Unsloth · Qwen 3.8

Qwen 3.8 27B GGUF

Verified by Badgr · Serve

Qwen 3.8 27B GGUF is a 27B chat and text-generation model available through supported Badgr execution routes.

Last validated or meaningfully updated: 2026-10-10

ChatLong context
Serve Qwen 3.8 27B GGUF nowGet help running this

✓ Verified by Badgr · llama.cpp · Serve

Last verified 2026-10-10

badgr serve --runtime llama.cpp --hf-repo unsloth/Qwen3.8-27B-GGUF --hf-file Qwen3.8-27B-UD-Q4_K_M.gguf --gpu RTX_4090 --funding paid --max-cost 3 --env LLAMA_ARG_CTX_SIZE=8192 --env LLAMA_ARG_N_GPU_LAYERS=99
GPU
NVIDIA GeForce RTX 4090Reported by the provider, not confirmed inside the container
Time to verified
197s
Deployment
dep-bd29b82a74
  • ✓ llama-server started and loaded the 16.5 GB Q4_K_M file
  • ✓ A chat completion returned: "The capital of Australia is Canberra."
  • ✓ final_state = VERIFIED
  • ✓ Teardown completed

A 27B model on one 24 GB card at an 8,192-token context. The speed figure is from a single short request, not a benchmark.

Raw evidence
final_state=VERIFIED failure_class=None providers_tried=1 spend_usd=0.0240 elapsed=197.0s
chat completion: 41 tokens at 47.9 tokens/s decode

Run from Badgr's local development environment. Documents that this deployment path works end-to-end for this model.

Availability

Not yet Badgr AI API

Not currently validated

✓ Dedicated endpoint

Available through Badgr

✓ Custom GPU deployment

Available through Badgr

Deployment profile

Architecture
Qwen3_5ForConditionalGeneration
Licence
Apache-2.0
Minimum VRAM
~58GB
Context
256K tokens

Recommended: A100 80GB. VRAM is an estimate and increases with context, cache, concurrency, and runtime overhead.

Model identity

Base model
Qwen/Qwen3.8-27B
Updated
1 months ago
HuggingFace revision
4ca720788d

Popularity and trust

Downloads (last month)

6.4M

Likes

5.0K

Spaces using this model

26

Files and formats

Weight formats

GGUF

Repository files

33

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

A100 80GB

Short context, low concurrency

Small production

H100 80GB

8K context, 1-4 concurrent requests

Higher throughput

H200 141GB

32K context, continuous batching

Large production

A100 80GB

Higher concurrency

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

Also runs well on H100 80GB, H200 141GB. Available in United States, Europe, Asia Pacific.

Serving compatibility

RuntimeStatusNotes
vLLMEstimatedUsed for Badgr dedicated endpoints
TransformersUnknownBasic fallback
llama.cppVerified by BadgrConfirmed by a real badgr serve run (deployment dep-bd29b82a74)
SGLangUnknownNot evaluated
OllamaUnknownNot evaluated
DiffusersUnknownNot evaluated
PyTorchUnknownNot evaluated
TensorRT-LLMUnknownConversion may be required
TGIUnknownNot evaluated

Ready-to-run Badgr configurations

Quick test

badgr serve unsloth/Qwen3.8-27B-GGUF --max-cost 2

Validated dedicated endpoint command

badgr serve unsloth/Qwen3.8-27B-GGUF --gpu A100 80GB --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

3–8 min

Provider estimate: endpoint cost

$1.30 – $1.40/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

A100 80GB · United States

Available

from $1.30/hr

40GB VRAM/GPU

Best for

LoRA Training, vLLM Endpoint, Qwen 2.5 32B Instruct

Startup: 3–8 min

Reliability: High

Last checked: just now

Serve modelCheck live route
View details →

A100 80GB · Europe

Estimated

starting from $1.40/hr

Badgr estimated starting price

Best for

LoRA Training, vLLM Endpoint, Qwen 2.5 32B Instruct

Startup: 3–8 min

Reliability: Good

Last checked: Live marketplace price not available yet

Serve modelCheck live route
View details →

A100 80GB · Europe

Estimated

starting from $1.40/hr

Badgr estimated starting price

Best for

LoRA Training, vLLM Endpoint, Qwen 2.5 32B Instruct

Startup: 3–8 min

Reliability: High

Last checked: Live marketplace price not available yet

Serve modelCheck live route
View details →

A100 80GB · Europe

Estimated

starting from $1.40/hr

Badgr estimated starting price

Best for

LoRA Training, vLLM Endpoint, Qwen 2.5 32B Instruct

Startup: 3–8 min

Reliability: High

Last checked: Live marketplace price not available yet

Serve modelCheck live route
View details →

A100 80GB · Europe

Estimated

starting from $1.40/hr

Badgr estimated starting price

Best for

LoRA Training, vLLM Endpoint, Qwen 2.5 32B Instruct

Startup: 3–8 min

Reliability: Good

Last checked: Live marketplace price not available yet

Serve modelCheck live route
View details →

A100 80GB · Europe

Estimated

starting from $1.40/hr

Badgr estimated starting price

Best for

LoRA Training, vLLM Endpoint, Qwen 2.5 32B Instruct

Startup: 3–8 min

Reliability: High

Last checked: Live marketplace price not available yet

Serve modelCheck live route
View details →

Known limitations

  • Memory use increases with context length and concurrency.

Related troubleshooting