Microsoft

COMPACT MULTIMODAL

Phi‑4 Multimodal

Compact Microsoft model that combines language, vision, and audio, including speech transcription and translation.

18 SEP 2026↗ CONVERSATION REPRESENTATION FOR SIMULATION

UserRepGen-4B

Microsoft checkpoint based on Qwen3.5-4B that turns text conversations into descriptions of the task and observed behaviour. Weights were uploaded to the official repository on October 14, 2026. It generates representations for a separate simulator: it does not itself produce user turns or execute their task. Although it retains the base model’s multimodal architecture, this release supports text only and was evaluated in English.

15 OCT 2026↗ VISUAL DESIGN AS EDITABLE CODE

AesCode 8B

Microsoft's multimodal family turns content requirements and optional visual references into editable HTML/CSS documents. The 8B and 32B checkpoints derive from Qwen3-VL-8B-Instruct and Qwen3-VL-32B-Instruct respectively. They produce code, not raster images or video files. The reference provides composition and style, while the prompt remains the source of truth for text, figures and relationships. The verified public release is October 11, 2026; earlier repository creation is not its release date.

11 OCT 2026↗ VISUAL DESIGN AS EDITABLE CODE

AesCode 32B

Microsoft's multimodal family turns content requirements and optional visual references into editable HTML/CSS documents. The 8B and 32B checkpoints derive from Qwen3-VL-8B-Instruct and Qwen3-VL-32B-Instruct respectively. They produce code, not raster images or video files. The reference provides composition and style, while the prompt remains the source of truth for text, figures and relationships. The verified public release is October 11, 2026; earlier repository creation is not its release date.

11 OCT 2026↗

GUIA

AesCode 32B: Verification Protocol for Local and Self-Hosted Deployment Costs

An operational guide to auditing the real costs of AesCode 32B, distinguishing between technical specifications confirmed by Microsoft and economic variables that require internal estimation, given that no public API pricing exists for this model.

18 Oct 2026 ↗

ANALISIS

AesCode Infographics Content: What It Measures, How It Runs, and Why Direct Comparison Is Blocked

A methodological audit of the 'Content' metric within the AesCode benchmark. This analysis defines its role in evaluating semantic fidelity of code-generated infographics, its integration with other visual metrics, and the specific limitations that prevent direct comparison with other industry standards.

17 Oct 2026 ↗

ANALISIS

AesCode Infographics Chart: what the evidence lets us verify—and what is missing for comparison

Public documentation describes the Chart channel, reports results, and provides evaluation code. But the datasets are not published, limiting independent reproduction and interpretation of the scores.

16 Oct 2026 ↗

ANALISIS

AesCode Infographics Bound: What It Measures, How It Runs, and What It Cannot Compare

A methodological audit of the 'Bound' metric within Microsoft's AesCode evaluation suite. This analysis examines its role as a programmatic constraint in infographic generation, its integration with other metrics, and the limitations it imposes on cross-model comparability.

16 Oct 2026 ↗

ANALISIS

Microsoft and AI After the Reorganization: Teams, Models, and Controls

Microsoft brings research, model development, Copilot products, and distribution through Foundry together under one AI offering, but public sources do not make it possible to assign every internal responsibility. This guide separates what Microsoft announced from what it documented, and explains what to check for each model and access channel.

29 Sep 2026 ↗