118 2 weeks ago

Quantized Q4_K_S version of Qwen3-coder 30B FP16 model

tools
ollama run LoPld/qwen3-coder-30b-a3b-q4_K_S

Applications

Claude Code
Claude Code ollama launch claude --model LoPld/qwen3-coder-30b-a3b-q4_K_S
OpenCode
OpenCode ollama launch opencode --model LoPld/qwen3-coder-30b-a3b-q4_K_S
Hermes Agent
Hermes Agent ollama launch hermes --model LoPld/qwen3-coder-30b-a3b-q4_K_S
OpenClaw
OpenClaw ollama launch openclaw --model LoPld/qwen3-coder-30b-a3b-q4_K_S

Models

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Readme

Qwen3-coder – 30B (Q4_K_S)

This is a quantized version (Q4_K_S) of the original:

Qwen3-coder – 30B (FP16)


Overview

  • Base model: Qwen3-coder – 30B (FP16)
  • Quantization: Q4_K_S
  • License: Apache 2.0
  • Format: Ollama model
  • Type: Inference-optimized snapshot

Purpose

This model was created to:

  • Reduce memory usage compared to FP16
  • Improve inference speed on consumer GPUs
  • Enable running a 24B model on more modest hardware
  • Preserve a stable snapshot of the original model

Performance / Size

  • Model footprint: ~17 GB (Q4_K_S)
  • VRAM usage increases with context length due to KV cache
  • Suitable for GPU inference on mid-to-high range consumer hardware

Hardware Notes (estimated)

  • 20 GB VRAM GPU:

    • Stable at ~4K context length in typical setups
  • ~24 GB VRAM GPU :

    • Likely supports ~6K–8K context depending on backend and KV cache settings (Not tested yet)

Trade-offs

Compared to FP16:

  • ✔ Lower VRAM usage
  • ✔ Faster inference
  • ❌ Slight reduction in output quality and precision

Usage

Run locally:

ollama run LoPld/qwen3-coder-30b-a3b-q4_K_S 

Reproducibility

Created from:

FROM qwen3-coder:30b-a3b-fp16

Quantized using:

ollama create <model> --quantize q4_K_S -f Modelfile

License

Original model: Apache 2.0 This quantized version inherits the same license terms.


Notes

  • This is a frozen snapshot of the original model
  • No upstream updates are expected for this version
  • Intended for long-term local use and reproducibility