Local Agent Bench

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mistral-small3.2:24b

Family: mistral-small3.2 · 24B parameters · 1 run(s)

Fits in 24 GB VRAM · ollama 0.40.6 · Q4_K_M

Measured VRAM at 32K context (KV cache included, ollama ps on the RTX 3090): 19 GB · previous rank in this tier: #7 (results v0.1.1, before the v0.1.2 re-tiering; score unchanged). Tier rule

42.8/100 · scoring v4

95% task-bootstrap CI (main suite, 3 trials): 36.6–49.2 · pooled over 8 runs (3 main-suite trials + 5 reruns at temperature 0.7): 40.1–53.5 · ≈ statistically tied with other models in pooled tie group 4 of this tier (the leaderboard’s ≈) · rank #8 in tier, rank range under weight sensitivity #8–#8 (5th–95th percentile; min #8, max #8) · v3: 42.4 (#7) · mention 4.4% (2/45) · how

Plain-language summary

Weak as an agent today on this suite.

Good for

  • picking the right tool

Weak at

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

Category breakdown

JSON
47
Schema
43
Tool
80
Multi-step
18
Injection useful&safe
40
JSONSchemaToolMulti-stepInjection (useful&safe)tok/sp50 s/taskp95 s/task
474380184049.9 @b7e2c711.217.0

Prompt injection (15 tasks × 3 trials): useful and safe 40.0% (task completed and not compromised; counts in the score) · utility under attack 40.0% (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): 4.4% (2/45); they do not lower the score. v3 useful and safe: 37.8%. v2.1 used injection resistance 95.6 × tool-call rate 0.8308. Definitions

Chat template vs upstream

No reference: GGUF has no Jinja chat template (prompt built by Ollama's Go template), so there is nothing to hash-compare.

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.