Qwen3 is the latest generation of large language models in Qwen series, offering a comprehensive suite of dense and mixture-of-experts (MoE) models. Built upon extensive training, Qwen3 delivers groundbreaking advancements in reasoning, instruction-following, agent capabilities, and multilingual support, with the following key features: - Uniquely support of seamless switching between thinking mode (for complex logical reasoning, math, and coding) and non-thinking mode (for efficient, general-purpose dialogue) within single model, ensuring optimal performance across various scenarios. - Significantly enhancement in its reasoning capabilities, surpassing previous QwQ (in thinking mode) and…
Open-weight model · Text generation
qwen3-4b-ablation-poe-no-base
by Yu OP12138/qwen3-4b-ablation-poe-no-base
The full ImmuneCoT method fuses the two safety branches with a Base-adjusted product-of-experts Qimm(v) ∝ q̃rec(v)·q̃res(v)/qB(v).
Parameters4B
Context40,960
Weights8.8 GB
Licenseapache-2.0
AccessOpen weights
Monthly Downloads—
Runs On
What it takes to serve qwen3-4b-ablation-poe-no-base (4B parameters): the memory its weights need at each precision, and the cheapest way to rent enough data-center GPUs to hold them.
| Precision | Weights | Memory needed | Cheapest setup | Per hour | Also fits |
|---|---|---|---|---|---|
| 16-bit | 8.0 GB | 9.7 GB | 1x MI300X (192 GB) Vultr |
$1.85 | 1x H100 $1.99 · 1x MI325X $2.00 |
| 8-bit | 4.0 GB | 4.8 GB | 1x MI300X (192 GB) Vultr |
$1.85 | 1x H100 $1.99 · 1x MI325X $2.00 |
| 4-bit | 2.0 GB | 2.4 GB | 1x MI300X (192 GB) Vultr |
$1.85 | 1x H100 $1.99 · 1x MI325X $2.00 |
Memory is the weights at that precision plus 20% for the runtime and a short context; a long context needs more. Prices are the lowest on-demand hourly rates in the SAVRN Index, read Sep 18, 2026.
Model Card
By Yu, published under apache-2.0, revision 158796b58970.
The full ImmuneCoT method fuses the two safety branches with a Base-adjusted product-of-experts Qimm(v) ∝ q̃rec(v)·q̃res(v)/qB(v). This checkpoint uses the naive fusion Qno-base(v) ∝ q̃rec(v)·q̃res(v) — the same branch weights (λrec=0.5, λres=0.7) but no division by the base distribution — isolating whether the gains come from combining Recognition+Response at all, or specifically from the Base-adjusted PoE term. Intended use: research reproducibility for the ImmuneCoT paper's RQ3 ablation.
Read Yu's full model card
ImmuneCoT-Qwen3-4B-ablation-poe-no-base (RQ3 ablation)
Ablation variant: poe_no_base (naive fusion, no Base-adjustment).
The full ImmuneCoT method fuses the two safety branches with a Base-adjusted
product-of-experts Q_imm(v) ∝ q̃_rec(v)·q̃_res(v)/q_B(v). This checkpoint uses
the naive fusion Q_no-base(v) ∝ q̃_rec(v)·q̃_res(v) — the same branch weights
(λ_rec=0.5, λ_res=0.7) but no division by the base distribution — isolating
whether the gains come from combining Recognition+Response at all, or
specifically from the Base-adjusted PoE term.
- Base model: Qwen3-4B (frozen teacher, full-parameter on-policy distillation)
- Data: iasd_data_decontam_v1.json (1571 samples), 2 epochs (198 steps)
- Objective: forward KL + per-token clip β=1.0 + top-k 256
- Fusion:
poe_no_base(P_immune = log Pd' + log Pr', no − log P_Ref)
Intended use: research reproducibility for the ImmuneCoT paper's RQ3 ablation.
Configuration
- Architecture
- Qwen3ForCausalLM
- Context length (tokens)
- 40,960
- Layers
- 36
- Hidden size
- 2,560
- Feed-forward size
- 9,728
- Attention heads
- 32
- Key/value heads
- 8
- Head dimension
- 128
- Vocabulary size
- 151,936
- RoPE base
- 1,000,000
- Model type
- qwen3
Identity and Version
- Repository
- OP12138/qwen3-4b-ablation-poe-no-base
- Publisher
- Yu
- Task
- Text generation
- Modality
- Text
- Library
- transformers
- Parameters
- 4B parameters
- Languages
- Not stated by the source
- Revision
- 158796b58970720d14d569f617e4fc73d4da9959
- First published
- 2026-09-18
- Last updated
- 2026-09-18
Files and Weights
14 files, 8.8 GB in total. The weights are 2 files totalling 8.8 GB in safetensors.
Weights2 files · 8.8 GB
Configuration5 files · 36.0 KB
Tokenizer4 files · 15.9 MB
Documentation1 file · 1.1 KB
Other1 file · 4.2 KB
Repository1 file · 1.6 KB
Every file
| File | Type | Size | SHA-256 |
|---|---|---|---|
| model-00001-of-00002.safetensors | Weights | 5.0 GB | ef56a99889c6 |
| model-00002-of-00002.safetensors | Weights | 3.9 GB | c404c4aeba52 |
| added_tokens.json | Configuration | 707 B | — |
| config.json | Configuration | 1.5 KB | — |
| generation_config.json | Configuration | 210 B | — |
| model.safetensors.index.json | Configuration | 32.9 KB | — |
| special_tokens_map.json | Configuration | 613 B | — |
| README.md | Documentation | 1.1 KB | — |
| chat_template.jinja | Other | 4.2 KB | — |
| .gitattributes | Repository | 1.6 KB | — |
| merges.txt | Tokenizer | 1.7 MB | — |
| tokenizer.json | Tokenizer | 11.4 MB | 5cee3f74f849 |
| tokenizer_config.json | Tokenizer | 5.4 KB | — |
| vocab.json | Tokenizer | 2.8 MB | — |
License and Download
- License
- apache-2.0
- Access
- Open weights, no gate
- Download size
- 8.8 GB
Download from Yu
Released by Yu through its official repository on Hugging Face. Read the license.
Built From
- Derived from Qwen/Qwen3-4B
Memory Requirements
| Precision | Weights in memory |
|---|---|
| As published | 8.8 GB |
| 16-bit | 8.0 GB |
| 8-bit | 4.0 GB |
| 4-bit | 2.0 GB |
Weights only, from the published parameter count; the key-value cache and runtime add to this.
Questions About qwen3-4b-ablation-poe-no-base
How much GPU memory does qwen3-4b-ablation-poe-no-base need?
About 9.7 GB at 16-bit and 2.4 GB at 4-bit: the weights (4B parameters) plus a working margin. A long context needs more.
What is the cheapest GPU to run qwen3-4b-ablation-poe-no-base on?
At 16-bit, 1x MI300X from $1.85 an hour; at 4-bit, 1x MI300X from $1.85 an hour, at the lowest on-demand prices the SAVRN Index lists.
Can I use qwen3-4b-ablation-poe-no-base commercially?
Yes. qwen3-4b-ablation-poe-no-base is released under Apache License 2.0. The Apache License 2.0 is a permissive open-source license. It permits commercial use, modification and redistribution. It requires keeping the license and copyright notices and any NOTICE file, stating significant changes, and it includes an express patent grant from contributors.
What is qwen3-4b-ablation-poe-no-base's context length?
40,960 tokens, from the maximum position embeddings in its published configuration.
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