PowerMoE-3b
PowerMoE-3B is a 3B sparse Mixture-of-Experts (sMoE) language model trained with the Power learning rate scheduler. It sparsely activates 800M parameters for each token. It is trained on a mix of open-source and proprietary datasets. PowerMoE-3B has shown promising results compared to other dense models with 2x activate parameters across various benchmarks, including natural language multi-choices, code generation, a...
Params
3.4 B
Context
4,096
Downloads 30d
1.8 M
Likes
22
Download history
daily snapshots · 10 days1.8 M1.8 M
Jul 28Jul 31Aug 3Aug 6
Can you run it?
Estimated VRAM at 8K context unless noted. Pick your hardware to see the verdict per quantization.
| File | Quant | Size | Est. VRAM | Verdict on RTX 4090 · 24 GB |
|---|---|---|---|---|
| model.safetensors | f32 | 13.5 GB | 15.9 GB | ✅ Runs comfortably |
Estimate: file size × 1.1 + KV cache at 8K + 0.5 GB overhead. Not a benchmark — how we calculate this.
Run it
copy-paste, exact tags checked against the Hub$ curl -s https://aimodelscomparison.com/api/v1/models/powermoe-3b
{
"hf_id": "ibm-research/PowerMoE-3b",
"params_b": 3.37,
"context_length": 4096,
"license": { "id": "apache-2.0", "commercial": "yes" },
"downloads_30d": 1843751,
"vram_estimates": [
{ "quant": "f32", "gb": 15.9 }
],
"updated_at": "2026-07-28T18:02:45Z"
}
Specifications
- Architecture
- GraniteMoeForCausalLM
- Parameters
- 3.4 B
- Tensor type
- F32
- Context length
- 4,096
- Vocabulary
- 49,152
- Layers / heads
- 32 / 24
- Licence
- apache-2.0
- First seen on the Hub
- 2024-08-14
- Training datasets
- undisclosed
- ARC (reported)
- 58.1
- MBPP (reported)
- 32.4
- PIQA (reported)
- 79.1
- BoolQ (reported)
- 65
- Hellaswag (reported)
- 71.5
- humaneval (reported)
- 20.1
- OpenBookQA (reported)
- 41
- Winogrande (reported)
- 65
- MMLU (5 shot) (reported)
- 42.8
- math (4 shot) (reported)
- 14.8
- GSM8k (5 shot) (reported)
- 25.9
- Added to our catalog
- 2026-07-28
Compare with
Sponsored · GPU cloud
Not enough VRAM?
Spin up a 24 GB L4 instance in 40 seconds. $0.44/hr.