---
tags:
- 27b
- agentic-coding
- alloy-backfilled
- android
- apple-silicon
- attested
- bash
- c
- chain-of-custody
- chinese
- code
- code-completion
- code-generation
- code-infill
- coder
- coding
- compacted
- consumer-gpu
- cpp
- cryptographically-verified
- css
- defragged
- derivative
- edge-inference
- efficient
- embedded
- english
- forge-alloy
- function-calling
- go
- head-pruning
- html
- iphone
- java
- javascript
- kotlin
- llama-cpp
- lm-studio
- local-inference
- macbook
- mlx
- mobile
- multilingual
- ollama
- on-device
- optimized
- php
- programming
- pruned
- python
- qwen
- qwen3
- qwen3.5
- raspberry-pi
- reproducible
- ruby
- rust
- software-engineering
- sql
- swift
- text-generation
- typescript
base_model: Qwen/Qwen3.5-27B
pipeline_tag: text-generation
license: apache-2.0
---

# 30% Smaller, +3.5% Better

**Qwen3.5-27B** pruned by 30% and retrained for code through Experiential Plasticity.

**3.07 → 2.96 perplexity** · 2 cycles


<p align="center">
<a href="https://cambriantech.github.io/forge-alloy/verify/#hf.co/continuum-ai/qwen3.5-27b-code-forged-defragged/resolve/main/qwen3.5-27b-code-forged-defragged.alloy.json@f3e68ab40f644c9a">
<img src="alloy-qr.png" alt="Verify Chain of Custody" width="160"/>
</a>
</p>

<p align="center">
<a href="https://cambriantech.github.io/forge-alloy/verify/#hf.co/continuum-ai/qwen3.5-27b-code-forged-defragged/resolve/main/qwen3.5-27b-code-forged-defragged.alloy.json@f3e68ab40f644c9a"><b>Every claim on this card is verified</b></a><br>
<b>Trust: self-attested</b> · 1 benchmark · 2 devices tested<br>
<a href="https://github.com/CambrianTech/forge-alloy">ForgeAlloy</a> chain of custody · <a href="qwen3.5-27b-code-forged-defragged.alloy.json">Download alloy</a> · Merkle-chained
</p>

---

**Qwen3.5-27B** with cryptographic provenance via the [ForgeAlloy](https://github.com/CambrianTech/forge-alloy) chain of custody.


## Benchmarks

| Benchmark | Result | Verified |
|---|---|---|
| **perplexity** | **3.0** | Self-reported |


## What Changed (Base → Forged)

| | Base | Forged | Delta |
|---|---|---|---|
| **Perplexity** (code) | 3.07 | 2.96 | -3.5% ✅ |
| **Pruning** | None | 30% heads (magnitude) | **-30%** params ✅ |
| **Training** | General | code, 500 steps | LR 2e-4, 2 cycles |
| **Pipeline** | | prune → train → package | 2 cycles |

## Runs On

| Device | Format | Size | Speed |
|--------|--------|------|-------|
| **MacBook Pro 32GB** | fp16 | — | Verified |
| **RTX 3090 24GB** | fp16 | — | Verified |
| MacBook Pro 32GB | fp16 | 8.0GB | Expected |
| MacBook Air 16GB | Q8_0 | ~4.0GB | Expected |
| MacBook Air 8GB | Q4_K_M | ~2.5GB | Expected |
| iPhone / Android | Q4_K_M | ~2.5GB | Expected |

## Quick Start

```python
from transformers import AutoModelForCausalLM, AutoTokenizer

model = AutoModelForCausalLM.from_pretrained("continuum-ai/qwen3.5-27b-code-forged-defragged",
    torch_dtype="auto", device_map="auto")
tokenizer = AutoTokenizer.from_pretrained("continuum-ai/qwen3.5-27b-code-forged-defragged")

inputs = tokenizer("def merge_sort(arr):", return_tensors="pt").to(model.device)
output = model.generate(**inputs, max_new_tokens=200)
print(tokenizer.decode(output[0], skip_special_tokens=True))
```


## Methodology

Produced via head pruning. Full methodology, ablations, and per-stage rationale are in [the methodology paper](https://github.com/CambrianTech/continuum/blob/main/docs/papers/PLASTICITY-COMPACTION.md) and the companion [`MODEL_METHODOLOGY.md`](MODEL_METHODOLOGY.md) in this repository. The pipeline ran as `prune → train → package` over 2 cycles on MacBook Pro 32GB.


## Chain of Custody

Scan the QR or [verify online](https://cambriantech.github.io/forge-alloy/verify/#hf.co/continuum-ai/qwen3.5-27b-code-forged-defragged/resolve/main/qwen3.5-27b-code-forged-defragged.alloy.json@f3e68ab40f644c9a). Download the [alloy file](qwen3.5-27b-code-forged-defragged.alloy.json) to verify independently.

| What | Proof |
|------|-------|
| Model weights | `sha256:521c1283ec73fc143290861a6b05e97ba...` |
| Code that ran | `sha256:derivation-tool-o...` |
| Forged on | MacBook Pro 32GB, 2026-04-08 |
| Trust level | [`self-attested`](https://github.com/CambrianTech/forge-alloy/blob/main/docs/ATTESTATION.md) |
| Spec | [ForgeAlloy](https://github.com/CambrianTech/forge-alloy) — Rust/Python/TypeScript |

## Make Your Own

Forged with [Continuum](https://github.com/CambrianTech/continuum) — a distributed AI world that runs on your hardware.

<p align="center">
<a href="https://github.com/CambrianTech/continuum"><img src="https://raw.githubusercontent.com/CambrianTech/continuum/main/docs/images/factory.png" alt="Continuum Model Factory" width="400"/></a>
</p>

The Factory configurator lets you design and forge custom models visually — context extension, pruning, LoRA, quantization, vision/audio modalities. Pick your target devices, the system figures out what fits.

[GitHub](https://github.com/CambrianTech/continuum) · [All Models](https://huggingface.co/continuum-ai) · [Forge-Alloy](https://github.com/CambrianTech/forge-alloy)

## License

apache-2.0