Can an 8 GB, 12 GB, 16 GB, 24 GB or 32 GB computer run Humanizer 12B?
The publisher now labels the 2-bit file for 8 GB, Q3 for 12 GB, Q4_K_M for about 14 GB, Q6_K for 16 GB and Q8_0 for 32 GB or more. Those are publisher planning tiers, not independent compatibility or speed tests. The 8 GB tier has the least headroom and the most aggressive quantization; reserve memory for the operating system, runtime, context cache and other workloads before choosing a computer.
Exact files at repository revision 8a6975e, checked 6 October 2026. Download size is not total runtime memory.
More fact mistakes than the larger files; check numbers and names
The publisher measured Q4_K_M, Q3 and 2-bit side by side as maximum llama-server resident memory on one Apple M5 Max, at an 8,192-token context, one request at a time and four real drafts. Q8_0 came from an earlier one-draft run that may read about 1.3 GB low; Q6_K remains estimated. A 32,768-token context added about 0.4 GB in that setup. None of these figures is independently reproduced or proves speed or compatibility on another computer.
Runtime checks before buying hardware
Context: the documented setup uses an 8,192-token context. Longer input or output can require more memory.
Prompt and sampling: the model is a text-completion rewriter with publisher-specified sampling. A generic chat preset can change or break its behavior.
Ollama: the publisher says Ollama's default Gemma template breaks this model and supplies a custom Modelfile. Do not treat a successful download as proof that a front end is configured correctly.
Old files: GGUF downloads from before 4 October do not contain the current chat template. Re-download the pinned file before troubleshooting an older copy.
Q3 tradeoff: the new 5.59 GB Q3 file measured 8.0 GB peak memory in the publisher's setup. Its strict fact judge flagged 64 of 420 English and 53 of 204 Chinese rewrites, versus 58 and 51 for Q4_K_M.
Why the low-bit QAT files matter: in the publisher's KL-divergence test against bf16, Q3 drift was 2.2× lower in English and 2.5× lower in Chinese than a standard build at the same size. The 2-bit file was 4.4× and 7.1× lower. The publisher estimates that standard files need about 0.9–1.0 GB more for Q3-like divergence and 1.2–1.4 GB more for 2-bit-like divergence. These are publisher lab comparisons, not speed, fact-accuracy or independent hardware benchmarks.
Smallest build: the 2-bit file measured 6.2 GB peak memory. The publisher's strict fact judge flagged 70 of 420 English and 66 of 204 Chinese rewrites, versus 44 and 54 for Q8_0. The card says the English gap was beyond noise, while the Chinese gap was within noise. These are publisher evaluations, not independent tests; verify numbers, dates and names.
These are existing purchase configurations, not Humanizer benchmarks. The two Windows mini PCs use ordinary system RAM and may rely on CPU inference or a separately configured integrated-GPU allocation. The Mac uses unified memory. None was tested here with this model.
As an Amazon Associate I earn from qualifying purchases. These links use the recorded exact US ASINs and johndowie-20. Current price and stock are not verified on this page.
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.
Humanizer fact fidelity · EN 420
89.52 / 100
Share of English rewrites where a single strict GLM-5.3 judge found no factual problem. Task-specific publisher evaluation, not a general benchmark or human review.
Benchmark efficiency: 7.066 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 evaluation of this Q8_0 file on 420 English rewrites from a held-out 312-draft, 18-genre set; 376 of 420 received no factual-problem finding from GLM-5.3, one strict judge vote per rewrite.
Task-specific publisher evaluation with an LLM judge, not human verification or a general capability score. The model can still alter details, especially numbers, dates and names.
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 12.67 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.
These complete configurations pass the initial weight-size check for the selected 12.67 GB file. Allow extra memory for context and software. Check the model’s runtime notes and your inference software before buying.
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.
Listing evidence: 2026-10-03. Apple US launch price announced 22 September 2026: USD 1,699. Dated manufacturer reference, not an Amazon offer; tax and shipping may differ.
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.
Confirm model architecture and quantization support in your runner. The selected weights use 12.67 GB; this excludes context cache, runtime buffers and other programs.
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.