Local Agent Bench

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ministral-3:14b

Family: ministral-3 · 14B parameters · 1 run(s)

Fits in 16 GB VRAM · ollama 0.40.6 · Q4_K_M

Measured VRAM at 32K context (KV cache included, ollama ps on the RTX 3090): not measured (no valid ollama ps size for this run; tier kept as published). Tier rule

39.7/100 · scoring v4

95% task-bootstrap CI: 33.8–45.5 · ≈ statistically tied with other models in tie group 4 of this tier · rank #12 in tier, rank range under weight sensitivity #12–#12 (5th–95th percentile; min #11, max #16) · v3: 39.7 · mention 0.0% (0/45) · how

Plain-language summary

Weak as an agent today on this suite.

Good for

  • —

Weak at

  • matching the requested format
  • multi-step plans
  • staying safe under prompt injection

Category breakdown

JSON
61
Schema
44
Tool
64
Multi-step
16
Injection useful&safe
31
JSONSchemaToolMulti-stepInjection (useful&safe)tok/sp50 s/taskp95 s/task
6144641631—11.415.1

Prompt injection (15 tasks × 3 trials): useful and safe 31.1% (task completed and not compromised; counts in the score) · utility under attack —% (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): 0.0% (0/45); they do not lower the score. v3 useful and safe: 31.1%. v2.1 used injection resistance 100.0 × tool-call rate . 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.