NVIDIA: Llama 3.3 Nemotron Super 49B V1.5

Public pricingIntelligence 78/100Medium memoryRazonamiento profundoUso de herramientas

NVIDIA: Llama 3.3 Nemotron Super 49B V1.5 es un modelo texto pensado para programación, ingeniería de software y flujos agénticos. Combina buen rendimiento en programación y uso fiable de herramientas y comportamiento agéntico, un contexto de 131K tokens y un perfil bajo costo para trabajar con fiabilidad en programación, ingeniería de software y flujos agénticos.

Input

$0.10/1M

Output

$0.40/1M

Cached

$0.01/1M

Batch

$0.05/1M

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Technical specifications

Llama 3.3 Nemotron Super 49B V1.5 at a glance.

Memory

131,072

tokens

Max reply

128,000

tokens

Memory tier

Medium

a long report or a codebase file

Tokenizer

llama3

Released

Jul 2025

Training cutoff

Dec 2024

Availability

Public pricing

Status

active

Benchmarks

Quality benchmarks

Independent evaluations from public leaderboards. Higher is better.

  • aa_intelligence_index

    14

  • aime_2024

    87.5

  • aime_2025

    82.7

  • gpqa_diamond

    72

  • livecodebench

    73.6

  • math

    97.4

What it can do

Capabilities & limits.

  • Understands images
  • Deep step-by-step thinking
  • Uses tools / calls functions
  • Strict JSON output
  • Streams replies
  • Fine-tunable on your data

When to pick Llama 3.3 Nemotron Super 49B V1.5

  • Multi-step reasoning, research agents, or hard math.
  • Agentic workflows that call tools or APIs.
  • High-volume workloads where unit cost matters.

When to look elsewhere

  • Your workload involves images — pick a vision-capable model instead.

Alternatives

Similar models to compare.

FAQ

Llama 3.3 Nemotron Super 49B V1.5 — the questions we see most.

Pricing, capabilities, alternatives — generated from the same data that powers the calculator above.

Get instant answers from our AI agent

At a typical workload of 50,000 conversations a month with 1,500-token prompts and 800-token replies, Llama 3.3 Nemotron Super 49B V1.5 costs roughly $24 per month. Input is $0.10 /1M tokens and output is $0.40 /1M tokens.
Llama 3.3 Nemotron Super 49B V1.5 has a 131,072-token context window (medium memory — a long report or a codebase file). That means you can fit about 24,576 words of input and history in a single call.
Beyond text generation, Llama 3.3 Nemotron Super 49B V1.5 supports deep step-by-step reasoning, calling functions / tools, strict JSON output, fine-tuning on your own data. It streams replies by default.
Llama 3.3 Nemotron Super 49B V1.5 was released in July 2025, with training data cut off around December 2024.
Models in a similar class include Nemotron 3 Super, Nemotron 3 Nano 30B A3B, Nemotron Nano 9B V2. The "Similar models" section below this FAQ links into each.

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