Answer.AI · ModernBERT

ModernBERT Large

ModernBERT Large is a 1B embeddings and reranking model available through supported Badgr execution routes.

Last validated or meaningfully updated: 2026-07-27

EmbeddingsRerankingEdge-capableFine-tunable

Availability

✓ Badgr AI API

Available through Badgr

Not yet Dedicated endpoint

Not currently validated

Not yet Custom GPU deployment

Not currently validated

Deployment profile

Architecture
ModernBertModel
Licence
Apache-2.0
Minimum VRAM
~6GB
Context
8K tokens

Recommended: RTX 4090 24GB. VRAM is an estimate and increases with context, cache, concurrency, and runtime overhead.

Model identity

Languages
en
Updated
1 years ago
HuggingFace revision
45bb4654a4

Popularity and trust

Downloads (last month)

636.0K

Likes

495

Spaces using this model

19

Files and formats

Weight formats

Safetensors, ONNX, PyTorch bin

Repository files

16

Chat template

Available

GPU deployment scenarios

Estimated from parameter count and quantisation. Will switch to “Verified by Badgr” once a real run backs a tier.

Testing

RTX 4090 24GB

Short context, low concurrency

Small production

L40S 48GB

8K context, 1-4 concurrent requests

Higher throughput

A100 80GB

32K context, continuous batching

Large production

RTX 4090 24GB

Higher concurrency

Estimated — multimodal inputs, long context, and concurrency all increase real VRAM use beyond this estimate.

Also runs well on L40S 48GB, A100 40GB. Available in United States, Europe.

Serving compatibility

RuntimeStatusNotes
vLLMEstimatedUsed for Badgr dedicated endpoints
TransformersDeclared by sourceBasic fallback
llama.cppRequires GGUF conversionNo GGUF weights found in repo
SGLangUnknownNot evaluated
TensorRT-LLMUnknownConversion may be required
TGIUnknownNot evaluated

Call this model through Badgr

curl https://api.aibadgr.com/v1/chat/completions \
  -H "Authorization: Bearer $BADGR_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"model":"answerdotai/ModernBERT-large","messages":[{"role":"user","content":"Hello"}]}'

Estimated pricing

Provider estimate: cold start

2–5 min

Provider estimate: endpoint cost

$0.18 – $0.45/hr

Idle cost

$0 when stopped

Per-token throughput cost is not shown here: Badgr has not benchmarked this model yet, and this page does not display figures it cannot back with real data.

Recommended Badgr routes

RTX 4090 24GB · United States

Available

from $0.18/hr

24GB VRAM/GPU32 vCPU16GB RAM1392.9GB storage0.01Gbps networkCUDA 13.2

Best for

ComfyUI, Batch Inference, Qwen 2.5 7B Instruct

Startup: 2–5 min

Reliability: Standard

Last checked: just now

RTX 4090 24GB · United States

Available

from $0.26/hr

24GB VRAM/GPU8 vCPU94.3GB RAM1563GB storage1.34Gbps networkCUDA 13.0

Best for

ComfyUI, Batch Inference, Qwen 2.5 7B Instruct

Startup: 2–5 min

Reliability: Standard

Last checked: just now

RTX 4090 24GB · United States

Available

from $0.44/hr

24GB VRAM/GPU48 vCPU83.9GB RAM914.5GB storage7.08Gbps networkCUDA 12.8

Best for

ComfyUI, Batch Inference, Qwen 2.5 7B Instruct

Startup: 2–5 min

Reliability: Standard

Last checked: just now

RTX 4090 24GB · United States

Available

from $0.44/hr

24GB VRAM/GPU

Best for

ComfyUI, Batch Inference, Qwen 2.5 7B Instruct

Startup: 2–5 min

Reliability: Standard

Last checked: just now

RTX 4090 24GB · United States

Available

from $0.44/hr

22.5GB VRAM/GPU256 vCPU125.8GB RAM759GB storage0.42Gbps networkCUDA 12.2

Best for

ComfyUI, Batch Inference, Qwen 2.5 7B Instruct

Startup: 2–5 min

Reliability: Standard

Last checked: just now

RTX 4090 24GB · United States

Available

from $0.45/hr

24GB VRAM/GPU48 vCPU41.9GB RAM414.16666666666663GB storage0.44Gbps networkCUDA 13.2

Best for

ComfyUI, Batch Inference, Qwen 2.5 7B Instruct

Startup: 2–5 min

Reliability: Standard

Last checked: just now

Known limitations

  • Memory use increases with context length and concurrency.

Related troubleshooting