DeepSeek R1 0528 deepseek-r1-0528

deepseek-ai · deepseek reasoning flagship

unranked — no quality signals yet

params
671B (A37B)
arch
moe
context
160k
license
mit open weights
released
May 2025
reasoning
yes
train compute
4.0e+24 FLOP
downloads/30d
213.5k

# architecture

attn shared · reasoning MHA ×128 router top-8 of 256 +1 shared expert ×256 expert out ×61 layers ctx 163,840 671B pool · A37B/token
layers
61
d_model
7168
heads
128q / 128kv
head dim
56
experts
top-8 of 256 + 1 shared
vocab
129280
family
deepseek_v3

signal path of one layer, generated from the registry's structured fields — dimension lines quote the model's real numbers; an MoE trace forks at the router, a dense trace runs straight through. Geometry fields come from the repo's config.json.

# why ranked

Overall: provisional — score 51.0 ● low — a single signal; treat with caution

provisional: too few independent signals for a numbered position — the score is shown, but this model sorts after every ranked model.

signalweightinput (0–100)
aa_intelligence 0.70
bench_composite 0.30 51.0

benchmark panel evidence:

complete panelscore (0–100)
aider-polyglot-v158.4
aime-2025-v166.2
browsecomp-v128.4

missing signals are dropped and the remaining weights renormalized — never imputed.

Coding: provisional — score 90.9 ● low — a single signal; treat with caution

provisional: too few independent signals for a numbered position — the score is shown, but this model sorts after every ranked model.

signalweightinput (0–100)
aa_coding 0.30
aider_polyglot 0.30 90.9
swe_bench_verified 0.40

missing signals are dropped and the remaining weights renormalized — never imputed.

full methodology

# trend

OGM score · last 55 days
OGM score over 55 days

methodology changed during this history window; score movement across that boundary is not model movement. See methodology v5.

# benchmarks

benchmarkscoresourcedate
Aider Polyglot 71.4 Aider Jun 2025
Aider-polyglot 0.7 / 1 LLM Stats
AIME 2024 0.9 / 1 LLM Stats
AIME 2025 0.9 / 1 LLM Stats
Browsecomp 0.1 / 1 LLM Stats
Browsecomp-zh 0.4 / 1 LLM Stats
Codeforces 0.6 / 3000 LLM Stats

# where to run

providerquantctx$/M in$/M out$/M cacheprice srctpsuptime
Featherless via hfrouter
Lambda 128k $0.20$0.60 via litellm
DeepInfrafp4 160k $0.50$2.15 deepinfra 99.9%
SiliconFlowfp8 160k $0.50$2.18 via openrouter 99.6%
StreamLakeunknown 125k $0.57$2.29 via openrouter 99.9%
Novitafp8 160k $0.70$2.50 novita 99.7%
Nebius 164k $0.80$2.40 via litellm
Hyperbolic 160k $3.00$3.00 hyperbolic
Crusoe 160k $3.00$7.00 via litellm

sorted by blended price ((3·input + output) / 4 per 1M) · ✓ = the provider's own catalog confirms the offer · "via …" prices are what the aggregator routing the offer charges, not the provider's own list price

source aliases
aa
deepseek-r1-0528
aider
DeepSeek R1 (0528)
arena
DeepSeek-R1-0528
epoch
DeepSeek-R1 (May 2025)
openrouter
deepseek/deepseek-r1-0528