Quinto 0.1 4B has 4.206 billion total parameters. The selected Q8_0 GGUF file is 4.482 GB.
Data snapshot: . 1 published test in this catalog.
Model file and details
Provider
fcreait
Total parameters
4,205,751,296
Exact file size
4,482,402,816 bytes
Quantization / precision
Q8_0
Weight repository
fcreait/Quinto-0.1-4b-GGUF
Original model repository
fcreait/Quinto-0.1-4b-GGUF
Weight revision
36fef48027a62f229a09f6b64b7b4ec65c43ed90
Model revision
36fef48027a62f229a09f6b64b7b4ec65c43ed90
Runtime notes
Confirm model architecture and quantization support in your runner.
Recorded release date
2026-10-12
Date evidence
The Apache-2.0 repository was created on 12 October 2026. Its card identifies a Qwen3.5-4B LoRA fine-tune for Italian, the selected checkpoint and the only published GGUF artifact.
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.
IFEval · prompt strict
80.6 / 100
Following every instruction in a prompt. Strict prompt-level accuracy on the full 541-prompt set.
Benchmark efficiency: 17.981 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 on the full 541-item IFEval set, strict prompt-level scoring, greedy decoding and thinking disabled. The model card reports 0.806 for Quinto and 0.815 for its Qwen3.5-4B base.
Publisher-run result, not independent validation. The card does not identify the evaluator revision, backend, hardware or whether the selected Q8_0 artifact was used. The publisher separately reports a task-specific Italian morphology experiment on 160 prompts at temperature 0.7: 2.65 defects per 1,000 words for Quinto versus approximately 6.1 for the base, with a second Quinto seed at 3.62 and stated noise of about 0.5-1.0. That lower-is-better result is not imported as a ranking score. The card also warns that tool calling regressed, thinking is untested, some sampled outputs loop, and the release is text-only. The 4,482,402,816-byte file excludes runtime, KV cache and context memory and does not establish device speed or compatibility.
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 4.482 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 4.48 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 4.482 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.