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NVIDIA: Nemotron 3 Super
nvidia/nemotron-3-super-120b-a12btextReasoning
NVIDIA open 120B model activating just 12B parameters (hybrid Mamba-Transformer MoE) — high compute efficiency and accuracy in complex multi-agent applications. Adjustable reasoning depth, 1M context.
Price in / out
Cache, read / write
Context / Max output
262K / 236K
Released
Mar 11, 2026
Parameters
messagesrequiredreasoning_effortoff · low · mediummax_tokensoptional · alias max_completion_tokensstreamtrue · falsetoolsfunction calling (OpenAI format)tool_choiceauto · none · requiredresponse_formatjson_object · json_schemaweb_search · · · providerrouting: order · only · ignore · sortstream_options{"include_usage": true}Fine-tuning · 11
temperature0–2stopoptionalseedoptionaltop_p0–1top_koptionalmin_p0–1frequency_penalty−2…2presence_penalty−2…2repetition_penalty0–2logprobstrue · falsetop_logprobs0–20How to use via API
from openai import OpenAI
client = OpenAI(base_url="https://api.mixen.ai/v1", api_key="mxn-...")
resp = client.chat.completions.create(
model="nvidia/nemotron-3-super-120b-a12b",
messages=[{"role": "user", "content": "Привет"}],
reasoning_effort="low", # off · low · medium
temperature=0.7,
max_tokens=1024,
stream=False,
)
print(resp.choices[0].message.content)
# Стриминг: stream=True — ответ приходит чанками
for chunk in client.chat.completions.create(
model="nvidia/nemotron-3-super-120b-a12b",
messages=[{"role": "user", "content": "Привет"}],
stream=True,
):
print(chunk.choices[0].delta.content or "", end="", flush=True)
