Models › DeepSeek-R1 family

DeepSeek-R1-Distill-Qwen-1.5B

deepseek-ai MIT out 21 months ago

1.78B parameters, text in, text out, 128K tokens of context. 1 provider serves it.

Verified 2026-10-25 Rank #85 in LLMs · score 102.1 method v1 Sources 3 Downloads 30d 1.3M · #95 of 619 tracked

Changed this week: 1 new quantized build on the Hub (277 in all).2026-10-24

Can I use it?MITPermissivelicence file2026-10-24
Do people use it?1.3Mdownloads, 30 days#95 of 619 we track · top 15%+10 likes, downloads −1% this week1,644 likesHugging Face2026-10-24

Worth reading

Picked by rule from 33 tracked pieces: the lab's own post, the most shared, a field report, the latest.

Most discussed · 1,843 HN pts
github.com 2025-01-20 1,843 HN pts · 663 comments 2.1k words about the DeepSeek R1 family family
Latest · 6 months ago

ZAYA1-8B matches DeepSeek-R1 on math with less than 1B active parameters

Zyphra released ZAYA1-8B, a model that matches DeepSeek-R1 on math benchmarks while using less than 1 billion active parameters.

  • The model was trained entirely on a 1,024 node AMD cluster built with IBM using AMD Pensando Pollara interconnect.
  • Zyphra trained ZAYA1-8B end to end on AMD Instinct MI300X GPUs for pretraining, midtraining, and supervised fine-tuning.
firethering.com 2026-05-07 117 HN pts · 56 comments 1.3k words about the DeepSeek R1 family family

25 best of 33 tracked

The 2 picks above, plus these 23. Top is the radar's score: discussion, source authority and the lab's own posts, fading with age.

  1. PaperDeepSeek-R1: Incentivizing Reasoning Capability in LLMs via RLarxiv.org · 2025-01-25 · 1,351 HN pts
  2. ArticlePromising results from DeepSeek R1 for codesimonwillison.net · 2025-01-28 · 979 HN pts
  3. ArticleRun DeepSeek R1 Dynamic 1.58-bitunsloth.ai · 2025-01-28 · 767 HN pts
  4. ArticleOpen-R1: an open reproduction of DeepSeek-R1huggingface.co · 2025-01-28 · 394 HN pts
  5. CodeDeepseek R1 Distill 8B Q40 on 4 x Raspberry Pi 5github.com · 2025-02-15 · 306 HN pts
  6. ArticleHow to Run DeepSeek R1 671B Locally on a $2000 EPYC Serverdigitalspaceport.com · 2025-02-01
  7. CodeDeepSeek-R1-671B-Q4_K_M with 1 or 2 Arc A770 on Xeongithub.com · 2025-03-06
  8. ArticleThe Illustrated DeepSeek-R1newsletter.languagemodels.co · 2025-01-27 · 578 HN pts
  9. ArticleDeepSeek R1 Is Now Available on Azure AI Foundry and GitHubazure.microsoft.com · 2025-01-29 · 109 HN pts
  10. DiscussionComplete hardware and software setup for running Deepseek-R1 locallytwitter.com · 2025-01-29 · 250 HN pts
  11. CodeTinyZero: Reproduction of DeepSeek R1 Zero in countdown and multiplication tasksgithub.com · 2025-01-25
  12. CodeOpen Reproduction of DeepSeek-R1github.com · 2025-01-27
  13. ArticleOfficial DeepSeek R1 Now on Ollamaollama.com · 2025-01-20
  14. ArticleBerkeley Researchers Replicate DeepSeek R1's Core Tech for Just $30: A Small Modxyzlabs.substack.com · 2025-01-28
  15. CodeImplementing DeepSeek R1's GRPO algorithm from scratchgithub.com · 2025-04-13
  16. ArticleMini-R1: Reproduce DeepSeek R1 "Aha Moment"philschmid.de · 2025-01-31
  17. DiscussionDeepSeek R1 671B running on 2 M2 Ultras faster than reading speedtwitter.com · 2025-01-29
  18. ArticleHow to run DeepSeek R1 locallyworkos.com · 2025-01-29
  19. ArticleHow to Run DeepSeek R1 Distilled Reasoning Models on RyzenAI and Radeon GPUsguru3d.com · 2025-02-02
  20. ArticleA new, faster DeepSeek R1-0528 variant appears from German labventurebeat.com · 2025-07-05
  21. ArticleRunning DeepSeek R1 Models Locally on NPUblogs.windows.com · 2025-02-01
  22. ArticleExperience the DeepSeek R1 Distilled 'Reasoning' Models on Ryzen AI and Radeoncommunity.amd.com · 2025-02-04
  23. ArticleDeepSeek R1 is far better than OpenAI o1 at finding bugs in pull requestsgreptile.com · 2025-01-30

Where to run it

Live hosted endpoints, cheapest first, USD per million tokens. Ties break on output price, then provider name.

#Cheapest live rowIn /1MOut /1MContextQuantSeen
1 Featherless — — — — Oct 25

All 1 provider →

Where it's used

Hugging Face does not say who downloads a model or with what. These are the proxies: API providers listing it, quantized builds, fine-tunes/adapters/merges, and Spaces that load it.

Served by 1 API provider; heavily run locally (277 quantized builds); a big base for builders (1,071 fine-tunes, adapters and merges).

  • As a service1Featherless
  • On own hardware277quantized builds
  • Built on1,071704 fine-tunes · 340 adapters · 27 merges
  • In apps100+Hugging Face Spaces

Top Spaces running it: pliny-the-prompter/obliteratus ♥ 621 · hesamation/primer-llm-embedding ♥ 374 · KBaba7/Quant ♥ 51 · FallnAI/Quantize-HF-Models ♥ 19

Will it fit?

Weights only, an estimate: leave room for the KV cache. Method

Fits a 16 GB card at INT4

About 1.1 GB at INT4, 2.1 GB at FP8, 4.3 GB at BF16: weights only, so leave room for the KV cache.

16 GB card64 GB Mac2×80 GB8×80 GBINT4: about 1.1 GB of weights (estimate; KV cache and activations extra)INT41.1 GBFP8: about 2.1 GB of weights (estimate; KV cache and activations extra)FP82.1 GBBF16: about 4.3 GB of weights (estimate; KV cache and activations extra)BF164.3 GB
16 GB card64 GB Mac2×80 GB8×80 GBINT4: about 1.1 GB of weights (estimate; KV cache and activations extra)INT41.1 GBFP8: about 2.1 GB of weights (estimate; KV cache and activations extra)FP82.1 GBBF16: about 4.3 GB of weights (estimate; KV cache and activations extra)BF164.3 GB

Estimate params × bytes per param × 1.2 · how we estimate

The story so far

Weights, every dated article, and repo commits on one rail.

Most coverage came in the first two weeks

Teal is the weights (2025-01-20), amber triangles are 10 dated articles (each links to it), grey ticks are repo commits.

What people built on it

1,348 derivatives on the Hub. Which build to run, by runtime: the most downloaded in each class.

1,348 derivatives on the Hub, most of them fine-tunes

From the Hugging Face model tree; quantized builds in teal, fine-tunes, merges and adapters in greys.

277 quantized (Hugging Face model tree)704 fine-tunes (Hugging Face model tree)27 merges (Hugging Face model tree)340 adapters (Hugging Face model tree)277 quantized704 fine-tunes27 merges340 adapters
277 quantized (Hugging Face model tree)704 fine-tunes (Hugging Face model tree)27 merges (Hugging Face model tree)340 adapters (Hugging Face model tree)277 quantized704 fine-tunes27 merges340 adapters

All variants →

Reference

Everything else, folded: the full tables, every source.

Benchmarks

6 rows

Benchmarks 6 rows

measured third-party leaderboard rowauthor-reported number from the model card or eval files (6)No confidence intervals unless the source gave them; settings differ between rows, so compare within a benchmark, not across. Date = the benchmark's own date when it gives one, else when we read it.
BenchmarkValueSetting / notesReported byDate
author-reported AIME 2024 · Reason through hard problems28.9 pass@1DeepSeek-R1-Distill-Qwen-1.5Bmodel author2026-10-07
author-reported AIME 2024 · Reason through hard problems52.7 otherDeepSeek-R1-Distill-Qwen-1.5Bmodel author2026-10-07
author-reported Codeforces · Write code with agents954 ratingDeepSeek-R1-Distill-Qwen-1.5Bmodel author2026-10-07
author-reported GPQA Diamond · Reason through hard problems33.8 pass@1DeepSeek-R1-Distill-Qwen-1.5Bmodel author2026-10-07
author-reported LiveCodeBench · Write code with agents16.9 pass@1DeepSeek-R1-Distill-Qwen-1.5Bmodel author2026-10-07
author-reported MATH-500 · Reason through hard problems83.9 pass@1DeepSeek-R1-Distill-Qwen-1.5Bmodel author2026-10-07

Use-case evidence

6 use cases

What it is good at 6 use cases

Labels are evidence, not verdicts: measured a third-party leaderboard row for this model; author-reported a number the model author published in the card or eval files; structural a deterministic signal from the name, config or chat template, or a decision-model estimate. Each chip links to its source. All use cases.

Facts

20 fields

Listed in LLMs

Facts

Pipeline tagtext-generation
Librarytransformers
ArchitecturesQwen2ForCausalLM
Model typeqwen2
Dtypebfloat16
Params by dtypeBF16: 1,777,088,000
Size bandS
MoEno
Context length131,072 (config.json max_position_embeddings)
PapersarXiv:2501.12948
LicenseMIT (mit)
Hub snapshot2026-10-25

Servability

vLLM · SGLang

Servability

vLLM: supported · Qwen2ForCausalLM · 7050ef881ff0835f6890a47db1859a24c65481d6SGLang: supported · Qwen2ForCausalLM · 773cb938fe9484a8f7e7e46fb1b1fe96412c59ed

vLLM registry (7050ef881ff0835f6890a47db1859a24c65481d6) · SGLang registry (773cb938fe9484a8f7e7e46fb1b1fe96412c59ed) · Matched by architecture class name against each project's registry on main; 'supported' means the architecture is registered, not that this checkpoint was tested.

Hardware fit

3 estimates

Hardware fit ESTIMATE

Weights-only memory for DeepSeek-R1-Distill-Qwen-1.5B: params × bytes/param × 1.2 overhead. KV cache and activations are extra. How this is computed.

BF16 (2 bytes/param)4.3 GB · Single GPU (<24 GB)
FP8 (1 byte/param)2.1 GB · Edge (<4 GB)
INT4 (0.5 bytes/param)1.1 GB · Edge (<4 GB)

Weights only (params × bytes/param × 1.2 overhead); KV cache and activations extra.

All variants

40 variants

Lineage

Original model Family: deepseek-ai/DeepSeek-R1 1,348 derivatives on the Hub

quantized: 277finetune: 704adapter: 340merge: 27

Top variants (40 shown, ranked by downloads)

Relation
Quant
40 rows
Variant Relation Quant Params Band License Author Likes Downloads
unsloth/DeepSeek-R1-Distill-Qwen-1.5B-GGUF quantized GGUF — — apache-2.0 unsloth 165 1.7M
litert-community/DeepSeek-R1-Distill-Qwen-1.5B finetune — — — mit litert-community 56 819.7k
agentica-org/DeepScaleR-1.5B-Preview finetune — 1.78B S mit agentica-org 584 752.6k
bartowski/DeepSeek-R1-Distill-Qwen-1.5B-GGUF quantized GGUF — — — bartowski 91 637k
unsloth/DeepSeek-R1-Distill-Qwen-1.5B-unsloth-bnb-4bit quantized -bnb 1.81B S apache-2.0 unsloth 17 354.3k
lmstudio-community/DeepSeek-R1-Distill-Qwen-1.5B-GGUF quantized GGUF — — — lmstudio-community 16 223.8k
mlx-community/deepseek-r1-distill-qwen-1.5b finetune — 1.78B S — mlx-community 24 209.1k
unsloth/DeepSeek-R1-Distill-Qwen-1.5B-bnb-4bit quantized -bnb 1.82B S apache-2.0 unsloth 11 191.9k
nvidia/DLER-R1-1.5B-Research finetune — 1.78B S — nvidia 21 128.9k
unsloth/DeepSeek-R1-Distill-Qwen-1.5B finetune — 1.78B S mit unsloth 16 104.5k
salakash/SamKash-Tolstoy adapter — — — apache-2.0 salakash 758 42.5k
onnx-community/DeepSeek-R1-Distill-Qwen-1.5B-ONNX quantized — — — — onnx-community 61 75.8k
mlx-community/DeepSeek-R1-Distill-Qwen-1.5B-8bit quantized -8bit 1.78B S — mlx-community 3 77.3k
mlx-community/DeepSeek-R1-Distill-Qwen-1.5B-4bit quantized -4bit 1.78B S — mlx-community 6 72.5k
RedHatAI/DeepSeek-R1-Distill-Qwen-1.5B-quantized.w8a8 quantized -quant 1.78B S mit RedHatAI 2 50.6k
Zyphra/ZR1-1.5B finetune — 1.78B S mit Zyphra 77 44.5k
agentica-org/DeepCoder-1.5B-Preview finetune — 1.78B S mit agentica-org 76 34.1k
Sweaterdog/Andy-3.5 quantized GGUF — — apache-2.0 Sweaterdog 6 36k
knoveleng/Open-RS3 finetune — 1.78B S mit knoveleng 21 33.6k
ggml-org/DeepSeek-R1-Distill-Qwen-1.5B-Q4_0-GGUF quantized Q4_0 — — — ggml-org 5 34.4k
OpenVINO/DeepSeek-R1-Distill-Qwen-1.5B-int4-ov quantized int4 — — mit OpenVINO 2 30.9k
hbx/JustRL-DeepSeek-1.5B finetune — 1.78B S apache-2.0 hbx 12 27.9k
Brianpuz/DeepSeek-R1-Distill-Qwen-1.5B-Q4_0-Q2_K-GGUF quantized Q4_0 — — mit Brianpuz 0 22.8k
Vinnnf/Thinkless-1.5B-Warmup finetune — 1.78B S apache-2.0 Vinnnf 4 19.9k
DevQuasar-7/deepseek-ai.DeepSeek-R1-Distill-Qwen-1.5B-GGUF quantized GGUF — — — DevQuasar-7 2 18.9k
GenPRM/GenPRM-1.5B finetune — 1.78B S mit GenPRM 2 17.8k
second-state/DeepSeek-R1-Distill-Qwen-1.5B-GGUF quantized GGUF — — mit second-state 0 16.1k
mlx-community/DeepSeek-R1-Distill-Qwen-1.5B-6bit quantized — 1.78B S — mlx-community 0 16.1k
huihui-ai/DeepSeek-R1-Distill-Qwen-1.5B-abliterated finetune — 1.78B S — huihui-ai 7 15.6k
NexaAI/DeepSeek-R1-Distill-Qwen-1.5B-NexaQuant quantized GGUF — — apache-2.0 NexaAI 92 11.2k
0xfaskety/task-1-microsoft-Phi-3-mini-4k-instruct adapter — — — — 0xfaskety 1 15.3k
knoveleng/Open-RS2 finetune — 1.78B S mit knoveleng 1 13.6k
ThomasBaruzier/DeepSeek-R1-ReDistill-Qwen-1.5B-v1.1-GGUF quantized GGUF — — mit ThomasBaruzier 0 13.5k
knoveleng/Open-RS1 finetune — 1.78B S mit knoveleng 4 13.1k
QuantFactory/DeepScaleR-1.5B-Preview-GGUF quantized GGUF — — mit QuantFactory 2 12.5k
mlx-community/DeepSeek-R1-Distill-Qwen-1.5B-3bit quantized — 1.78B S — mlx-community 1 12.3k
Mungert/DeepCoder-1.5B-Preview-GGUF quantized GGUF — — mit Mungert 4 11.9k
Mungert/Nemotron-Research-Reasoning-Qwen-1.5B-GGUF quantized GGUF — — cc-by-nc-4.0 Mungert 2 10.6k
hdnh2006/DeepSeek-R1-Distill-Qwen-1.5B-GGUF quantized GGUF — — apache-2.0 hdnh2006 3 10.5k
zwhe99/DeepMath-1.5B finetune — 1.78B S mit zwhe99 5 10.2k

Repository changelog

12 commits
changed in the last 7 daysOther: 2026-10-24all changes

Repository changelog 12 commits

DateCommitSHA
2025-02-24 Update bib info ad9f0ae
2025-02-09 Update tokenizer_config.json 530ca3e
2025-02-01 Update README.md 6393b75
2025-01-26 Update README.md 0092dee
2025-01-23 Update README.md 5d85599
2025-01-22 Update tokenizer_config.json 164af3f
2025-01-22 Update tokenizer_config.json e937840
2025-01-21 Add generation_config.json 73d63fa
2025-01-21 add library tag for better code snippets and tags (#1) aa76ddc
2025-01-20 Release DeepSeek-R1 80da49e
2025-01-20 Add files using upload-large-folder tool e164738
2025-01-20 initial commit 8f1dfda

All providers

1 provider · 1 endpoint

Where to run 1 providers · 1 endpoints

Hosted endpoints observed for DeepSeek-R1-Distill-Qwen-1.5B, sorted by input price (USD per million tokens). Each row names its observer and date; prices change daily, so check the source before quoting.

ProviderModel refContextQuant$/M in$/M outtok/sTTFTToolsStatusObserved
Featherless
hf
deepseek-ai/DeepSeek-R1-Distill-Qwen-1.5B — — — — — — — live 2026-10-25

Articles and coverage

33 pieces

Ranked by source signals (HN, Lobsters, authority domains, official posts) and recency. Summaries are generated from a stored copy of the article text; every sentence cites a span of that text, and nothing is shown that failed the citation check.

Analysis9

firethering.com2026-05-07HN front pageabout the DeepSeek R1 familyHN 117 pts · 56 comments1,293 words
Zyphra released ZAYA1-8B, a model that matches DeepSeek-R1 on math benchmarks while using less than 1 billion active parameters. The 8.4B parameter mixture of experts model activates only 760M parameters at inference and employs Markovian RSA to scale performance with compute budget. It requires a specific vLLM fork for local deployment and is available under an Apache 2.0 license.written, reviewed, cited
  • The model was trained entirely on a 1,024 node AMD cluster built with IBM using AMD Pensando Pollara interconnect.
  • Zyphra trained ZAYA1-8B end to end on AMD Instinct MI300X GPUs for pretraining, midtraining, and supervised fine-tuning.
  • The model requires Zyphra's own fork of vLLM to run properly because the standard vLLM install won't work.
arxiv.org2025-01-25authorityHN front pageabout the DeepSeek R1 familyHN 1,351 pts · 1,056 comments371 words
simonwillison.net2025-01-28authorityHN front pageabout the DeepSeek R1 familyHN 979 pts · 746 comments345 words
A PR for llama.cpp delivers x2 speed for WASM by optimizing SIMD instructions for qX_K_q8_K and qX_0_q8_0 dot product functions. Surprisingly, 99% of the code in this PR is written by DeekSeek-R1. The model spent 3-5 minutes thinking about each prompt to generate the optimization.written, reviewed, cited
github.com2025-01-20authorityHN front pageabout the DeepSeek R1 familyHN 1,843 pts · 663 comments2,107 words
unsloth.ai2025-01-28authorityHN front pageabout the DeepSeek R1 familyHN 767 pts · 332 comments
huggingface.co2025-01-28authorityHN front pageabout the DeepSeek R1 familyHN 394 pts · 234 comments890 words
github.com2025-02-15authorityHN front pageabout the DeepSeek R1 familyHN 306 pts · 156 comments766 words
newsletter.languagemodels.co2025-01-27HN front pageabout the DeepSeek R1 familyHN 578 pts · 118 comments1,715 words
azure.microsoft.com2025-01-29authorityHN front pageabout the DeepSeek R1 familyHN 109 pts · 49 comments

Community1

twitter.com2025-01-29HN front pageabout the DeepSeek R1 familyHN 250 pts · 192 comments
All coverage tracked for this model (33) — append-only, nothing is ever removed
TitleSourcePublishedFirst seenSignals
DeepSeek-R1-Distill-Qwen-1.5B: Efficient Reasoningemergentmind.com—2026-10-07exa
DeepSeek R1 Distill Qwen 1.5B — 1.5B model specs & benchmarks | BestLLMforbestllmfor.com—2026-10-07exa
DeepSeek-R1 vs DeepSeek R1 Distill Qwen 1.5B: Benchmarks, Pricing & Which Is Better in 2026llm-stats.com—2026-10-07exa
ZAYA1-8B matches DeepSeek-R1 on math with less than 1B active parametersfirethering.com2026-05-072026-10-07hn
DeepSeek R1 1.5B Review: Run Reasoning on Your Laptop - TokenMix Blogtokenmix.ai2026-04-242026-10-07exa
A new, faster DeepSeek R1-0528 variant appears from German labventurebeat.com2025-07-052026-10-07hn
Implementing DeepSeek R1's GRPO algorithm from scratchgithub.com2025-04-132026-10-07hn
DeepSeek-R1-671B-Q4_K_M with 1 or 2 Arc A770 on Xeongithub.com2025-03-062026-10-07hn
Deepseek R1 Distill 8B Q40 on 4 x Raspberry Pi 5github.com2025-02-152026-10-07hn
Experience the DeepSeek R1 Distilled 'Reasoning' Models on Ryzen AI and Radeoncommunity.amd.com2025-02-042026-10-07hn
How to Run DeepSeek R1 Distilled Reasoning Models on RyzenAI and Radeon GPUsguru3d.com2025-02-022026-10-07hn
How to Run DeepSeek R1 671B Locally on a $2000 EPYC Serverdigitalspaceport.com2025-02-012026-10-07hn
Running DeepSeek R1 Models Locally on NPUblogs.windows.com2025-02-012026-10-07hn
How to run 1.58bit DeepSeek R1 with Open WebUIdocs.openwebui.com2025-01-312026-10-07hn
Mini-R1: Reproduce DeepSeek R1 "Aha Moment"philschmid.de2025-01-312026-10-07hn
DeepSeek R1 is far better than OpenAI o1 at finding bugs in pull requestsgreptile.com2025-01-302026-10-07hn
DeepSeek R1 Is Now Available on Azure AI Foundry and GitHubazure.microsoft.com2025-01-292026-10-07hn
How to run DeepSeek R1 locallyworkos.com2025-01-292026-10-07hn
Complete hardware and software setup for running Deepseek-R1 locallytwitter.com2025-01-292026-10-07hn
DeepSeek R1 671B running on 2 M2 Ultras faster than reading speedtwitter.com2025-01-292026-10-07hn
Berkeley Researchers Replicate DeepSeek R1's Core Tech for Just $30: A Small Modxyzlabs.substack.com2025-01-282026-10-07hn
Promising results from DeepSeek R1 for codesimonwillison.net2025-01-282026-10-07hn
Run DeepSeek R1 Dynamic 1.58-bitunsloth.ai2025-01-282026-10-07hn
Open-R1: an open reproduction of DeepSeek-R1huggingface.co2025-01-282026-10-07hn
The Illustrated DeepSeek-R1newsletter.languagemodels.co2025-01-272026-10-07hn
Open Reproduction of DeepSeek-R1github.com2025-01-272026-10-07hn
DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via RLarxiv.org2025-01-252026-10-07hn
TinyZero: Reproduction of DeepSeek R1 Zero in countdown and multiplication tasksgithub.com2025-01-252026-10-07hn
DeepSeek-R1-Distill-Qwen-1.5B: The best small-sized LLM? | by Mehul Gupta | Data Science in Your Pocket | Mediummedium.com2025-01-242026-10-07exa
Official DeepSeek R1 Now on Ollamaollama.com2025-01-202026-10-07hn
DeepSeek-R1github.com2025-01-202026-10-07hn
DeepSeek-R1-Distill-Qwen-1.5B: Specs & Benchmarks | AI/TLDRai-tldr.dev2025-01-202026-10-07exa
DeepSeek-R1 Model Series: From Light Distillation to Full-Scale | RiseUniontheriseunion.com2025-01-012026-10-07exa

Papers

1 paper

Papers 1

arXiv links found in the model card and its tags. "Peer-reviewed" is shown only with evidence: a published venue in OpenAlex (measured) or the authors' own journal reference on arXiv (reported).

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Sources

3 sources

Sources

Hub snapshot: 2026-10-25 · HF API: 2026-10-24 21:33 UTC · Providers: 2026-10-24 21:44 UTC · Articles: 2026-10-24 21:45 UTC · Summary: 2026-10-07 15:00 UTC · Last verified 2026-10-25

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