Benchmarks / Composite

Vals RSI Index v1.1: Pre-training: Compression

Can a model do the research that builds the next model? Autonomous LLM R&D scored against frozen published, human, and frontier-model references. Published Pre-training: Compression score in percentage points.

25models
–Open Index weight
2026-10-15last updated
Vals AIpublisher

Vals RSI Index v1.1: Pre-training: Compression

Higher is better · best effort per model

Chart settings
25 of 25 selected

full table below

#ModelEffortScoreCost / taskHarness
1Opus 5.5max46.5%––
2Gemini 4max44.7%––
3Fable 5.1max44.3%––
4GPT-6.1 Solmax43.5%––
5GPT-6 Astramax42.6%––
6Opus 5max42.6%––
7GPT-6 Solmax42.3%––
8GPT-5.6 Solmax41.0%––
9Fable 5max38.3%––
10Opus 4.8max38.3%––
11Grok 4.6max37.8%––
12Wonder Fullmax35.4%––
13Qwen 3.8 Maxmax35.3%––
14GLM 5.3max33.4%––
15Kimi K3max33.3%––
16Opus 4.7max31.4%––
17GPT-5.5xhigh29.2%––
18Gemini 3.8 Flashmax29.0%––
19GPT-5.2xhigh28.7%––
20Grok 4.7max27.9%––
21GPT-5.4xhigh25.2%––
22Gemini 3.7 Flashmax25.0%––
23Muse Spark 1.3max23.1%––
24Opus 4.5high22.3%––
25Kimi K2.5max0.0%––