Qwen 2.5 7B

Open-weights LLM used as one of three student models for character training experiments

Neighborhood — ranked by edge-count

paper

concept

Qwen3-1.7B
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Smallest Qwen3 model tested; used in conscientiousness sweep example (Table 6)
Qwen3.5-9B
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Smallest model tested as evolver; produces harness updates comparable to Claude Opus 4.6 on SkillsBench
Qwen2.5-VL-7B
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Base vision-language model used to instantiate ATLAS.

cosine ≥ 0.65 · no typed edge

Entities in the same semantic neighborhood but without a typed relation to this one — candidates for new edges or unrecognized duplicates.

Qwen 3 0.6B Embeddingmethod0.828
Embedding model used to embed user messages for ridge regression analysis of persona drift causes
Qwen3-4Bconcept0.821
4B Qwen3 model tested in OCEAN benchmarks
Qwen3-235Bconcept0.813
One of the four frontier models evaluated; shows the largest robustness drop (-88%) and sigma surge (+744%)
Qwen3-32Bconcept0.803
Weak-tier open-source model exhibiting both harness activation failure and adherence failure, with 25.1% skill-load rate
Qwen3-14Bconcept0.796
14B Qwen3 model quantized to 4-bit NF4; tested in OCEAN benchmarks
Qwen3-235B-A22Bconcept0.793
Large open-source model used as anchor agent and anchor evolver; illustrates benchmark-dependent evolver performance
Qwen 2.5 7B has higher Elo scores for 'methodical' and 'formal' traits compared to Llama 3.1 8B which prefers 'colloquial'finding0.787
Model-specific baseline personality difference revealed by revealed preferences experiment
Qwen 35B (3B active params, score 4.38) outscores Hermes 405B (405B active params, score 1.75) by 2.5xfinding0.779
Parameters don't predict scores; 135x more parameters yields 60% lower score