ARC Prize published Claude Fable 5.2’s ARC-AGI results on 9 November. The same day, Anthropic announced on X that Fable 5.2 and Claude Mythos 5.2 are available. ARC Prize tested Fable 5.2 with two harnesses at five reasoning effort levels, ten configurations in total.

A harness is the program that controls an agent: it gives the model its tools and runs its steps. ARC-AGI-3 tasks are games, and a single game can last up to the 12-hour time limit. In ARC Prize’s Standard harness, the model can keep notes of its own choosing for the whole game.

The Provider Adapter harness instead preserves the model’s opaque reasoning state between requests. In long conversations it uses compaction. This lets the model reuse its prior work, ARC Prize said.

The gap appears at every reasoning effort level

The table shows ARC-AGI-3 results with both harnesses. The best scores, 81.2 per cent and 97.7 per cent, came at different reasoning effort levels, so they cannot be compared directly. At the same XHigh level, the gap is 16.1 percentage points.

Source: ARC Prize, verified results on the semi-private test set, 9 November 2026.

ARC Prize does not say which Provider Adapter feature explains the gap: preserving reasoning state or compaction. This suggests that comparing ARC-AGI-3 scores requires knowing which harness was used.

At Max, the Standard harness reached only 65.7 per cent. In 28 of 55 games the run lasted the full 12-hour time limit, ARC Prize said. In those games, the time limit constrained the test’s progress.

The gap also shows in individual public demo games. In TU93 and BP35, the Standard harness scored 2.2 per cent at XHigh, while Provider Adapter scored 100 per cent. Fable 5.2’s best results at XHigh were 98.5 per cent on ARC-AGI-1 and 93.8 per cent on ARC-AGI-2.

Artificial Analysis: top of the index, but not in every benchmark

Benchmarking company Artificial Analysis said on X that Fable 5.2 at Max took first place in its Intelligence Index v5 with 65 points. The closest other models are Gemini 4 Carbon (High, 60) and Claude Opus 5.5 (Max, 59). On the Terminal-Bench 4.0 coding benchmark, Fable 5.2 scored 60 per cent, level with Opus 5.5. Kimi K3.1 Pro scored 67 per cent.

At Max, an index task cost an average of $26.5, about 2.6 times the cost for Opus 5.5 ($10.0), Artificial Analysis said. At High and XHigh, Fable 5.2 scored 62 points, more than any other model at any level.

Fable 5.2 costs $8 per 1 million input tokens and $40 per 1 million output tokens. Artificial Analysis said this is 20 per cent less than Fable 5.1’s price. The context window is 1 million tokens, and the model accepts text and images.