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NVIDIA: Nemotron 3.5 Lightning (free)

NVIDIA Nemotron 3.5 Lightning is an open mixture-of-experts model from NVIDIA, with 3B active parameters out of 30B total. It is suited for high-throughput agentic workloads and specialized tasks that...

Voir la source sur OpenRouter Hugging Face
Présentation

Caractéristiques du modèle

Context
1 000 000 tokens
Sortie maximale
65 536 tokens
Architecture
text->text
Tokenizer
Other
Limite des connaissances
Not provided
Modéré
Non
Capacités et modalités

Input → Output

Input
text
Output
text
Raisonnement

Non

API

Paramètres API pris en charge

include_reasoningmax_tokensreasoningseedtemperaturetool_choicetoolstop_p
Fournisseurs disponibles

2 fournisseurs

DeepInfra

bf16
Context
262K
Sortie maximale
131K
Input
$0.080
Output
$0.200
Lecture du cache
$0.040
Écriture du cache
Not provided

CoreWeave

bf16
Context
262K
Sortie maximale
236K
Input
$0.100
Output
$0.250
Lecture du cache
$0.050
Écriture du cache
Not provided
nvidia

models

Tous les modèles
Nnvidia

NVIDIA: Nemotron 3.5 ASR Streaming Multilingual 0.6B

Nemotron 3.5 ASR Streaming Multilingual 0.6B is a speech recognition model from NVIDIA. Its prompt-conditioned, cache-aware FastConformer-RNNT design targets low-latency transcription across more than 40 languages for real-time captioning, voice...

Context
Not provided
Input
audio
Output
transcription
Input: $3.33Output: Freeper 1M tokens
Voir la fiche du modèle →
Nnvidia

NVIDIA: Nemotron 3.5 Lightning

NVIDIA Nemotron 3.5 Lightning is an open mixture-of-experts model from NVIDIA, with 3B active parameters out of 30B total. It is suited for high-throughput agentic workloads and specialized tasks that...

Context
262K
Input
text
Output
text
Input: $0.080Output: $0.200per 1M tokens
Voir la fiche du modèle →
Nnvidia

NVIDIA: Nemotron 3 Embed 1B (free)

NVIDIA Nemotron 3 Embed 1B is an open text embedding model from NVIDIA, optimized for high-throughput, low-latency retrieval. It is suited for enterprise search, RAG, code retrieval, and agentic retrieval...

Context
33K
Input
text
Output
embeddings
Input: FreeOutput: Freeper 1M tokens
Voir la fiche du modèle →