DeepSeek-R1-Distill-Qwen-1.5B-Q4_K_M
This seed file names one model file by its SHA-256. The player downloads it, checks every byte and runs it on your CPU, or refuses.
- Passed start-up
- Same on Linux and Windows
- Same on AMD and Intel, same OS
Use this seed
Download the playerHave the player? Run itNeeds
- RAM: the player refuses below 1.04 GiB
- Peak memory: not measured for this seed. The player compares your RAM with the file size, not with the memory it will use; on the 2 seeds we measured, the largest process peaked 49% and 77% above the file size (Linux, )
- Free disk ≥ 1.09 GiB
- x86-64 processor with AVX2, FMA and F16C
- Linux (glibc 2.35 or newer) or Windows 11 (builds 26100 and 26200 measured)
The player checks RAM, free disk and the processor before downloading, and stops if any of them falls short; a value it cannot read does not stop it.
Downloads 1.04 GiB from Hugging Face.
Seed file · 526 bytes · already in the player's archive,catalogue folderSeed r1-qwen-15b · 526 bytes
Model by deepseek-ai · file converted by bartowski (bartowski/DeepSeek-R1-Distill-Qwen-1.5B-GGUF)
MIT · No extra terms (keep the licence notice) · label and model card read; licence file not opened · as declared, read · not legal advice
Linux vs Windows comparison: same tokens on 3 test questions, 2 machines, .
Run it
From the unpacked player folder. --maison is the folder for this model and your conversations.
# germer: download the model file and check every byte./memown germer catalogue/r1-qwen-15b.graine.json --maison ~/ia/r1-qwen-15b Expected: a line starting with VERDICT : VERT (VERT: all four checks passed, including the byte-for-byte check)
# germer: download the model file and check every byte.\memown.exe germer catalogue\r1-qwen-15b.graine.json --maison "$env:USERPROFILE\ia\r1-qwen-15b" Expected: a line starting with VERDICT : VERT (VERT: all four checks passed, including the byte-for-byte check)
Compare your answer with ours
Ask it first, right after germer, in a new --maison folder. Type the question exactly, in French: the published fingerprint is for these exact bytes.
Expected: 256 tokens, seen on 5 machines (Linux and Windows 11), to , 0 differences · fingerprint 54ff31663a15d53f327db1b2667f842f18a228809e9205bfe32f2c1e047a991c Click once to select the whole value.
# parler: ask a question./memown parler --maison ~/ia/r1-qwen-15b --dire "Quelle est la capitale de la France ?"grep -c '"ids_sha256":"54ff31663a15d53f327db1b2667f842f18a228809e9205bfe32f2c1e047a991c"' ~/ia/r1-qwen-15b/vies/vie/journal.json Expected: 1
# parler: ask a question.\memown.exe parler --maison "$env:USERPROFILE\ia\r1-qwen-15b" --dire "Quelle est la capitale de la France ?"Select-String -Quiet -SimpleMatch -Path "$env:USERPROFILE\ia\r1-qwen-15b\vies\vie\journal.json" -Pattern '"ids_sha256":"54ff31663a15d53f327db1b2667f842f18a228809e9205bfe32f2c1e047a991c"'Expected: True
1 or True: your tokens are the same as ours. 0 or False: they differ. Tell us either way.
To ask your own question, change the text after --dire. Keep the test question to compare with ours.
What this seed names
- Model file
DeepSeek-R1-Distill-Qwen-1.5B-Q4_K_M.gguf- Size
- 1,117,320,800 bytes (1.04 GiB)
- SHA-256
1741e5b2d062b07acf048bf0d2c514dadf2a48f94e2b4aa0cfe069af3838ee2f- Hosted at
- Hugging Face gave the same SHA-256 for this file (checked ) · If that file changes, the player refuses it.
- Licence
- MIT · No extra terms
- Seed file
r1-qwen-15b.graine.json· 526 bytes ·d7c8d7f78d7b5b994217f023cba5478f553bf8313e32c63fdb36d9f0eee55f47
What we measured
- Start-up: passed on when the seed was made (Linux, glibc 2.35).
- Linux vs Windows: same tokens · 3 test questions · 2 machines · · data (JSON)
- AMD vs Intel, same OS: same tokens · 3 test questions · 2 machines ·
- 12 expected answers · up to 5 machines · 0 differences
- 37.4–59.5 tokens/s · 3 rented AMD EPYC servers shared with other work · 8 threads · short answers in a new conversation · player 1.2, same engines as 1.3.1 · . Your speed: not measured.
Not measured for this seed
- Peak memory
Not measured for any seed: see Measurements.
12 expected answers
| Question | Expected | Measured |
|---|---|---|
| Quelle est la capitale de la France ? (“What is the capital of France?”) | 256 tokens · SHA-256 of the token IDs 54ff3166…a991c | 5 machines |
| Continue la suite : 2, 4, 8, 16, (“Continue the sequence: 2, 4, 8, 16,”) | 249 tokens · SHA-256 of the token IDs 233e68a6…81af8 | 3 machines |
| What is the capital of Italy? | 256 tokens · SHA-256 of the token IDs f026d9df…cddf6 | 4 machines |
| Continue la suite : 2, 4, 8, 16, (“Continue the sequence: 2, 4, 8, 16,”) | 256 tokens · SHA-256 of the token IDs d2fddd04…68472 | 4 machines |
| Explique en deux phrases pourquoi le ciel est bleu. (“Explain in two sentences why the sky is blue.”) | 256 tokens · SHA-256 of the token IDs 002d3130…3f289 | 3 machines |
| Recopie exactement : le chat dort sur le tapis rouge et la pluie tombe doucement. (“Copy exactly: the cat sleeps on the red rug and the rain falls gently.”) | 256 tokens · SHA-256 of the token IDs a680c3ac…de6c4 | 3 machines |
| Donne trois nombres premiers entre 10 et 30. (“Give three prime numbers between 10 and 30.”) | 256 tokens · SHA-256 of the token IDs 00f4a294…5f915 | 3 machines |
| Traduis en anglais : la mer est calme ce soir. (“Translate into English: the sea is calm tonight.”) | 115 tokens · SHA-256 of the token IDs 450f0612…73c2a | 3 machines |
| Quel est le plus grand océan du monde ? (“What is the largest ocean in the world?”) | 247 tokens · SHA-256 of the token IDs a1a897a7…a81db | 3 machines |
| Écris une phrase de politesse pour finir un e-mail. (“Write a polite sentence to end an email.”) | 246 tokens · SHA-256 of the token IDs 0af91532…31ad9 | 3 machines |
| Résume en une phrase ce que fait un four à pain. (“Sum up in one sentence what a bread oven does.”) | 256 tokens · SHA-256 of the token IDs 4e19478a…ca8cb | 3 machines |
| Continue la suite : 3, 6, 12, 24, (“Continue the sequence: 3, 6, 12, 24,”) | 256 tokens · SHA-256 of the token IDs 71a87273…271bf | 3 machines |
The seed file (JSON, 526 bytes)
{"matiere":{"nom":"DeepSeek-R1-Distill-Qwen-1.5B-Q4_K_M.gguf","octets":1117320800,"sha256":"1741e5b2d062b07acf048bf0d2c514dadf2a48f94e2b4aa0cfe069af3838ee2f","substrat":["hf:bartowski/DeepSeek-R1-Distill-Qwen-1.5B-GGUF/DeepSeek-R1-Distill-Qwen-1.5B-Q4_K_M.gguf"]},"nom":"r1-qwen-15b","notes":"licence declaree par l hebergeur : mit. les poids ne sont pas ici : ils sont NOMMES.","recette":{"classe":"x86-64-fils8","empreinte":"869bef8788166262e4a72fe04f0809756f561a2bae03a52a95e3fb7f294b8226"},"scellee_le":"2026-08-17","v":1}Licence as we read it, in French
Aucun seuil, aucune obligation de nommage.
La seule chose qui suit la redistribution est la mention de droit d'auteur et le texte de la licence, à conserver dans toute copie.
La carte amont dit : « This code repository and the model weights are licensed under the MIT License.
DeepSeek-R1 series support commercial use, allow for any modifications and derivative works, including, but not limited to, distillation for training other LLMs. » Elle précise aussi que ce modèle est « derived from Qwen-2.5 series, which are originally licensed under Apache 2.0 License » — l'articulation des deux licences est une DÉCLARATION du fournisseur, pas une clause de son texte.
étiquette et carte du dépôt amont lues (étiquette croisée README brut + API) ; le fichier de licence lui-même n'a pas été ouvert