Most Reliable AI Agents. How they behave in real sessions.
A model can ace a test and still be frustrating to work with. This list uses Arena's signals from real agent sessions: did the task work, were tool calls valid, did shell commands succeed, and did the agent follow corrections.
Reliability ranking
Ranked by average position across four signals from Arena's real agent sessions.
As of November 3, 2026, GPT-6.1 Terra holds first place on the reliability board, with an average rank of 5.50 across 4 Arena signals, ahead of Claude Opus 5.5 (7.25).
Behavior in real sessions: outcomes, tool calls, shell use, steering. A model needs a rank on at least 3 of these 4 boards to be listed.
| Rank | Model | Average rank | Arena: task outcome | Arena: tool calls | Arena: shell reliability | Arena: steerability | Agreement | Week |
|---|---|---|---|---|---|---|---|---|
| 1 |  OpenAI · Proprietary | 5.50 | 10 | 2 | 3 | 7 | Boards disagree | – |
| 2 |  Anthropic · Proprietary | 7.25 | 1 | 24 | 2 | 2 | Boards disagree | – |
| 3 | Anthropic · Proprietary | 7.50 | 2 | 15 | 4 | 9 | Boards disagree | – |
| 4 | OpenAI · Proprietary | 7.50 | 5 | 6 | 14 | 5 | Boards disagree | – |
| 5 | Anthropic · Proprietary | 9.00 | 6 | 17 | 10 | 3 | Boards disagree | – |
| 6 | OpenAI · Proprietary | 9.25 | 9 | 3 | 19 | 6 | Boards disagree | – |
| 7 | Anthropic · Proprietary | 9.50 | 8 | 8 | 8 | 14 | Mostly agree | – |
| 8 | OpenAI · Proprietary | 10.75 | 16 | 12 | 5 | 10 | Boards disagree | – |
| 9 |  Moonshot AI · Proprietary | 12.25 | 21 | 1 | 15 | 12 | Boards disagree | – |
| 10 | Anthropic · Proprietary | 13.75 | 15 | 22 | 7 | 11 | Boards disagree | – |
| 11 |  Meta · Proprietary | 14.75 | 7 | 28 | 16 | 8 | Boards disagree | – |
| 12 | OpenAI · Proprietary | 15.75 | 28 | 16 | 6 | 13 | Boards disagree | – |
| 13 | OpenAI · Proprietary | 16.50 | 32 | 7 | 11 | 16 | Boards disagree | – |
| 14 |  Google · Proprietary | 18.25 | 3 | 23 | 46 | 1 | Boards disagree | – |
| 15 | Anthropic · Proprietary | 18.75 | 34 | 25 | 1 | 15 | Boards disagree | – |
| 16 |  xAI · Proprietary | 19.25 | 18 | 11 | 13 | 35 | Boards disagree | – |
| 17 | Meta · Proprietary | 19.75 | 22 | 14 | 26 | 17 | Boards disagree | – |
| 18 | Google · Proprietary | 20.25 | 4 | 30 | 43 | 4 | Boards disagree | – |
| 19 |  DeepSeek · Open weights | 21.50 | 17 | 27 | 21 | 21 | Boards disagree | – |
| 20 | Moonshot AI · Open weights | 22.75 | 20 | 4 | 42 | 25 | Boards disagree | – |
| 21 | Meta · Proprietary | 23.25 | 11 | 43 | 20 | 19 | Boards disagree | – |
| 22 | xAI · Proprietary | 23.50 | 36 | 20 | 12 | 26 | Boards disagree | – |
| 23 |  Xiaomi · Open weights | 24.00 | 12 | 37 | 25 | 22 | Boards disagree | – |
| 24 | Google · Proprietary | 24.25 | 31 | 29 | 9 | 28 | Boards disagree | – |
| 25 |  Z.ai · Open weights | 24.50 | 25 | 5 | 41 | 27 | Boards disagree | – |
| 26 | DeepSeek · Open weights | 24.75 | 14 | 21 | 35 | 29 | Boards disagree | – |
| 27 | Anthropic · Proprietary | 26.25 | 26 | 44 | 17 | 18 | Boards disagree | – |
| 28 | OpenAI · Proprietary | 26.75 | 41 | 13 | 30 | 23 | Boards disagree | – |
| 29 | Z.ai · Open weights | 27.50 | 24 | 9 | 44 | 33 | Boards disagree | – |
| 30 |  Tencent · Open weights | 28.75 | 19 | 34 | 38 | 24 | Boards disagree | – |
| 31 | DeepSeek · Open weights | 29.00 | 39 | 18 | 27 | 32 | Boards disagree | – |
| 32 | Xiaomi · Open weights | 30.50 | 13 | 50 | 39 | 20 | Boards disagree | – |
| 33 | Google · Proprietary | 30.50 | 38 | 26 | 18 | 40 | Boards disagree | – |
| 34 | Z.ai · Open weights | 30.75 | 27 | 10 | 48 | 38 | Boards disagree | – |
| 35 |  Alibaba · Proprietary | 32.50 | 23 | 40 | 37 | 30 | Boards disagree | – |
| 36 |  StepFun · Proprietary | 33.50 | 35 | 19 | 49 | 31 | Boards disagree | – |
| 37 |  Reflection · Open weights | 37.00 | 42 | 41 | 22 | 43 | Boards disagree | – |
| 38 |  MiniMax · Open weights | 37.00 | 29 | 33 | 45 | 41 | Boards disagree | – |
| 39 | Alibaba · Proprietary | 38.25 | 45 | 38 | 23 | 47 | Boards disagree | – |
| 40 | Google · Proprietary | 38.50 | 47 | 36 | 29 | 42 | Boards disagree | – |
| 41 |  Mistral · Proprietary | 38.50 | 33 | 55 | 32 | 34 | Boards disagree | – |
| 42 | Meta · Proprietary | 38.75 | 40 | 31 | 36 | 48 | Boards disagree | – |
| 43 | Meta · Proprietary | 40.25 | 44 | 32 | 40 | 45 | Boards disagree | – |
| 44 | Alibaba · Open weights | 40.25 | 37 | 35 | 50 | 39 | Boards disagree | – |
| 45 | Alibaba · Open weights | 40.75 | 30 | 42 | 54 | 37 | Boards disagree | – |
| 46 | Alibaba · Proprietary | 41.50 | 43 | 49 | 28 | 46 | Boards disagree | – |
| 47 | MiniMax · Open weights | 43.25 | 50 | 46 | 33 | 44 | Boards disagree | – |
| 48 | Xiaomi · Open weights | 43.50 | 46 | 45 | 34 | 49 | Boards disagree | – |
| 49 |  Thinking Machines · Open weights | 45.25 | 54 | 48 | 24 | 55 | Boards disagree | – |
| 50 | Thinking Machines · Open weights | 46.25 | 53 | 47 | 31 | 54 | Boards disagree | – |
| 51 | Tencent · Open weights | 47.25 | 48 | 53 | 52 | 36 | Boards disagree | – |
| 52 |  NVIDIA · Open weights | 49.25 | 52 | 39 | 53 | 53 | Boards disagree | – |
| 53 | Mistral · Open weights | 49.50 | 49 | 51 | 47 | 51 | Mostly agree | – |
| 54 | NVIDIA · Open weights | 51.50 | 51 | 54 | 51 | 50 | Mostly agree | – |
| 55 |  Upstage · Proprietary | 53.50 | 55 | 52 | 55 | 52 | Mostly agree | – |
The boards behind this ranking
- Arena: task outcome by ArenaHow often people say the task worked. 55 models. Updated Oct 28.
- Arena: tool calls by ArenaHow rarely the agent calls tools that do not exist. 55 models. Updated Oct 28.
- Arena: shell reliability by ArenaHow reliably shell commands succeed. 55 models. Updated Oct 28.
- Arena: steerability by ArenaHow well the agent follows corrections mid-task. 55 models. Updated Oct 28.
Sources: Arena leaderboard dataset (CC BY 4.0; we keep each model's best configuration and renumber), Terminal-Bench, Vals AI benchmarks. Re-read every week. How we calculate it. eSEOspace does not run these benchmarks and has not tested these models for this ranking. The order comes from the formula, and no one can pay for a position. eSEOspace is a member of the Claude Partner Network, and Claude is one of the models ranked here.
How to read it
How to read this ranking
Read the average rank first: lower is better. Then look at the Agreement column. A model the boards agree on is a safer bet than one that is first on one board and twentieth on another.
Select a model's name to see its score on each board and the harness used. Use the tabs to switch from the overall list to coding, knowledge work or reliability, and the filters to narrow by lab or to open-weight models.
Other views: Overall. Coding. Knowledge work. Methodology.
Limits
What this ranking can't tell you
A high average tells you a model did well on these tests. It does not prove it will handle your work, your data or your tools. Run your own trial on real tasks before you commit.
Boards do not cover every model. A model missing from a tough board can look better than one that was tested and scored lower, which is why we show how many boards each model appears on and whether they agree.
Benchmarks can also be gamed. Researchers have shown that agents can sometimes score well by exploiting a test rather than solving it, so treat a small gap between two models as a tie.
All four signals on this tab come from one publisher, Arena, and from the people who use its site. Treat it as one view of behavior rather than an independent consensus, and read Arena's own notes on how the signals are built.
FAQ
Common questions
What makes an AI agent reliable?
Why can a top model rank lower here?
Next steps
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