Empero Qwen3.8 9B has 9.653 billion total parameters. The selected Q4_K_M GGUF file is 5.78 GB.
Data snapshot: . 2 published tests in this catalog.
Model file and details
Provider
Empero
Total parameters
9,653,104,368
Exact file size
5,780,090,176 bytes
Quantization / precision
Q4_K_M
Weight repository
empero-ai/Qwen3.8-9B-Distill-GGUF
Original model repository
empero-ai/Qwen3.8-9B-Distill
Weight revision
760121cd70bb4c36b2b5ec58eb765e0df5987efe
Model revision
0934f3d2327ff2df2197495278c4c46ae5a56bd9
Runtime notes
Reasoning distillation, not an official Qwen 3.8 9B release. Use a recent llama.cpp build with Qwen3.5 / Gated DeltaNet support; older builds can fail to load it. Apache-2.0 licensed. The 5.780 GB Q4_K_M file is only the weight file: runtime, KV cache and long contexts need additional memory. The recorded MMLU and GSM8K results are from the source checkpoint, not Q4 speed or compatibility tests.
Recorded release date
2026-08-15
Date evidence
Official Empero source checkpoint and GGUF repositories created 15 August 2026; surfaced in the bounded trending scan on 8 October 2026.
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.
GSM8K
87 / 100
Solving grade-school math word problems. Published answer accuracy; known small subsets are separate.
Benchmark efficiency: 15.052 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: Empero publisher evaluation with lm-evaluation-harness and the Hugging Face backend, using gsm8k_cot flexible-extract exact match. Base and student used identical settings; generation sampling was temperature 0.6, top-p 0.95 and top-k 20. The card does not state the evaluated GSM8K sample count.
Source-checkpoint result, not an independent test and not a direct benchmark of the selected Q4_K_M file. The 5.780 GB file excludes runtime, KV cache and context memory; it does not establish device compatibility or token speed.
Empero evaluation across 57 subjects, about 1,700 questions. Zero-shot CoT, flexible extraction; not the full MMLU test.
Benchmark efficiency: 12.993 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: Empero publisher evaluation with lm-evaluation-harness and the Hugging Face backend, using mmlu_flan_cot_zeroshot flexible-extract accuracy across all 57 subjects and about 1,700 questions. Base and student used identical settings; generation sampling was temperature 0.6, top-p 0.95 and top-k 20.
Source-checkpoint result, not an independent test and not a direct benchmark of the selected Q4_K_M file. This limited CoT protocol remains separate from standard MMLU views. Long context, backend, prompt formatting and quantization can materially change behavior and memory use.
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 5.78 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 5.78 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.
Reasoning distillation, not an official Qwen 3.8 9B release. Use a recent llama.cpp build with Qwen3.5 / Gated DeltaNet support; older builds can fail to load it. Apache-2.0 licensed. The 5.780 GB Q4_K_M file is only the weight file: runtime, KV cache and long contexts need additional memory. The recorded MMLU and GSM8K results are from the source checkpoint, not Q4 speed or compatibility tests. The selected weights use 5.78 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.