also runs on other frameworks (such as vLLM, SGLang, and Transformers); for usage with those, see the upstream [Qwen/Qwen3-Coder-30B-A3B-Instruct-FP8](https://huggingface.co/Qwen/Qwen3-Coder-30B-A3B-Instruct-FP8) model card. ## Overview Qwen3-Coder-30B-A3B-Instruct is the streamlined coding variant of the Qwen3-Coder series, an auto-regressive **Mixture-of-Experts (MoE)** transformer with 30.5B total parameters of which about 3.3B are activated per token. It is optimized for agentic coding and code-related tasks — code generation, repository-scale understanding, and tool use — and operates in non-thinking mode only. Its intended use is the same as the upstream [Qwen/Qwen3-Coder-30B-A3B-Instruct-FP8](https://huggingface.co/Qwen/Qwen3-Coder-30B-A3B-Instruct-FP8), and it is released under the [Apache 2.0 License](https://huggingface.co/Qwen/Qwen3-Coder-30B-A3B-Instruct-FP8/blob/main/LICENSE). - **Architecture:** Qwen3-MoE (Mixture-of-Experts) - **Input / Output:** Text / Text - **Supported Inference Engine:** Furiosa LLM - **Supported Hardware:** FuriosaAI RNGD ### Quantization 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. ### Features - **Tool calling.** The model supports tool (function) calling through the `hermes` tool-call parser, the parser used by the Qwen3 series. ### Parallelism Strategy On RNGD, Qwen3-Coder-30B-A3B-Instruct-FP8 runs with a **tensor-parallel size of 32 PEs**, which maps to **four RNGD cards** (8 PEs per card). ## Usage To run this model with Furiosa-LLM, follow the example commands below after [installing Furiosa-LLM and its prerequisites]...

Source context: 1362 downloads · 0 likes · Pipeline text-generation · Library furiosa-llm · Repo furiosa-ai/Qwen3-Coder-30B-A3B-Instruct-FP8

Source context: 456 downloads · 0 likes · Pipeline text-generation · Library furiosa-llm · Repo furiosa-ai/Qwen3-Coder-30B-A3B-Instruct-FP8