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Alibaba QwenDense

Qwen3 Coder Plus RAM Calculator

Qwen3 Coder Plus is Alibaba's proprietary version of the Open Source Qwen3 Coder 480B A35B. It is a powerful coding agent model specializing in autonomous programming via tool calling and...

Standard Recommendation

384GB RAM

Calculated for 4-bit (Q4_K_M) @ 8K Context

1. Select Quantization Level

Quantization compresses model weights to reduce RAM usage, with minor impacts on output quality.

2. Set Target Context Length

Longer contexts require more active memory for the Key-Value (KV) cache.

8,192 tokens
1K tokens32K64K128K tokens

Inference Bandwidth & Speed Matrix

Estimates generation speeds (tokens per second) based on physical memory channel bandwidth constraints.

DDR4 CPU Mode

45 GB/s

0.5 t/s

DDR5 CPU Mode

96 GB/s

1.0 t/s

Mac Unified Memory

300 GB/s

3.0 t/s

GPU VRAM (RTX 4090)

1008 GB/s

5.0 t/s

*Token throughput calculated strictly from weight volume transfers over memory channels. Actual generation speeds can be further throttled by processing threads or VRAM offloading parameters.

Technical Specifications

Total Parameter Count480 Billion
Active Parameters Per TokenDense (All active)
Maximum Context Window1 Million tokens
Primary Framework SupportOllama, llama.cpp, ExLlamaV2, vLLM

GPU & VRAM Sizing Profile

Enterprise GPU Node / Mac Studio 192GB
Est. VRAM Required282 GB VRAM
Target GPU HardwareApple Mac Studio (192GB Unified Memory) or Institutional Node (8x H100 / A100)

Hardware Profile: Server-scale deployment. Running this model locally requires extreme unified memory Apple systems or professional multi-GPU servers.

Qwen3 Coder Plus Memory FAQs

How much RAM does Qwen3 Coder Plus require?

To run Qwen3 Coder Plus locally, memory size depends on your selected quantization. At 4-bit compression (Q4_K_M), the weights take up ~270GB of RAM. When combined with context cache and OS overhead, a standard **384GB system memory kit** is recommended. Unquantized FP16 execution requires a **1024GB memory setup**.

What are the hardware requirements to run Qwen3 Coder Plus at FP16 precision?

Running Qwen3 Coder Plus at unquantized 16-bit precision requires loading ~960GB of model weights directly into VRAM or system memory. A minimum system memory target of **1024GB RAM** is required to run the weights stably and avoid out-of-memory crashes.

Is Qwen3 Coder Plus dense or Mixture-of-Experts (MoE)?

Qwen3 Coder Plus is built on a **Dense** architecture. It features a dense parameter layout containing 480 Billion parameters. All weights are active and computed on every single pass during token generation.

How does context window size affect RAM usage for Qwen3 Coder Plus?

Context size directly scales the size of the Key-Value (KV) cache. At a standard 8,192 token context, the KV cache for Qwen3 Coder Plus uses ~1.18GB. If you scale this to 1 Million tokens, the KV cache can scale past hundreds of GBs, requiring multi-GPU or workstation-class RAM configurations.