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JonathanColetti · MODEL RECORD

Qwen3.8-27B Uncensored (JonathanColetti)

Qwen3.8-27B Uncensored (JonathanColetti) has 27.321 billion total parameters. The selected Q4_K_M GGUF file is 16.811 GB.

Data snapshot: . 2 published tests in this catalog.

Model file and details

Provider
JonathanColetti
Total parameters
27,320,697,856
Exact file size
16,810,714,528 bytes
Quantization / precision
Q4_K_M
Weight repository
JonathanColetti/Qwen3.8-27B-Uncensored-GGUF
Original model repository
JonathanColetti/Qwen3.8-27B-Uncensored
Weight revision
45d0fc0ad6cfcf9eeee6008ddaea925536409b18
Model revision
5bb7aa90f0efef548e87005b1fb7658e522b6b7f
Runtime notes
Confirm model architecture and quantization support in your runner.
Recorded release date
2026-08-14
Date evidence
Source repository createdAt (release-date proxy); reviewed 29 September 2026

Qwen3.8-27B-Uncensored-Q4_K_M.gguf

GGUF file and download on Hugging Face · Original model card

Published benchmark results

These scores were compiled from the linked sources. These published scores were not independently tested here. Different prompts, precision, thinking budgets and tools can change results.

MMLU · 0-shot reported

83.3 / 100

Zero-shot MMLU accuracy. Kept separate from mixed/few-shot published scores. Runtime, prompt formatting and weight precision can still differ.

Benchmark efficiency: 4.955 published score points per GB of selected weights. This ratio is not an inference-speed measure; check the test settings to see whether the score covers the selected quantization.

Test settings: Publisher lm-evaluation-harness zero-shot evaluation of this modified model at BF16; text stack only. Published table: Uncensored column.

Not comparable to Qwen few-shot release results. Selected Q4_K_M was not tested on these tasks. Uses llama.cpp; integrated MTP needs compatible runtime.

Read the MMLU · 0-shot reported source

HellaSwag · 0-shot reported

82.9 / 100

Zero-shot HellaSwag results. Publisher-reported accuracy; normalization is not fully specified. Separate from the mixed-setting view.

Benchmark efficiency: 4.931 published score points per GB of selected weights. This ratio is not an inference-speed measure; check the test settings to see whether the score covers the selected quantization.

Test settings: Publisher lm-evaluation-harness zero-shot evaluation of this modified model at BF16; text stack only. Published table: Uncensored column.

Not comparable to Qwen few-shot release results. Selected Q4_K_M was not tested on these tasks. Uses llama.cpp; integrated MTP needs compatible runtime.

Read the HellaSwag · 0-shot reported source

Memory and comparison limits

Context and version evidence: The repository and file name identify the selected model. Revision hashes are shown above when recorded. Tested context length, full hardware configuration and run date are not consistently recorded in this snapshot. Only settings explicitly stated in each benchmark record are known.

The 16.811 GB figure covers model weights in this file. It excludes the context cache, runtime, operating system and any separate multimodal files. It is not a measured RAM requirement or a token-generation speed.

Use the model ranking chart to compare one test at a time. Use the 8, 16 and 32 GB memory guide. Check hardware memory and bandwidth before choosing a model.

Need a computer for Qwen3.8-27B Uncensored (JonathanColetti)?

These complete configurations pass the initial weight-size check for the selected 16.81 GB file. Allow extra memory for context and software. Check the model’s runtime notes and your inference software before buying.

CPU inference

GMKtec K15 · 32GB

Core Ultra 5 125U, 32GB DDR5-4800 (2 x 16GB), 512GB PCIe 4.0 SSD

$669.99Dated reference · not a live offer

32 GB system RAM · CPU planning

Low-power CPU and shared graphics limit heavy inference.

Check price on Amazon ↗Specifications & model limits
Listing and price evidence

Listing evidence: 2026-09-25. Amazon.com base price visible in an owner-supplied screenshot reviewed 25 Sep 2026; capture time not supplied. Dated reference, not a live quote. Excludes card signup offers, coupons, tax and shipping.

Apple unified memory

Apple Mac Studio M5 Max · 36GB

18-core CPU, 32-core GPU, 36GB unified memory, 512GB SSD

$2,499.00Dated reference · not a live offer

36 GB unified memory

Fixed 36GB memory and internal storage; no CUDA support; price is a manufacturer reference rather than a verified Amazon offer.

Check price on Amazon ↗Specifications & model limits
Listing and price evidence

Listing evidence: 2026-10-02. Apple US launch price for the base M5 Max Mac Studio, published 22 September 2026: USD 2,499. Dated manufacturer reference, not an Amazon offer; tax and shipping may differ.

AMD unified memory

GMKtec EVO-X2

Ryzen AI Max+ 395, 64GB LPDDR5X-8000, 1TB PCIe 4.0 SSD

$2,199.99Dated reference · not a live offer

64 GB unified memory

Memory is soldered and shared with the operating system.

Check price on Amazon ↗Specifications & model limits
Listing and price evidence

Listing evidence: 2026-09-24. GMKtec, EVO-X2 / 64GB / 1TB, recorded 22 Sep 2026; exact ASIN capacity identified 24 Sep. This is a dated reference, not a current Amazon price; tax, shipping and bundle contents may differ.

Memory matches are estimates, not tested compatibility or speed. As an Amazon Associate I earn from qualifying purchases.

Compare more computers for this model

RAM and VRAM planning for JC Qwen3.8 27B

Confirm model architecture and quantization support in your runner. The selected weights use 16.811 GB; this excludes context cache, runtime buffers and other programs.

System RAM (CPU inference)
32 GB planning tier · 22.4 GB initial weight budget
Dedicated VRAM
24 GB planning tier · 19.2 GB initial weight budget
Unified memory
32 GB planning tier · 22.4 GB initial weight budget

These are the first listed tiers that pass our reserve policy, not measured minimum requirements. System RAM and VRAM remain separate. Use the memory tool to change the reserve for your context and runner.

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