Comprehensive side-by-side LLM comparison
Qwen3-VL Flash supports multimodal inputs. Both models have their strengths depending on your specific coding needs.
Microsoft
Phi-3.5-MoE-instruct is a sparse mixture-of-experts model from Microsoft's Phi research team, released in August 2024 with 42 billion total parameters across 16 experts and approximately 6.6 billion active parameters per forward pass. The model applies Microsoft's small-data, high-quality training philosophy — developed across earlier Phi generations — to a MoE architecture, targeting reasoning quality comparable to much larger dense models at a fraction of the inference compute. Released under the MIT license, it was notable in the research community for demonstrating that MoE efficiency gains could be realized at smaller total parameter counts than typical large-scale MoE deployments.
Alibaba / Qwen
Qwen3-VL Flash is a lightweight multimodal variant from Alibaba's Qwen3-VL family, designed for efficient visual reasoning and image understanding at lower inference cost. It inherits the joint visual-textual architecture of the Qwen3-VL series and targets latency-sensitive applications requiring multimodal input processing at scale.
1 year newer

Phi-3.5-MoE Instruct
Microsoft
2024-08-22
Qwen3-VL Flash
Alibaba / Qwen
2026-01-22
Available providers and their performance metrics
Phi-3.5-MoE Instruct
Qwen3-VL Flash
Phi-3.5-MoE Instruct
Qwen3-VL Flash