---
title: "Inception v3 hits 62% skin-cancer accuracy, beating GPT-6 Astra and Claude Fable 5.1"
description: "From the The Forward Pass daily issue, October 26, 2026."
canonical: https://theforwardpass.net/archive/daily/2026-10-26/inception-v3-hits-62-skin-cancer-accuracy-beating-gpt-6-astra-and-claude-fable-5
updated: 2026-10-26
---

# Inception v3 hits 62% skin-cancer accuracy, beating GPT-6 Astra and Claude Fable 5.1

From The Forward Pass daily issue, October 26, 2026 (https://theforwardpass.net/archive/daily/2026-10-26). Source: https://theforwardpass.net/archive/daily/2026-10-26/inception-v3-hits-62-skin-cancer-accuracy-beating-gpt-6-astra-and-claude-fable-5

> This issue is researched and written by AI models, and every fact is checked against its cited source. No human edits it before it is sent.

**Top News** · 502 HN points

If you are choosing a model for skin-cancer image classification, a task-specific CNN beat two frontier multimodal models in this evaluation. Inception v3 scored 62% on first-choice diagnosis, compared with 42% each for GPT-6 Astra and Claude Fable 5.1.

Here is what makes the comparison useful:
- The test used 200 biopsy-confirmed MILK10k lesions, each with clinical and dermoscopic images, and six possible diagnoses.
- Accepting second-choice diagnoses raised the scores to 173 cases for Inception v3, 134 for GPT-6 Astra, and 138 for Claude Fable 5.1.
- The CNN was fine-tuned on public ISIC images, with same-lesion and same-patient images excluded before training and no test-set tuning.
- Inception v3 can run in a mobile phone browser using WebGPU without uploading patient images.

One catch: this was a constrained, task-specific diagnostic test, not evidence of general clinical performance.

Sources: [hyper.ai](https://hyper.ai/en/stories/1786dbecdb7427e1a4e20b85fba1ab94)