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Vals Science Index leaderboard

GPT-6 Astra leads
65.1%
models measured
20
lead over #2
+5.5 pts
median
38.3%

Leader on Vals Science Index · read October 22

On October 22, 2026, 20 of our catalog's models had a Vals Science Index result, and OpenAI GPT-6 Astra led with 65.1%, ahead of OpenAI GPT-6.1 Sol at 59.6%.

One measure of agentic science: biology data investigation, mechanism discovery and research workflows, weighted equally by Vals AI.

Role in the index

Vals Science Index is shown as published and does not feed any of our indexes. Read the methodology

20 models with a result

Original board: Vals AI boards
Vals Science Index results for models in the catalog
# Model Result Cost per test Duration, as printed Evidence Coding index Output $/Mtok
1 GPT-6 AstraOpenAI 65.1% $8.03 40m 37s 85.1 $50.00
2 GPT-6.1 SolOpenAI 59.6% $1.36 33m 11s 82.4 $10.00
3 Claude Sonnet 5.5Anthropic 59.1% $13.24 1h 09m 87.3 $10.00
4 Claude Opus 5.5Anthropic 58.7% $9.13 1h 00m 88.8 $20.00
5 Gemini 4 ArgonGoogle 55.4% $18.40 57m 00s 81.0 $10.00
6 Claude Opus 5Anthropic 47.9% $13.04 1h 02m 83.0 $25.00
7 GPT-6 SolOpenAI 45.0% $2.31 31m 16s 76.0 $10.00
8 GPT-5.6 SolOpenAI 41.5% $3.40 43m 32s 73.5 $20.00
9 Muse WonderMeta 39.1% $8.74 43m 08s 71.9 $20.00
10 Claude Haiku 5.5Anthropic 38.5% $1.86 39m 58s 70.7 $0.50
11 Grok 4.6xAI 38.1% $2.45 40m 10s 65.7 $6.00
12 Gemini 3.8 FlashGoogle 35.8% $2.98 22m 00s 61.6 $3.75
13 Grok 4.7xAI 34.8% $7.12 40m 34s 66.7 $6.00
14 Ember-1Fireworks 31.8% $10.99 1h 18m 52.6 $15.00
15 MiMo-V2.6-FlashXiaomi 31.7% $0.12 1h 41m 54.7 $0.28
16 DeepSeek V4.1 FlashDeepSeek 29.6% $0.29 1h 07m 62.5 $0.84
17 Step 5 PreviewStepFun 29.6% $1.78 1h 07m 61.1 $2.70
18 GPT-6 LunaOpenAI 28.4% $0.11 30m 15s 57.3 $0.50
19 Gemini 3.1 Pro PreviewGoogle 27.4% $2.56 18m 03s 32.3 $12.00
20 GPT-5.6 LunaOpenAI 25.3% $0.26 50m 00s 58.0 $1.20

Only models in our catalog are listed, and each appears once with its best published run. 137 rows were read from the source on October 22, 2026, and rows that match no catalog model are left out. Cost per test is what Vals AI reports one test cost on the run behind the result, in US dollars. Every other column is a figure the board publishes for the same run.