Openbmb · MiniCPM5

MiniCPM5-2B-GGUF

Unverified · community-discovered, not yet reviewed

MiniCPM5-2B-GGUF 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

ChatEdge-capableMultilingualFine-tunable

Availability

Not yet Badgr AI API

Not currently validated

Dedicated endpoint

Available through Badgr

Custom GPU deployment

Available through Badgr

Deployment profile

Architecture
Source metadata pending
Minimum VRAM
~8GB
Context
Source dependent

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

Model identity

Languages
en, zh
Updated
1 day ago
HuggingFace revision
c451f4d674

Popularity and trust

Downloads (last month)

70.8K

Likes

165

Spaces using this model

3

Files and formats

Weight formats

GGUF

Repository files

6

Chat template

Not detected

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.cppDeclared by sourceGGUF weights available in repo
SGLangUnknownNot evaluated
TensorRT-LLMUnknownConversion may be required
TGIUnknownNot evaluated

Ready-to-run Badgr configurations

Quick test

badgr serve openbmb/MiniCPM5-2B-GGUF --max-cost 2

Dedicated endpoint command

badgr serve openbmb/MiniCPM5-2B-GGUF --gpu RTX 4090 --max-cost 10

Advanced configuration (defaults to automatic)

  • Runtime
  • Quantisation
  • GPU and GPU count
  • Context length
  • Maximum concurrency
  • Region
  • Maximum hourly spend
  • Persistent or capped runtime

Estimated pricing

Provider estimate: cold start

2–5 min

Provider estimate: endpoint cost

$0.18 – $0.40/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 RAM1432.9GB storageCUDA 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 $0.28/hr

24GB VRAM/GPU64 vCPU125.7GB RAM290.4GB storage0.92Gbps 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 $0.28/hr

2x GPU24GB VRAM/GPUSame host128 vCPU62.9GB RAM237.575GB storage0.53Gbps 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 $0.29/hr

24GB VRAM/GPU128 vCPU31.5GB RAM118.7875GB storage0.53Gbps 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 $0.35/hr

24GB VRAM/GPU12 vCPU24.4GB RAM74GB storage0.26Gbps 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 $0.40/hr

24GB VRAM/GPU192 vCPU71.9GB RAM956.7142857142857GB storage0.89Gbps 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

  • 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