Models › DeepSeek-R1 family

DeepSeek-R1-0528

deepseek-ai MIT out 17 months ago

685B parameters (8 of 256 experts per token), text in, text out, 160K tokens of context. 5 providers serve it from $0.50 per million input tokens.

Verified 2026-10-25 Rank #41 in LLMs · score 109.2 method v1 Sources 4 Downloads 30d 165.2k · #266 of 619 tracked

Can I run it?411GB at INT4Estimateneeds a multi-GPU nodemethod
What does it cost?$0.50/1M incheapest of 4DeepInfrafp42026-10-25
Can I use it?MITPermissivelicence file2026-10-24
Does it work?71.4on Aider Polyglot#1 of 13 measuredleaderboard2025-06-06
Do people use it?165.2kdownloads, 30 days#266 of 619 we track · top 43%+4 likes, downloads −5% this week2,490 likesHugging Face2026-10-24

Worth reading

Picked by rule from 41 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 41 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. ArticleDeepSeek R1 0528 — Architecture, Evals & Inference Performance | InferenceXinferencex.semianalysis.com · undated
  20. ArticleDeepSeek R1 0528 - Intelligence, Performance & Price ...artificialanalysis.ai · undated
  21. ArticleHow to Run DeepSeek R1 Distilled Reasoning Models on RyzenAI and Radeon GPUsguru3d.com · 2025-02-02
  22. ArticleA new, faster DeepSeek R1-0528 variant appears from German labventurebeat.com · 2025-07-05
  23. ArticleDeepSeek-R1-0528 Did Not Have a Momentthezvi.substack.com · 2025-06-06

Where to run it

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

4 providers from $0.50

4 providers with a live price, from $0.50 to $0.70 per million input tokens; the median is $0.54. One dot per provider, cheapest in teal.

$0.010$0.10$1.00$10.00DeepInfra: $0.50 in / $2.15 out per 1M · observed 2026-10-25 · https://huggingface.co/api/models/deepseek-ai/DeepSeek-R1-0528?expand[]=inferenceProviderMappingSiliconFlow: $0.50 in / $2.18 out per 1M · observed 2026-10-24 · https://openrouter.ai/deepseek/deepseek-r1-0528StreamLake: $0.57 in / $2.29 out per 1M · observed 2026-10-24 · https://openrouter.ai/deepseek/deepseek-r1-0528Novita: $0.70 in / $2.50 out per 1M · observed 2026-10-25 · https://huggingface.co/api/models/deepseek-ai/DeepSeek-R1-0528?expand[]=inferenceProviderMappingcheapest $0.50median $0.54
$0.010$0.10$1.00$10.00DeepInfra: $0.50 in / $2.15 out per 1M · observed 2026-10-25 · https://huggingface.co/api/models/deepseek-ai/DeepSeek-R1-0528?expand[]=inferenceProviderMappingSiliconFlow: $0.50 in / $2.18 out per 1M · observed 2026-10-24 · https://openrouter.ai/deepseek/deepseek-r1-0528StreamLake: $0.57 in / $2.29 out per 1M · observed 2026-10-24 · https://openrouter.ai/deepseek/deepseek-r1-0528Novita: $0.70 in / $2.50 out per 1M · observed 2026-10-25 · https://huggingface.co/api/models/deepseek-ai/DeepSeek-R1-0528?expand[]=inferenceProviderMappingcheapest $0.50 · median $0.54 (white tick)
#Cheapest 5In /1MOut /1MContextQuantSeen
1 DeepInfra $0.50 $2.15 160K fp4 Oct 25
2 SiliconFlow $0.50 $2.18 160K fp8 Oct 24
3 StreamLake $0.57 $2.29 125K unknown Oct 24
4 Novita $0.70 $2.50 160K — Oct 25
5 Featherless — — — — Oct 25

All 5 providers →

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.

Widely served (5 API providers); 47 quantized builds for local use; a big base for builders (79 fine-tunes, adapters and merges).

  • As a service5DeepInfra, Featherless, Novita, SiliconFlow +1
  • On own hardware47quantized builds
  • Built on7959 fine-tunes · 16 adapters · 4 merges
  • In apps100+Hugging Face Spaces

Top Spaces running it: umint/ai ♥ 258 · hadadrjt/ai ♥ 86 · ginigen/deepseek-r1-0528-API ♥ 62 · linusorii/deepsite-v2 ♥ 61

Will it fit?

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

Needs an 8×80 GB node even at INT4

About 411 GB at INT4, 821 GB at FP8, 1.64 TB at BF16: weights only, so leave room for the KV cache. Every expert must be resident, so total parameters count.

16 GB card64 GB Mac2×80 GB8×80 GBINT4: about 411 GB of weights (estimate; KV cache and activations extra)INT4411 GBFP8: about 821 GB of weights (estimate; KV cache and activations extra)FP8821 GBBF16: about 1.64 TB of weights (estimate; KV cache and activations extra)BF161.64 TB
16 GB card64 GB Mac2×80 GB8×80 GBINT4: about 411 GB of weights (estimate; KV cache and activations extra)INT4411 GBFP8: about 821 GB of weights (estimate; KV cache and activations extra)FP8821 GBBF16: about 1.64 TB of weights (estimate; KV cache and activations extra)BF161.64 TB

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

How it scores

Third-party measurements only; author-reported numbers stay in Reference, marked as such.

#1 of 13 on Aider Polyglot so far

71.4. Each tick is a model on this site with a measured Aider Polyglot row; author-reported numbers stay in Reference. Percent (pass_rate_2). edit_format=diff

Qwen/Qwen3-235B-A22B: 59.6 · observed 2026-10-25 · https://aider.chat/docs/leaderboards/moonshotai/Kimi-K2-Instruct: 59.1 · observed 2026-10-25 · https://aider.chat/docs/leaderboards/deepseek-ai/DeepSeek-R1: 56.9 · observed 2026-10-25 · https://aider.chat/docs/leaderboards/deepseek-ai/DeepSeek-V3-0324: 55.1 · observed 2026-10-25 · https://aider.chat/docs/leaderboards/openai/gpt-oss-120b: 41.8 · observed 2026-10-25 · https://aider.chat/docs/leaderboards/Qwen/Qwen3-32B: 40 · observed 2026-10-25 · https://aider.chat/docs/leaderboards/Qwen/QwQ-32B: 26.2 · observed 2026-10-25 · https://aider.chat/docs/leaderboards/Qwen/QwQ-32B: 20.9 · observed 2026-10-25 · https://aider.chat/docs/leaderboards/Qwen/Qwen2.5-Coder-32B-Instruct: 16.4 · observed 2026-10-25 · https://aider.chat/docs/leaderboards/meta-llama/Llama-4-Maverick-17B-128E-Instruct: 15.6 · observed 2026-10-25 · https://aider.chat/docs/leaderboards/Qwen/Qwen2.5-Coder-32B-Instruct: 8 · observed 2026-10-25 · https://aider.chat/docs/leaderboards/google/gemma-3-27b-it: 4.9 · observed 2026-10-25 · https://aider.chat/docs/leaderboards/010071.4 · #1 of 13
Qwen/Qwen3-235B-A22B: 59.6 · observed 2026-10-25 · https://aider.chat/docs/leaderboards/moonshotai/Kimi-K2-Instruct: 59.1 · observed 2026-10-25 · https://aider.chat/docs/leaderboards/deepseek-ai/DeepSeek-R1: 56.9 · observed 2026-10-25 · https://aider.chat/docs/leaderboards/deepseek-ai/DeepSeek-V3-0324: 55.1 · observed 2026-10-25 · https://aider.chat/docs/leaderboards/openai/gpt-oss-120b: 41.8 · observed 2026-10-25 · https://aider.chat/docs/leaderboards/Qwen/Qwen3-32B: 40 · observed 2026-10-25 · https://aider.chat/docs/leaderboards/Qwen/QwQ-32B: 26.2 · observed 2026-10-25 · https://aider.chat/docs/leaderboards/Qwen/QwQ-32B: 20.9 · observed 2026-10-25 · https://aider.chat/docs/leaderboards/Qwen/Qwen2.5-Coder-32B-Instruct: 16.4 · observed 2026-10-25 · https://aider.chat/docs/leaderboards/meta-llama/Llama-4-Maverick-17B-128E-Instruct: 15.6 · observed 2026-10-25 · https://aider.chat/docs/leaderboards/Qwen/Qwen2.5-Coder-32B-Instruct: 8 · observed 2026-10-25 · https://aider.chat/docs/leaderboards/google/gemma-3-27b-it: 4.9 · observed 2026-10-25 · https://aider.chat/docs/leaderboards/010071.4 · #1 of 13

Source · leaderboard · 2025-06-06

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 (2025-05-28), amber triangles are 10 dated articles (each links to it), grey ticks are repo commits.

What people built on it

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

126 derivatives on the Hub, led by 59 fine-tunes

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

47 quantized (Hugging Face model tree)59 fine-tunes (Hugging Face model tree)4 merges (Hugging Face model tree)16 adapters (Hugging Face model tree)47 quantized59 fine-tunes4 merges16 adapters
47 quantized (Hugging Face model tree)59 fine-tunes (Hugging Face model tree)4 merges (Hugging Face model tree)16 adapters (Hugging Face model tree)47 quantized59 fine-tunes4 merges16 adapters

All variants →

Reference

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

Benchmarks

24 rows

Benchmarks 24 rows

measured third-party leaderboard row (2)author-reported number from the model card or eval files (22)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
measured Aider Polyglot · Write code with agents71.4 percent (pass_rate_2)edit_format=diffleaderboard2025-06-06
measured LiveCodeBench · Write code with agents84.36 percent pass@1 (mean over questions)all 1055 questions in file, 2023-05-08..2025-04-07leaderboard2025-04-07
author-reported AIME 2024 · Reason through hard problems91.4 pass@1DeepSeek R1 0528model author2026-10-07
author-reported AIME 2024 · Reason through hard problems86DeepSeek-R1-0528-Qwen3-8Bmodel author2026-10-07
author-reported AIME 2025 · Reason through hard problems87.5 pass@1DeepSeek R1 0528model author2026-10-07
author-reported AIME 2025 · Reason through hard problems76.3DeepSeek-R1-0528-Qwen3-8Bmodel author2026-10-07
author-reported Aider Polyglot · Write code with agents71.6DeepSeek R1 0528model author2026-10-07
author-reported BFCL · Call tools and APIs37DeepSeek R1 0528model author2026-10-07
author-reported CNMO 2024 (Pass@1)86.9 pass@1DeepSeek R1 0528model author2026-10-07
author-reported Codeforces · Write code with agents1930 ratingDeepSeek R1 0528model author2026-10-07
author-reported FRAMES (Acc.)83DeepSeek R1 0528model author2026-10-07
author-reported GPQA Diamond · Reason through hard problems81 pass@1DeepSeek R1 0528model author2026-10-07
author-reported GPQA Diamond · Reason through hard problems61.1DeepSeek-R1-0528-Qwen3-8Bmodel author2026-10-07
author-reported HMMT · Reason through hard problems79.4 pass@1DeepSeek R1 0528model author2026-10-07
author-reported HMMT · Reason through hard problems61.5DeepSeek-R1-0528-Qwen3-8Bmodel author2026-10-07
author-reported Humanity's Last Exam · Reason through hard problems17.7 pass@1DeepSeek R1 0528model author2026-10-07
author-reported LiveCodeBench · Write code with agents73.3 pass@1DeepSeek R1 0528model author2026-10-07
author-reported LiveCodeBench · Write code with agents60.5DeepSeek-R1-0528-Qwen3-8Bmodel author2026-10-07
author-reported MMLU · Reason through hard problems93.4DeepSeek R1 0528model author2026-10-07
author-reported MMLU-Pro · Reason through hard problems85DeepSeek R1 0528model author2026-10-07
author-reported SWE-bench Verified · Write code with agents57.6DeepSeek R1 0528model author2026-10-07
author-reported SimpleQA · Reason through hard problems27.8DeepSeek R1 0528model author2026-10-07
author-reported tau-bench · Call tools and APIs53.5 pass@1DeepSeek R1 0528 (Airline)model author2026-10-07
author-reported tau-bench · Call tools and APIs63.9 pass@1DeepSeek R1 0528 (Retail)model author2026-10-07

Use-case evidence

5 use cases

What it is good at 5 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

22 fields

Listed in LLMs · MoE

Facts

Pipeline tagtext-generation
Librarytransformers
ArchitecturesDeepseekV3ForCausalLM
Model typedeepseek_v3
Dtypebfloat16
Params by dtypeBF16: 3,918,786,560 · F32: 41,555,600 · F8_E4M3: 680,571,043,840
Size bandXXL
MoEyes
Experts256
Experts per token8
Context length163,840 (config.json max_position_embeddings)
PapersarXiv:2501.12948
LicenseMIT (mit)
Hub snapshot2026-10-25

Servability

vLLM · SGLang

Servability

vLLM: supported · DeepseekV3ForCausalLM · 7050ef881ff0835f6890a47db1859a24c65481d6SGLang: supported · DeepseekV3ForCausalLM · 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-R1-0528: params × bytes/param × 1.2 overhead. KV cache and activations are extra. How this is computed.

BF16 (2 bytes/param)1.64 TB · Cluster (≥640 GB)
FP8 (1 byte/param)821 GB · Cluster (≥640 GB)
INT4 (0.5 bytes/param)411 GB · Multi-GPU node (<640 GB)

Weights only (params × bytes/param × 1.2 overhead); KV cache and activations extra. MoE: all experts must be resident, so total parameters count.

All variants

40 variants

Lineage

Original release (shipped quantized by the lab) Family: deepseek-ai/DeepSeek-R1 126 derivatives on the Hub

finetune: 59quantized: 47merge: 4adapter: 16

Top variants (40 shown, ranked by downloads)

Relation
Quant
40 rows
Variant Relation Quant Params Band License Author Likes Downloads
nvidia/DeepSeek-R1-0528-NVFP4-v2 finetune NVFP4 394B XXL mit nvidia 27 5.4M
unsloth/DeepSeek-R1-0528-GGUF quantized GGUF — — mit unsloth 202 474.7k
nvidia/DeepSeek-R1-0528-NVFP4 finetune NVFP4 397B XXL mit nvidia 48 443.6k
amd/DeepSeek-R1-0528-MXFP4 quantized MXFP4 356B XXL mit amd 2 197.8k
amd/DeepSeek-R1-0528-MXFP4-v2 quantized MXFP4 350B XXL mit amd 0 149.8k
amd/DeepSeek-R1-0528-MXFP4-MTP-MoEFP4 quantized MXFP4 350B XXL mit amd 0 68.8k
bartowski/deepseek-ai_DeepSeek-R1-0528-GGUF quantized GGUF — — mit bartowski 11 58.2k
ubergarm/DeepSeek-R1-0528-GGUF quantized GGUF — — mit ubergarm 53 32.8k
tngtech/DeepSeek-TNG-R1T2-Chimera merge — 684B XXL mit tngtech 287 21k
QuixiAI/DeepSeek-R1-0528-AWQ quantized AWQ 671B XXL mit QuixiAI 19 28.5k
unsloth/DeepSeek-R1-0528-BF16 finetune -BF16 684B XXL mit unsloth 10 23.5k
RedHatAI/DeepSeek-R1-0528-quantized.w4a16 quantized -quant 676B XXL mit RedHatAI 13 14k
DevQuasar/deepseek-ai.DeepSeek-R1-0528-GGUF quantized GGUF — — — DevQuasar 7 10.5k
unsloth/DeepSeek-R1-0528 quantized — 685B XXL mit unsloth 15 9.5k
QuantTrio/DeepSeek-R1-0528-GPTQ-Int4-Int8Mix-Medium quantized GPTQ 912B XXL mit QuantTrio 1 7.3k
mlx-community/DeepSeek-R1-0528-3bit quantized — 671B XXL mit mlx-community 0 6.3k
lmstudio-community/DeepSeek-R1-0528-GGUF quantized GGUF — — mit lmstudio-community 9 5.2k
QuantTrio/DeepSeek-R1-0528-GPTQ-Int4-Int8Mix-Compact quantized GPTQ 847B XXL mit QuantTrio 5 5.4k
amd/DeepSeek-R1-0528-MXFP4-ASQ quantized MXFP4 342B XXL mit amd 1 5k
dyadya-sam/DeepSeek-R1-0528-GGUF-Q4_K_XL quantized GGUF — — mit dyadya-sam 0 3.4k
mlx-community/DeepSeek-R1-0528-5bit quantized — 671B XXL mit mlx-community 3 1.8k
adamo1139/DeepSeek-R1-0528-AWQ quantized AWQ 671B XXL mit adamo1139 4 1.6k
anikifoss/DeepSeek-R1-0528-DQ4_K_R4 quantized GGUF — — mit anikifoss 9 753
QuantTrio/DeepSeek-R1-0528-GPTQ-Int4-Int8Mix-Lite quantized GPTQ 721B XXL mit QuantTrio 2 963
moxin-org/DeepSeek-R1-0528-Moxin-GGUF quantized GGUF — — mit moxin-org 5 651
kaxap/mlx-DeepSeek-R1-0528-2bit quantized mlx 671B XXL mit kaxap 0 860
AmpereComputing/deepseek-r1-0528-gguf quantized gguf — — — AmpereComputing 0 790
kaxap/mlx-DeepSeek-R1-0528-4bit quantized mlx 671B XXL mit kaxap 0 748
bobchenyx/DeepSeek-R1-0528-HFK-GGUF quantized GGUF — — mit bobchenyx 0 721
NOYOUllm2/fortinet-lora-gguf quantized gguf — — mit NOYOUllm2 1 652
bullerwins/DeepSeek-R1-0528-GGUF quantized GGUF — — mit bullerwins 0 606
tachyphylaxis/DeepSeek-R1-0528-GGUF quantized GGUF — — mit tachyphylaxis 0 587
bobchenyx/DeepSeek-R1-0528-MLA-GGUF quantized GGUF — — mit bobchenyx 1 517
ArtusDev/deepseek-ai_DeepSeek-R1-0528-GGUF quantized GGUF — — mit ArtusDev 0 520
TVS759/DeepSeek-TNG-R1T2-Chimera merge — 684B XXL mit TVS759 0 439
mmbela/DeepSeek-R1-0528-optimized-for-512Gb-GGUF quantized GGUF — — mit mmbela 1 352
Jinx-org/Jinx-DeepSeek-R1-0528 finetune — 684B XXL apache-2.0 Jinx-org 6 73
amd/DeepSeek-R1-0528-ptpc quantized — 671B XXL mit amd 0 367
ling1000T/DeepSeek-R1-0528-gguf quantized gguf — — mit ling1000T 1 298
gghfez/DeepSeek-R1-0528-256x21B-BF16 finetune -BF16 — — mit gghfez 0 320

Repository changelog

13 commits

Repository changelog 13 commits

DateCommitSHA
2025-05-29 Release DeepSeek-R1-0528 4236a6a
2025-05-29 Update .gitattributes 54b97b8
2025-05-28 Add files using upload-large-folder tool 174da7f
2025-05-28 Add files using upload-large-folder tool f90ddc6
2025-05-28 Add files using upload-large-folder tool 8f1a7bc
2025-05-28 Add files using upload-large-folder tool 8504b97
2025-05-28 Add files using upload-large-folder tool d9d887f
2025-05-28 Add files using upload-large-folder tool 894d8c6
2025-05-28 Add files using upload-large-folder tool ecba5ba
2025-05-28 Add files using upload-large-folder tool 4823201
2025-05-28 Add files using upload-large-folder tool 2fb3b9e
2025-05-28 Add files using upload-large-folder tool 1162836
2025-05-28 initial commit f3602d5

All providers

5 providers · 5 endpoints

Where to run 5 providers · 5 endpoints

Hosted endpoints observed for DeepSeek-R1-0528, sorted by input price (USD per million tokens). Each row names its observer and date; prices change daily, so check the source before quoting. Cheapest observed input price: $0.50/M.

ProviderModel refContextQuant$/M in$/M outtok/sTTFTToolsStatusObserved
DeepInfra
hf, deepinfra, openrouter
deepseek-ai/DeepSeek-R1-0528 160K fp4 $0.50 $2.15 23.1 726 ms yes live 2026-10-25
SiliconFlow
openrouter
deepseek/deepseek-r1-0528 160K fp8 $0.50 $2.18 — — yes live 2026-10-24
StreamLake
openrouter
deepseek/deepseek-r1-0528 125K unknown $0.57 $2.29 — — — live 2026-10-24
Novita
hf
deepseek/deepseek-r1-0528 160K — $0.70 $2.50 25.8 914 ms yes live 2026-10-25
Featherless
hf
deepseek-ai/DeepSeek-R1-0528 — — — — — — — live 2026-10-25

Articles and coverage

41 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 (41) — append-only, nothing is ever removed
TitleSourcePublishedFirst seenSignals
DeepSeek R1 0528 — Architecture, Evals & Inference Performance | InferenceXinferencex.semianalysis.com—2026-10-07exa
DeepSeek R1 0528 - Intelligence, Performance & Price ...artificialanalysis.ai—2026-10-07exa
DeepSeek | DeepSeek R1 0528 | Kagglekaggle.com—2026-10-07exa
DeepSeek R1 0528 Deep Diverunpod.io—2026-10-07exa
DeepSeek: R1 0528 - AI Model Details & Benchmarksbenchable.ai—2026-10-07exa
ZAYA1-8B matches DeepSeek-R1 on math with less than 1B active parametersfirethering.com2026-05-072026-10-07hn
A new, faster DeepSeek R1-0528 variant appears from German labventurebeat.com2025-07-052026-10-07hn
DeepSeek R1 0528 scored 71% on the aider polyglot coding benchmark (3rd)twitter.com2025-06-092026-10-07hn
DeepSeek-R1-0528 Did Not Have a Momentthezvi.substack.com2025-06-062026-10-07hn
The 'Minor Upgrade' That's Anything But: DeepSeek R1-0528 Deep Diverunpod.ghost.io2025-05-312026-10-07exa
DeepSeek-R1-0528: A Detailed Review of its AI Coding Performance & Latency | ForgeCodeforgecode.dev2025-05-302026-10-07exa
DeepSeek-R1-0528 Releasedapi-docs.deepseek.com official2025-05-292026-10-07hn
DeepSeek-R1-0528 is heretwitter.com2025-05-292026-10-07hn
Deepseek-R1-0528 Dynamic 1-bitunsloth.ai2025-05-292026-10-07hn
DeepSeek-R1-0528 is now live on Hyperbolicapp.hyperbolic.xyz2025-05-282026-10-07hn
DeepSeek R1-0528: The Update That Quietly Closed the Gap With o3 — Redeepredeep.blog2025-05-282026-10-07exa
DeepSeek R1 (0528) Review — Benchmarks, Pricing & AI Panel Verdict | TopReviewed.aitopreviewed.ai2025-05-272026-10-07exa
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
Official DeepSeek R1 Now on Ollamaollama.com2025-01-202026-10-07hn
DeepSeek-R1github.com2025-01-202026-10-07hn

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

4 sources

Sources

Hub snapshot: 2026-10-25 · HF API: 2026-10-24 21:32 UTC · Providers: 2026-10-24 21:44 UTC · Articles: 2026-10-24 21:45 UTC · Summary: 2026-10-07 14:59 UTC · Last verified 2026-10-25

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