GP MoLFormer Uniq — Hardware Requirements & GPU Compatibility
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GP MoLFormer Uniq is a 47M-parameter open language model from ibm-research. It supports a context window of up to 202 tokens. At BF16 it needs about 0.10 GB of VRAM — see which GPUs and Macs can run it below.
2.0K downloads
6 likesSpecifications
- Publisher
- ibm-research
- Parameters
- 47M
- Architecture
- MolformerForCausalLM
- Context Length
- 202 tokens
- Vocabulary Size
- 2,362
- Release Date
- 2025-05-01
- License
- Apache 2.0
Get Started
HuggingFace
How Much VRAM Does GP MoLFormer Uniq Need?
Select a quantization to see compatible GPUs below.
| Quantization | Bits | VRAM | + Context | File Size | Quality |
|---|---|---|---|---|---|
| BF16 | 16.00 | 0.1 GB | — | 0.09 GB | Brain floating point 16 — preferred for training |
Which GPUs Can Run GP MoLFormer Uniq?
BF16 · 0.1 GBGP MoLFormer Uniq (BF16) requires 0.1 GB of VRAM to load the model weights. For comfortable inference with headroom for KV cache and system overhead, 1+ GB is recommended. 35 GPUs can run it, including NVIDIA GeForce RTX 5090, NVIDIA GeForce RTX 3090 Ti.
Runs great
— Plenty of headroomWhich Devices Can Run GP MoLFormer Uniq?
BF16 · 0.1 GB33 devices with unified memory can run GP MoLFormer Uniq, including NVIDIA DGX H100, NVIDIA DGX A100 640GB.
Runs great
— Plenty of headroomRelated Models
Frequently Asked Questions
- How much VRAM does GP MoLFormer Uniq need?
GP MoLFormer Uniq requires 0.1 GB of VRAM at BF16.
VRAM = Weights + KV Cache + Overhead
Weights = 47M × 16 bits ÷ 8 = 0.1 GB
VRAM usage by quantization
BF160.1 GB- Can I run GP MoLFormer Uniq on a Mac?
GP MoLFormer Uniq requires at least 0.1 GB at BF16, which exceeds the unified memory of most consumer Macs. You would need a Mac Studio or Mac Pro with a high-memory configuration.
- Can I run GP MoLFormer Uniq locally?
Yes — GP MoLFormer Uniq can run locally on consumer hardware. At BF16 quantization it needs 0.1 GB of VRAM. Popular tools include Ollama, LM Studio, and llama.cpp.
- How fast is GP MoLFormer Uniq?
At BF16, GP MoLFormer Uniq can reach ~29150 tok/s on AMD Instinct MI300X. On NVIDIA GeForce RTX 4090: ~6552 tok/s. Speed depends mainly on GPU memory bandwidth. Real-world results typically within ±20%.
tok/s = (bandwidth GB/s ÷ model GB) × efficiency
Example: AMD Instinct MI300X → 5300 ÷ 0.1 × 0.55 = ~29150 tok/s
Estimated speed at BF16 (0.1 GB)
~29150 tok/s~6552 tok/s~21788 tok/s~18022 tok/sReal-world results typically within ±20%. Speed depends on batch size, quantization kernel, and software stack.
- What's the download size of GP MoLFormer Uniq?
At BF16, the download is about 0.09 GB.
- Which GPUs can run GP MoLFormer Uniq?
35 consumer GPUs can run GP MoLFormer Uniq at BF16 (0.1 GB). Top options include AMD Radeon RX 6700 XT, AMD Radeon RX 6800, AMD Radeon RX 6800 XT. 35 GPUs have plenty of headroom for comfortable inference.
- Which devices can run GP MoLFormer Uniq?
33 devices with unified memory can run GP MoLFormer Uniq at BF16 (0.1 GB), including Mac Mini M4 (16 GB), Mac Mini M4 (32 GB), Mac Mini M4 Pro (24 GB), Mac Mini M4 Pro (48 GB). Apple Silicon Macs use unified memory shared between CPU and GPU, making them well-suited for local LLM inference.