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nemotron-3.5-lightning-30b-a3bNVIDIA

from /1M infreenvidia
context1.0M66K out
best ttft1.37snvidia
endpoints11 region
endpoints
1
regions
1
best tok/s
57
api
chat
released
August 2026

capabilities 2/8

visionreasoningtoolscachingweb searchjson schemacomputer useimage gen

endpoints

1 / 1 region
Providers serving nemotron-3.5-lightning-30b-a3b, with pricing and measured performance. Best value in each column is coloured.
#flags
1NVIDIAGlobal1.0Mfreefreefree1.37s57.0-
provider price, no markupper 1M tokensblank where no qualifying sample

measured

through Nov 2
median
1.16s4.69s8.22s08-3109-2811-021.88s
hover the plot for weekly values
time to first token per provider: current value, window low and high, and change across the window
providernowlowhighchange
NVIDIA1.37s1.75s7.63s-65%

median wait before the first token lands. this is the number a user feels, and it moves with provider load through the day.

Lines are steps: each sample is one week of traffic held flat, not a slide from the week before. Click a name in the key to drop it from the plot. Measured through Nov 2.

benchmarks

artificial analysis

no published benchmark scores for this model

call it

model=
nemotron-3.5-lightning-30b-a3b

requesty routes this id across every provider serving nemotron-3.5-lightning-30b-a3b, picking on price and health and failing over automatically. the id stays valid when a provider changes underneath it

Base url is https://router.requesty.ai/v1 for every id here. One key reaches the whole catalog.

quickstart

openai compatible
main.py
from openai import OpenAI client = OpenAI(    api_key="YOUR_REQUESTY_API_KEY",    base_url="https://router.requesty.ai/v1",) response = client.chat.completions.create(    model="nemotron-3.5-lightning-30b-a3b",    messages=[        {"role": "user", "content": "Explain quantum computing in one paragraph."},    ],) print(response.choices[0].message.content)

Change the base url, use your Requesty key, set the model to any id in the call pane. Existing OpenAI SDK code needs no other edit, and the same key reaches every other model in the catalog, so switching later is a one-parameter change. Browse all models

notes

reference

NVIDIA Nemotron 3.5 Lightning 30B-A3B is a hybrid Mamba-2 + MoE + Attention model with 30B total and 3B active parameters, pre-trained on over 20T tokens with an NVFP4 recipe and Multi-Token Prediction for fast generation. Up to 1M token context for long-running autonomous agents, sub-agent workhorse deployments, and agentic workflows. Supports reasoning and tool calling. English and coding languages plus Spanish, French, German, Italian, and Japanese. Open weights under the OpenMDW License Agreement v1.1. Part of the NVIDIA Nemotron family.

questions 6

Which providers serve nemotron-3.5-lightning-30b-a3b?
nemotron-3.5-lightning-30b-a3b is available from 1 provider through Requesty: NVIDIA. All endpoints share one OpenAI-compatible API and one key, and Requesty fails over between them automatically.
How much does nemotron-3.5-lightning-30b-a3b cost?
Pricing starts at free per million input tokens and free per million output tokens on the cheapest provider. Prices vary by provider and region; the table above shows every endpoint. Requesty charges exactly what the upstream provider charges, with no markup.
Is nemotron-3.5-lightning-30b-a3b open weights?
Yes. nemotron-3.5-lightning-30b-a3b is an open-weights model from NVIDIA, which is why multiple inference providers can host it. Provider choice affects price, latency, and data-privacy terms, all compared above.
What is the context window of nemotron-3.5-lightning-30b-a3b?
nemotron-3.5-lightning-30b-a3b supports up to 1.0M tokens of context, with up to 66K output tokens per response. Some providers expose a smaller window; check the per-endpoint context column above.
How do I use nemotron-3.5-lightning-30b-a3b with the OpenAI SDK?
Install the OpenAI SDK, set base_url to "https://router.requesty.ai/v1", set your API key to your Requesty key, and set the model to "nemotron-3.5-lightning-30b-a3b" or any endpoint id from the table above. The quickstart section shows Python, JavaScript and cURL snippets.
Should I call nemotron-3.5-lightning-30b-a3b by its managed id or a provider id?
Use the managed id, "nemotron-3.5-lightning-30b-a3b". Requesty picks which of the 1 provider serves each request based on price and health, and fails over when one degrades, so the id keeps working while the routing changes underneath it. Send a provider id like "nvidia/nemotron-3.5-lightning-30b-a3b" only when you need one specific deployment and want no failover.

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route nemotron-3.5-lightning-30b-a3b through one endpoint

One key for 1 provider on this model and 600+ others. No markup on provider prices, automatic failover, caching built in. Weekly aggregates in the measured pane come from production traffic routed through Requesty, one line per provider on a shared axis. Methodology

nemotron-3.5-lightning-30b-a3b1 provider1 endpointsfrom free /1M inctx 1.0Mttft 1.37supdated Nov 2