Using Qwen3-Coder-480B-A35B-Instruct on NVIDIA NIM

Quick Start

1. 1
   Create an account at NVIDIA NIM and generate an API key.
2. 2
   Use the NVIDIA NIM SDK or REST API to call qwen/qwen3-coder-480b-a35b-instruct — see the documentation for request format.
3. 3
   You'll be billed . See full pricing.

Code Examples

About NVIDIA NIM

NIM packages inference runtimes and model profiles into containers that expose standard API surfaces such as chat completions, completions, model listing, tokenization, health, and management endpoints. The hosted API path is useful for prototyping and catalog discovery, while the NGC/container path is the self-hosted route for teams that want GPU-hour infrastructure control, private-network deployment, Kubernetes scaling, or NVIDIA AI Enterprise support. Per-token pricing is not a universal provider-level claim in the current seed data; pricing should stay attached to sourced model-provider rows or NVIDIA's current catalog terms.

NVIDIA NIM is NVIDIA's deployment platform for GPU-accelerated inference microservices. Developers can try hosted NIM APIs through the NVIDIA API Catalog on build.nvidia.com, then move the same model families into self-hosted NIM containers on NVIDIA GPUs in a data center, private cloud, public cloud, or workstation. The catalog positions NIM around optimized open and NVIDIA models, including chat, coding, reasoning, retrieval, vision, speech, and safety use cases, with downloadable model cards and API endpoints where NVIDIA exposes them.

Pricing on NVIDIA NIM

Capabilities

About Qwen3-Coder-480B-A35B-Instruct

Qwen3-Coder-480B-A35B-Instruct is Alibaba's flagship open-source code generation and agentic model, released July 22, 2025 under the Apache 2.0 license. The model has 480 billion total parameters with 35 billion active parameters per token, organized across 62 transformer layers with 160 specialized expert networks and 8 experts activated per token. It uses Grouped Query Attention (GQA) with 96 query heads and 8 key-value heads and supports a native context window of 262,144 tokens, extendable to 1 million tokens via YaRN position scaling. The model is purpose-built for software engineering tasks and agentic workflows: code generation, code review, test writing, multi-step debugging, and browser-based agentic task execution. On release, it achieved state-of-the-art results among open models on Agentic Coding, Agentic Browser-Use, and Agentic Tool-Use benchmarks, with performance comparable to Claude Sonnet 4 on these tasks. Available via Fireworks AI, Google Vertex AI, NVIDIA NIM, AWS Bedrock, Novita AI, and the Vercel AI Gateway.