test(ai): screen smollm2/hermes3/mistral — none beat qwen2.5:3b
Pulled and benchmarked three more tool-capable CPU models looking for a better default. All score 0/12 (vs qwen2.5:3b at 2/12): in the multi-turn agent loop they leak the positional-in-tags dialect (<tools>run_shell 'cmd'</tools>) the parser can't recover, even when they emit clean structured tool_calls on a single-turn probe; smollm2 and mistral also wedge into repeating summaries. qwen3:4b could not be pulled — Ollama 0.3.9 is too old (HTTP 412), same as granite3.1-dense:2b. Upgrading Ollama is the highest-leverage next step to test the qwen3/granite3.x generation. qwen2.5:3b remains the default. Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
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@@ -95,7 +95,29 @@ band. **qwen2.5:3b stays the default** (best capability/latency); 0.5b is now a
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floor option for trivial tasks. Treat absolute scores as a *relative* regression
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yardstick, not a grade.
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Usable models: qwen2.5(-coder) 0.5b–7b, llama3.2:3b (all tool-capable). Rejected:
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### Candidate screening (2026-06-13) — can anything beat qwen?
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Pulled and benchmarked three more tool-capable models to look for a better
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default. None did — all 0/12, worse than qwen2.5:3b. The pattern repeats: in the
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multi-turn agent loop the weak models leak a **positional-in-tags** dialect
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(`<tools>run_shell 'cmd'</tools>`) that the parser can't recover, even when they
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emit clean structured `tool_calls` on a single-turn probe.
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| model | size | PASS | avg s | note |
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|---|---|---|---|---|
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| smollm2:1.7b | 1.8 GB | 0/12 | ~50 | wedges into a repeating fabricated summary |
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| hermes3:3b | 2.0 GB | 0/12 | ~47 | leaks `<tools>NAME "arg"</tools>` positional form |
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| mistral:7b | 4.1 GB | 0/12 | ~70 | clean call on probe, leaks prose-tags live; then wedges |
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`qwen3:4b` could not be pulled — **Ollama 0.3.9 is too old** (HTTP 412, "requires a
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newer version of Ollama"), same root cause as `granite3.1-dense:2b`. Upgrading
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Ollama would unlock the qwen3 / granite3.x generation and is the highest-leverage
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next step if we want to retest newer architectures.
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**Conclusion: qwen2.5:3b remains the default.** No CPU-runnable model on this
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Ollama version beats it.
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Usable models: qwen2.5(-coder) 0.5b–7b, llama3.2:3b, smollm2:1.7b, hermes3:3b,
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mistral:7b (all tool-capable; the last three still score 0/12 here). Rejected:
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`deepseek-r1` and `westenfelder/NL2SH` reject Ollama's `tools` field;
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`granite3.1-dense:2b` errors (`model not supported by your version of Ollama` — needs
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a newer Ollama).
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`granite3.1-dense:2b` and `qwen3:4b` need a newer Ollama (0.3.9 installed).
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