Hugging Face trending modelspublished Sep 5, 08:21 UTC (10d ago)ingested Sep 13, 16:57 UTCTokenRhythm

TokenRhythm/NeoHorse-1-4B — new model trending #30 on Hugging Face

AI summary · glm-5.3

TokenRhythm releases NeoHorse-1-4B, an Apache-2.0 agentic fine-tune of Qwen3.5-4B claiming +5.93 benchmark macro-average gain.

NeoHorse-1-4B is a roughly 4B-parameter text-only causal language model post-trained by TokenRhythm from Qwen/Qwen3.5-4B for agent harnesses, tool use, coding, and instruction following. It applies routing-guided curriculum SFT and routing-guided on-policy distillation over execution trajectories as an early prototype toward recursive self-improvement (RSI). The release reports a 64.87 macro average across ten benchmarks versus 58.94 for Qwen3.5-4B (+5.93) and is distributed under Apache-2.0, trending #30 on Hugging Face.

4B text-only model fine-tuned from Qwen3.5-4B by TokenRhythm
Routing-guided curriculum SFT and on-policy distillation from agent trajectories
Reports 64.87 macro average over ten benchmarks, +5.93 over base
Apache-2.0 weights positioned as an early recursive self-improvement prototype

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Tagsmodel-release qwen agentic post-training open-weights llm recursive-self-improvement 4b

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<h1>NeoHorse-1-4B</h1>

<p><b>Towards Recursive Self-Improvement via Agentic Post-Training with Routing Harness.</b></p>

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<a href="https://arxiv.org/abs/2609.08183"><b>Technical Report</b></a>

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NeoHorse-1-4B is a 4B causal language model and an initial prototype on the path toward **recursive self-improvement (RSI)**. It is post-trained from Qwen3.5-4B for text-based agent harnesses, tool use, coding, and instruction following.

Derived from [Qwen/Qwen3.5-4B](https://huggingface.co/Qwen/Qwen3.5-4B) and fine-tuned by TokenRhythm. This release contains **language-model weights only** and is repackaged for text-only inference. Vision weights are not included. Repackaging changes configuration and tensor key names, without changing the fine-tuned tensor values.

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## Highlights

- **Path toward RSI:** the routing harness assigns tasks to a heterogeneous model pool, records tool interactions and outcomes, estimates capability demand, and uses capability-level feedback to shape the next training mixture. Updated models can return to the harness, closing a prototype evaluation–selection–update loop; extending this loop across successive iterations is the next step toward RSI.

- **Agentic post-training framework:** the associated research explores routing-guided curriculum SFT and routing-guided on-policy distillation to turn execution trajectories into training signal while preserving execution and harness context around each response.

- **Data quality:** exact and near-duplicate removal, evaluation decontamination, structural validation, six-dimensional semantic evaluation, and subscene-level Scene/Goal/Outcome labeling.

- **Broad gains:** 64.87 macro average across ten benchmarks versus 58.94 for Qwen3.5-4B (**+5.93**).

## Model Details

<th style="padding:9px 10px;text-align:left;border-bottom:2px solid #f97316;color:#c2410c;background:rgba(249,115,22,.10)">Property</th>

<th style="padding:9px 10px;text-align:left;border-bottom:2px solid #f97316;color:#c2410c;background:rgba(249,115,22,.10)">Value</th>

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<td style="padding:9px 10px;border-bottom:1px solid rgba(249,115,22,.16);font-weight:600">Model family</td>

<td style="padding:9px 10px;border-bottom:1px solid rgba(249,115,22,.16)">NeoHorse Agent-Native Causal Language Model</td>

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<td style="padding:9px 10px;border-bottom:1px solid rgba(249,115,22,.16);font-weight:600">Parameters</td>

<td style="padding:9px 10px;border-bottom:1px solid rgba(249,115,22,.16)">Approximately <strong>4B</strong></td>

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<td style="padding:9px 10px;border-bottom:1px solid rgba(249,115,22,.16);font-weight:600">Base model</td>

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<td style="padding:9px 10px;border-bottom:1px solid rgba(249,115,22,.16);font-weight:600">Post-training</td>

<td style="padding:9px 10px;border-bottom:1px solid rgba(249,115,22,.16)">Routing-guided agentic post-training</td>

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<td style="padding:9px 10px;border-bottom:1px solid rgba(249,115,22,.16);font-weight:600">Interface</td>

<td style="padding:9px 10px;border-bottom:1px solid rgba(249,115,22,.16)">Text input and text output</td>

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Text extracted automatically; images, tables and formatting may be missing. Original: https://huggingface.co/TokenRhythm/NeoHorse-1-4B