RL Environments and the Hierarchy of Agentic Capabilities
Our RL environment run on 9 models revealed the core capabilities all agents need to master: tool use, planning, adaptability, groundedness, and common sense.
Agentic Healthcare
DAYJOB: Healthcare
DAYJOB: Healthcare evaluates long-horizon healthcare agents across clinical, operational, payer, pharmacy, and compliance workflows. Rather than telling models exactly what to do, it asks whether agents can figure out what needs to be done, and reason through it until the end.
DAYJOB: Healthcare Leaderboard
1
Claude
Opus 5.5 (Adaptive/Max)
24.7
%
1
GPT
6 Astra (Max reasoning)
11.6
%
1
Claude
Fable 5.1 (Adaptive/Max)
9.6
%
1
Gemini
4 Argon (High reasoning)
9.6
%
1
Claude
Opus 5 (Adaptive/Max)
8.4
%
1
Grok
4.7 (xHigh reasoning)
8.4
%
1
Muse
Spark 1.3 (Max reasoning)
7.8
%
1
Claude
Fable 5 (Adaptive/Max)
5.6
%
1
GPT
6 Sol (Max reasoning)
3.6
%
1
Grok
4.6 (xHigh reasoning)
2.8
%
1
Muse
Spark 1.2 (xHigh reasoning)
2
%
1
Qwen
3.8 Max (xHigh reasoning)
2
%
1
GPT
5.6 Sol (Max reasoning)
1.6
%
1
GPT
5.6 Terra (xHigh reasoning)
1.6
%
1
Kimi
K3 (Max reasoning)
1.2
%
1
Gemini
3.8 Flash (High reasoning)
0.8
%
1
Hy
Hy4 Preview (High reasoning)
0.8
%
1
GLM
5.3 (Max reasoning)
0.4
%
1
GLM
5.3 Flash (Max reasoning)
0.4
%
1
GPT
5.6 Luna (Max reasoning)
0.4
%
1
DeepSeek
V4 Pro (Max reasoning)
0.4
%
1
Hy
Hy3 (High reasoning)
0.4
%
1
Claude
Sonnet 5 (Adaptive/Max)
0
%
1
Gemini
3.7 Flash (High reasoning)
0
%
1
Inkling
Inkling (Max reasoning)
0
%
1
DeepSeek
V4 Flash (Max reasoning)
0
%
1
Gemini
3.1 Pro (High reasoning)
0
%
1
Kimi
K2.7 Code (Max reasoning)
0
%
1
Muse
Glimmer 30B (xHigh reasoning)
0
%
1
Nemotron
3 Ultra
0
%
1
Mistral
Large 3
0
%
1
GPT
6 Luna (Max reasoning)
0
%
VIEW ALL BENCHMARKS
Agentic Coding
sudo L7
Coding agents are getting very good at being L3s. But do they have the judgment to become L7s? Across 60 tasks, agents must navigate unfamiliar systems, choose architectures, spot hidden risks, and know when technically correct code is still the wrong thing to ship.
Rank
Model
Score
41.7
%
Claude Sonnet 5.5 (Adaptive/Max)
Anthropic
41.7
%
Claude Opus 5.5 (Adaptive/Max)
Anthropic
33.9
%
GPT 6 Astra (Max)
OpenAI
31.1
%
Claude Fable 5.1 (Adaptive/Max)
Anthropic
28.9
%
GPT 6.1 Sol (Max)
OpenAI
20.6
%
Qwen 3.8 Max
Alibaba Cloud
Agentic Finance
DAYJOB: Finance
DAYJOB: Finance measures long-horizon finance agents across corporate finance, banking, credit, investing, and real assets. It's built around the messy reality of knowledge work: realistic requests, complex environments, and end-to-end professional judgment.
Rank
Model
Score
23.9
%
Claude Opus 5.5 (Adaptive/Max)
Anthropic
21.5
%
GPT 6 Astra (Max)
OpenAI
20.3
%
Gemini 4 Argon (High)
Google
19.8
%
Claude Fable 5.1 (Adaptive/Max)
Anthropic
14.8
%
Muse Spark 1.3 (Max)
Meta
14.5
%
Grok 4.7 (xHigh)
xAI