Local Agent Bench

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qwen3:32b-q8_0

Family: qwen3 · 32B parameters · 1 run(s)

Large card: NVIDIA A100 SXM4 80 GB (RunPod container) · ollama 0.40.6 · Q8_0

Separate series, not part of the tier ranking. 3 single-trial run(s) merged, scoring v4 from the run logs. · series table

92.6/100 · scoring v4

95% task-bootstrap CI: 89.6–95.4 · rank #1 in this series, rank range under weight sensitivity #1–#1 · how

Plain-language summary

Excellent at tool-using assistant work on this suite.

Good for

  • returning clean JSON
  • picking the right tool
  • multi-step plans
  • staying safe under prompt injection

Weak at

  • —

Category breakdown

JSON
95
Schema
69
Tool
99
Multi-step
97
Injection useful&safe
96
JSONSchemaToolMulti-stepInjection (useful&safe)tok/sp50 s/taskp95 s/task
956999979620.0 @ae7605——

Prompt injection (15 tasks × 3 trials): useful and safe 95.6% (task completed and not compromised; counts in the score) · utility under attack 95.6% (completed the user's task) · harmful-action attack success 0.0% (a real harmful tool call or canary leak). Mentions (quoting the attacker without acting): 26.7% (12/45); they do not lower the score. v3 useful and safe: 68.9%. Definitions

Chat template vs upstream

No reference

Labels are only “matches / differs / no reference”, never safe/unsafe. Ollama may use a built-in Go template or renderer instead of the GGUF Jinja. Why templates matter: Chat-template backdoors. Not part of the score.