Meta · Embeddings and rerank · 29.78B parameters · Apache-2.0
MetaEncoder-30B
Needs 36 GB at FP8 / INT8. The smallest real configuration today is 2× Tesla V100 32GB at Vast.ai, $0.14 per hour, about $99 a month at 730 hours.
Parameters29.78Bdense
Context—maximum published
Checkpoint60 GBBF16, as published
LicenseApache-2.0check before commercial use
ReleasedSep 30, 2026documented date
Smallest configuration · FP8 / INT8
2× Tesla V100 32GB64 GB VRAM · 56% used
- Per hour
- $0.14
- Per month
- $99
- Cheapest at
Vast.ai
What is documented about MetaEncoder-30B
news checked 2026-10-27Instruction-following multimodal encoder (text, images, video; vLLM path text+image only), contrastively fine-tuned from meta-models/Muse-Glimmer-30B. arXiv 2610.11316. Low traction so far. Date = HF repo creation.
- https://huggingface.co/facebook/meta-encoder
- https://huggingface.co/api/models/facebook/meta-encoder?blobs=true
How much VRAM it needs
Weights plus runtime overhead. The context dimension appears once the model's architecture is on file.
| Precision | Weights | Weights + headroom |
|---|---|---|
| BF16published checkpoint | 60 GB | 72 GB |
| FP8 / INT8estimated | 30 GB | 36 GB |
| INT4 / MXFP4estimated | 18 GB | 22 GB |
Cross-checked on Hugging Face Oct 28, 2026: 29.8B parameters in the safetensors headers, 59.5 GB of weight files. Method: weights as published at the native precision, verified on Hugging Face 2026-10-28; other precisions estimated at 1 (8-bit) and 0.6 (4-bit) bytes per parameter; × 1.2 runtime headroom; KV cache not added (architecture not readable).
What it costs to run, GPU by GPU
The fewest GPUs of one type whose total memory fits the model at short context, priced from the cheapest eligible on-demand offer for exactly that count (45-day window, newest reading per provider), with the next providers beside it. Monthly = 730 hours.
| GPU | Smallest config | VRAM used | $ / hour | $ / month | Cheapest at |
|---|---|---|---|---|---|
| Tesla V100 32GBBest fit | 2× 32 GB64 GB total | 56% | $0.14 | $99 | |
| T4 | 4× 16 GB64 GB total | 56% | $0.16 | $117 | |
| RTX 3060 | 4× 12 GB48 GB total | 74% | $0.16 | $119 | |
| Tesla P100 | 4× 16 GB64 GB total | 56% | $0.19 | $138 | |
| RTX 3090 | 2× 24 GB48 GB total | 74% | $0.21 | $157 | |
| Quadro RTX 8000 | 1× 48 GB48 GB total | 74% | $0.25 | $186 | |
| RTX 6000 | 2× 24 GB48 GB total | 74% | $0.27 | $196 | |
| Titan RTX | 2× 24 GB48 GB total | 74% | $0.27 | $196 | |
| Titan Xp | 4× 12 GB48 GB total | 74% | $0.27 | $196 | |
| L40 | 1× 48 GB48 GB total | 74% | $0.27 | $196 | |
| RTX 2080 Ti | 4× 11 GB44 GB total | 81% | $0.28 | $202 | |
| RTX A6000 | 1× 48 GB48 GB total | 74% | $0.33 | $241 | GPURentonot scored · read Nov 1 · receipt · also gcube $0.34, Thunder Compute $0.35 |
| A100 40GB | 1× 40 GB40 GB total | 89% | $0.34 | $246 | |
| A40 | 1× 48 GB48 GB total | 74% | $0.35 | $255 | GPURentonot scored · read Nov 1 · receipt · also Vast.ai $0.48, Exoscale $1.05 |
| RTX 5060 Ti | 4× 16 GB64 GB total | 56% | $0.35 | $258 | |
| RTX A4000 | 4× 16 GB64 GB total | 56% | $0.36 | $266 | |
| RTX 3080 | 4× 10 GB40 GB total | 89% | $0.38 | $274 | |
| RTX A5000 | 2× 24 GB48 GB total | 74% | $0.38 | $274 | |
| RTX 4070 Super | 4× 12 GB48 GB total | 74% | $0.38 | $274 | |
| Tesla V100 16GB | 4× 16 GB64 GB total | 56% | $0.38 | $275 | |
| RTX 6000 Ada | 1× 48 GB48 GB total | 74% | $0.40 | $290 | |
| Quadro RTX 5000 | 4× 16 GB64 GB total | 56% | $0.40 | $294 | |
| RTX 3090 Ti | 2× 24 GB48 GB total | 74% | $0.42 | $304 | |
| L40S | 1× 48 GB48 GB total | 74% | $0.43 | $314 | |
| The 24 cheapest of 74 GPU types that fit. Every GPU, any precision and context, in the finder | |||||
