Qwen / MODEL EVIDENCE

Qwen3.5-4B

2 benchmarks · 2 observations · 2 sources · released 2026-02-24

Scores at a glance

2 benchmarks · large dot: Qwen3.5-4B; small dots: closest models where reported

Closest models by score

Similar positions on shared benchmark leaderboards. Smaller gaps are closer.

26.1 percentile-point gap

2 of 2 shared benchmark comparisons

How similarity is measured

Mean absolute gap in percentile positions on shared benchmark settings; lower is closer. At least 60% overlap is required, with a minimum of three when available. Independent evaluations are used when there are at least three; otherwise published report comparisons are used. Repeated model observations within one setting are averaged before ranking. Writing-style traits and composite indices are excluded. This describes similarity, not an overall quality ranking.

POST-TRAINING / SOURCE DISCLOSURE

What the Qwen3.5 post-trained family report says

The reviewed card describes progressively harder agent environments and asynchronous reinforcement-learning infrastructure. Its architecture and multimodal training are documented separately from its post-training objective.

  • Agent environments with increasing task complexity
  • Large-scale asynchronous reinforcement learning

The card reviewed is for 397B-A17B. It does not name a complete policy objective; the background links do not establish that every Qwen3.5 checkpoint used the same optimizer.

  1. Qwen3.5-397B-A17B model card ↗

    Qwen Team · 2026

Sources

Every plotted observation links to its evaluation. Reported configurations, benchmark versions and task subsets can differ; similarity describes shared scores, not training lift.

  1. OTIS Mock AIME 2024-2025 ↗

    Epoch AI

  2. Scale Labs — evaluation methodology and results ↗

    Scale Labs / SEAL · 2026

Names used in source tables

Qwen3.5-4B · Qwen3.5-4B (Thinking)