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OpenPipe/Qwen3-14B-InstructDmlExecutionProvidermodel.onnxmodel.onnx.data ← INT4 weights (≈ 9 GB)genai_config.jsontokenizer.json, vocab.json, merges.txtchat_template.jinja1using Microsoft.ML.OnnxRuntimeGenAI;
2
3var modelPath = @"Qwen3-14B-Instruct-DirectML-INT4";
4
5using var model = Model.Load(modelPath, new ModelOptions
6{
7 ExecutionProvider = ExecutionProvider.DirectML
8});
9
10using var tokenizer = new Tokenizer(model);
11var tokens = tokenizer.Encode("Explain what a Dutch mortgage deed is.");
12
13using var generator = new Generator(model, new GeneratorParams
14{
15 MaxLength = 1024,
16 Temperature = 0.7f
17});
18
19generator.AppendTokens(tokens);
20generator.Generate();
21
22string output = tokenizer.Decode(generator.GetSequence(0));
23Console.WriteLine(output);
24Prompt Format
25This model supports standard chat-style prompts and works well with Hermes-style system prompts and tool calling.
26
27The included chat_template.jinja can be used to format multi-role conversations.
28
29Performance Notes
30INT4 allows the 14B model to run on:
31
3216 GB VRAM GPUs (Arc 130V, RTX 3060, RX 6800)
33
34Throughput depends heavily on DirectML backend and driver quality.
35
36First token latency may be high due to graph compilation.
37
38License & Attribution
39Base model:
40
41Qwen3-14B-Instruct by Alibaba / OpenPipe
42
43License: see original model card
44
45Conversion:
46
47ONNX + INT4 quantization performed by Wekkel using Microsoft Olive.
48
49This is an independent community conversion.
50
51No affiliation with Alibaba or Qwen team.