AIPAI Pentium
← Model index
general AI

mradermacher/gemma-4-31B-it-Claude-Opus-Distill-v2-i1-GGUF

mradermacher/gemma-4-31B-it-Claude-Opus-Distill-v2-i1-GGUF is a AI workload model indexed for deployment research. Estimated minimum GPU memory is 24 GB. It is publicly listed on Hugging Face.

View on Hugging Face ↗Add to comparison
Parameters31.0B
Downloads3,412
Likes0
Licenseapache-2.0
Librarytransformers
Hardware tierProsumer
DEPLOYMENT NOTES

What to verify before deployment

  • Confirm the exact weight format and quantization.
  • Measure memory at your intended context or image size.
  • Review model-card limitations and evaluation methodology.
  • Test latency and throughput on your target runtime.
LICENSE SIGNAL

Likely commercial-friendly

License metadata is an index signal, not legal advice. Follow the repository license and any model-specific acceptable-use terms.

Verify at the source →
RUN THIS MODEL

Choose how you want to deploy

GPU CLOUD · SIMPLE START

Rent a GPU sized for this model

Start with at least 48 GB VRAM, then measure memory and latency with your workload.

Check RunPod availability ↗Referral link. AI Pentium may earn credits or commission from qualifying new users.
GPU MARKETPLACE · PRICE SHOP

Compare marketplace GPU offers

Filter Vast.ai offers for a GPU with at least 48 GB VRAM and compare availability by region.

Compare GPUs on Vast.ai ↗Referral link. AI Pentium may earn commission from qualifying new users.
ORIGINAL SOURCE

Inspect weights and model card

Verify files, license terms, limitations and usage instructions before deploying.

View on Hugging Face ↗Source link; AI Pentium does not host model weights.
SIMILAR OPTIONS

More AI models

sentence-similarity

sentence-transformers/all-MiniLM-L6-v2

sentence-transformers/all-MiniLM-L6-v2 is a sentence similarity model indexed for deployment research. Estimated minimum GPU memory is 4 GB. It is publicly listed on Hugging Face.

↓ 253,331,994♡ 5,620
Unknown4 GB+ VRAMapache-2.0
Deployment details →
text-ranking

cross-encoder/ms-marco-MiniLM-L6-v2

cross-encoder/ms-marco-MiniLM-L6-v2 is a text ranking model indexed for deployment research. Estimated minimum GPU memory is 8 GB. It is publicly listed on Hugging Face.

↓ 86,661,012♡ 315
Unknown8 GB+ VRAMapache-2.0
Deployment details →
feature-extraction

BAAI/bge-small-en-v1.5

BAAI/bge-small-en-v1.5 is a feature extraction model indexed for deployment research. Estimated minimum GPU memory is 4 GB. It is publicly listed on Hugging Face.

↓ 64,933,788♡ 550
Unknown4 GB+ VRAMmit
Deployment details →
general AI

google/electra-base-discriminator

google/electra-base-discriminator is a AI workload model indexed for deployment research. Estimated minimum GPU memory is 8 GB. It is publicly listed on Hugging Face.

↓ 58,160,168♡ 159
Unknown8 GB+ VRAMapache-2.0
Deployment details →
fill-mask

google-bert/bert-base-uncased

google-bert/bert-base-uncased is a fill mask model indexed for deployment research. Estimated minimum GPU memory is 8 GB. It is publicly listed on Hugging Face.

↓ 50,396,517♡ 3,033
Unknown8 GB+ VRAMapache-2.0
Deployment details →

Operate a GPU cloud or inference API?

Reach developers after they have selected a model and are ready to run it.

Become a platform partner