DavidAU · GLM 4.7 Flash Uncensored Heretic NEO CODE Imatrix MAX GGUF

GLM-4.7-Flash-Uncensored-Heretic-NEO-CODE-Imatrix-MAX-GGUF

Unverified · community-discovered, not yet reviewed

GLM-4.7-Flash-Uncensored-Heretic-NEO-CODE-Imatrix-MAX-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

Multilingual

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
Minimum VRAM
~18GB
Context
Source dependent

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

Model identity

Base model
Olafangensan/GLM-4.7-Flash-heretic
Languages
en, zh
Updated
3 months ago
HuggingFace revision
4395b80e6a

Popularity and trust

Downloads (last month)

33.2K

Likes

427

Spaces using this model

6

Files and formats

Weight formats

GGUF

Repository files

14

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

Estimated pricing

Provider estimate: cold start

2–5 min

Provider estimate: endpoint cost

$0.26 – $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 $0.26/hr

24GB VRAM/GPU32 vCPU16GB RAM1392.9GB storage0.02Gbps 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 $0.44/hr

24GB VRAM/GPU256 vCPU125.8GB RAM778.5GB 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/GPU32 vCPU100.7GB RAM160GB storage1.48Gbps 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 · Europe

Estimated

starting from $0.45/hr

Badgr estimated starting price

Best for

ComfyUI, Batch Inference, Qwen 2.5 7B Instruct

Startup: 2–5 min

Reliability: Standard

Last checked: Live marketplace price not available yet

RTX 4090 24GB · Europe

Estimated

starting from $0.45/hr

Badgr estimated starting price

Best for

ComfyUI, Batch Inference, Qwen 2.5 7B Instruct

Startup: 2–5 min

Reliability: Standard

Last checked: Live marketplace price not available yet

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