Nvidia Nemotron Nano 9B V2 nvidia-nemotron-nano-9b-v2

nvidia · nvidia

#93 overall

params
8.9B
arch
dense
license
other open weights

# architecture

attn shared GQA 40q/8kv feed-forward (dense) every parameter, every token out ×56 layers 8.9B — no routing
layers
56
d_model
4480
heads
40q / 8kv
head dim
128
vocab
131072
family
nemotron_h

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: #93 — score 16.2 ● high — all signals present

signalweightinput (0–100)
aa_intelligence 0.70 11.4
bench_composite 0.30 27.6

benchmark panel evidence:

complete panelscore (0–100)
aa-math-v131.1
aime-2025-v124.0

full methodology

# trend

OGM score · last 97 days
OGM score over 97 days
overall rank (up is better)
Overall rank over 97 days

methodology changed during this history window; score movement across that boundary is not model movement. See methodology v6.

# benchmarks

benchmarkscoresourcedate
AA Intelligence Index 7.4 Artificial Analysis —
AA Math Index 69.7 Artificial Analysis —
AIME 2025 0.7 / 1 LLM Stats —
Bfcl-v3-multiturn 0.7 / 1 LLM Stats —
Math-500 1.0 / 1 LLM Stats —

# where to run

providerquantctx$/M in$/M out$/M cacheprice srctpsuptime✓
DeepInfra 128k $0.04$0.16— via litellm — —
Together 128k $0.06$0.25— via litellm — —
Amazon Bedrock 125k $0.07$0.28— 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
nvidia-nemotron-nano-9b-v2
llmstats
nvidia-nemotron-nano-9b-v2