Meta Llama · Llama 3.1

Llama-3.1-8B

Unverified · community-discovered, not yet reviewed

Llama-3.1-8B is a discovered model from public model catalogues. Badgr builds a GPU serving profile from source metadata, estimated VRAM, context length, and available execution routes.

Last validated or meaningfully updated: Dynamic source discovery

ChatMultilingual

Availability

Not yet Badgr AI API

Not currently validated

Not yet Dedicated endpoint

Not currently validated

Not yet Custom GPU deployment

Not currently validated

Deployment profile

Architecture
Source metadata pending
Licence
llama3.1
Minimum VRAM
~20GB
Context
Source dependent

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

Model identity

Languages
en, de, fr, it, pt, hi, es, th
Updated
1 years ago
HuggingFace revision
d04e592bb4

Popularity and trust

Downloads (last month)

597.5K

Likes

2.6K

Spaces using this model

100

Access

Gated on HuggingFace

Files and formats

Weight formats

Safetensors

Repository files

17

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

Estimated pricing

Provider estimate: cold start

2–5 min

Provider estimate: endpoint cost

$0.34 – $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 $0.34/hr

24GB VRAM/GPU20 vCPU31.5GB RAM79GB storage0.06Gbps networkCUDA 13.4

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 $0.38/hr

24GB VRAM/GPU128 vCPU62.9GB RAM259GB storage0.34Gbps networkCUDA 12.6

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/GPU32 vCPU50.3GB RAM522GB storage0.12Gbps 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 $0.44/hr

48GB VRAM/GPU48 vCPU31.2GB RAM1675.8GB storage0.65Gbps 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 $0.44/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 $0.45/hr

24GB VRAM/GPU64 vCPU62.9GB RAM1076.5GB storage0.88Gbps networkCUDA 12.8

Best for

ComfyUI, Batch Inference, Qwen 2.5 7B Instruct

Startup: 2–5 min

Reliability: Standard

Last checked: just now

Known limitations

  • Source-discovered pages use best-effort metadata from an automated publication gate, not manual review.
  • Licence, gated access, runner compatibility, and exact memory use should be checked before production deployment.

Related troubleshooting