AI BriefingAccelerating Qwen3-8B on Intel Core Ultra
Key point
OpenVINO and depth-pruning boosted Qwen3-8B inference speed by 1.4x on Intel Core Ultra.
Details
Qwen3-8B is an agent-specialized model with tool-calling and multi-step reasoning capabilities, making it well-suited for AIPC environments.
By applying Speculative Decoding using OpenVINO.GenAI, with Qwen3-0.6B used as the Draft model, a speedup of about 1.3x was achieved compared to the baseline.
On top of this, Depth-Pruning, a technique that removes layers from the draft model, was combined to further boost performance. Out of the 28 layers of the Qwen3-0.6B model, 6 were removed, and then fine-tuning with synthetic data was used to restore accuracy.
As a result, the draft model's latency was reduced, ultimately confirming an acceleration effect of about 1.4x, demonstrating that AI agents can be run faster and more efficiently in local environments.
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