Best AI model for recovering from shell errors

How well the model recovers after a failed terminal command instead of thrashing. Ranked by Arena agent_bash_recovery_steps, priced against live API rates. 29 models have a published score on this board.

Capability published 2026-09-08 · pricing retrieved 2026-09-10

Most capable
Claude Opus 5
Anthropic
$10.00 / 1M blended
100% of leader strength
anthropic/claude-opus-5
Best value
Claude Opus 5
Anthropic
$10.00 / 1M blended
100% of leader strength
anthropic/claude-opus-5
Budget
Claude Sonnet 5
Anthropic
$4.00 / 1M blended
62% of leader strength · 60% cheaper
anthropic/claude-sonnet-5
Best for agents
Claude Opus 5
Anthropic
$10.00 / 1M blended
100% of leader strength
anthropic/claude-opus-5

Top 25 models for recovering from shell errors

Rows marked frontier are Pareto-optimal — nothing we track is both stronger and cheaper. "Strength" rescales the board so 100% = parity with the leader.

#ModelProviderScoreStrength$/1MContextTools
1 Claude Opus 5
anthropic/claude-opus-5
Anthropic 0.1312 100% $10.001M tools
2 Claude Fable 5.1
anthropic/claude-fable-5.1
Anthropic 0.1071 82% $20.001M tools
3 Claude Fable 5
anthropic/claude-fable-5
Anthropic 0.0917 70% $20.001M tools
4 Claude Sonnet 5
anthropic/claude-sonnet-5
Anthropic 0.0813 62% $4.001M tools
5 Claude Opus 4.8
anthropic/claude-opus-4.8
Anthropic 0.0733 56% $10.001M tools
6 Grok 4.5
x-ai/grok-4.5
xAI 0.0640 49% $3.00500K tools
7 Claude Sonnet 4.6
anthropic/claude-sonnet-4.6
Anthropic 0.0616 47% $6.001M tools
8 DeepSeek V4 Pro 0813
deepseek/deepseek-v4-pro-0813
DeepSeek 0.0568 43% $1.571.048576M tools
9 DeepSeek V4 Pro 0423
deepseek/deepseek-v4-pro
DeepSeek 0.0568 43% $1.201.048576M tools
10 Grok 4.6
x-ai/grok-4.6
xAI 0.0549 42% $3.00500K tools
11 GPT-6 Astra
openai/gpt-6-astra
OpenAI 0.0533 41% $20.001.05M tools
12 GPT-5.6 Sol
openai/gpt-5.6-sol
OpenAI 0.0493 38% $4.001.05M tools
13 GPT-5.6 Terra
openai/gpt-5.6-terra
OpenAI 0.0451 34% $4.501.05M tools
14 Kimi K3
moonshotai/kimi-k3
Moonshot AI 0.0439 33% $6.001.048576M tools
15 GPT-5.6 Luna
openai/gpt-5.6-luna
OpenAI 0.0406 31% $0.451.05M tools
16 Qwen3.8 Max (0902)
qwen/qwen3.8-max-0902
Qwen (Alibaba) 0.0369 28% $3.001M tools
17 MiniMax M3
minimax/minimax-m3
MiniMax 0.0193 15% $0.531.048576M tools
18 Gemini 3.8 Flash
google/gemini-3.8-flash
Google 0.0079 6% $1.501.048576M tools
19 GLM 5.2
z-ai/glm-5.2
Z.ai (Zhipu) 0.0079 6% $1.491.048576M tools
20 DeepSeek V4 Flash 0731
deepseek/deepseek-v4-flash-0731
DeepSeek 0.0078 6% $0.101.31072M tools
21 DeepSeek V4 Flash 0423
deepseek/deepseek-v4-flash
DeepSeek 0.0078 6% $0.111.048576M tools
22 Qwen3.7 Max
qwen/qwen3.7-max
Qwen (Alibaba) -0.0048 -4% $2.211M tools
23 Qwen3.7 Plus
qwen/qwen3.7-plus
Qwen (Alibaba) -0.0157 -12% $0.561M tools
24 GLM 5.3
z-ai/glm-5.3
Z.ai (Zhipu) -0.0294 -22% $2.151.31072M tools
25 GLM 5.3 Flash
z-ai/glm-5.3-flash
Z.ai (Zhipu) -0.0505 -38% $0.241.31072M tools

Capability: Arena leaderboard dataset (CC-BY-4.0), Arena agent_bash_recovery_steps, published 2026-09-08. Pricing: OpenRouter, retrieved 2026-09-10. (input x 3 + output x 1) / 4.

What this measures: Human pairwise preference votes. Measures perceived answer quality on this category, not correctness on a fixed test set. For each model this is its score as a share of the board leader's score — 1.0 means parity.

Get this as JSON

curl -s https://agentleaderboards.com/api/v1/route/agent-recovery.json | jq .picks

No key, open CORS, refreshed daily. Set your own budget and constraints →

Other tasks