NVIDIA: Llama 3.3 Nemotron Super 49B V1.5

Public pricingIntelligence 78/100Medium memory심층 추론도구 활용

NVIDIA: Llama 3.3 Nemotron Super 49B V1.5은 코딩, 소프트웨어 엔지니어링, 에이전트 워크플로에 맞춘 텍스트 모델입니다. 강력한 코딩 성능、안정적인 도구 사용과 에이전트 동작, 131K tokens의 컨텍스트, 저비용 특성을 결합해 코딩, 소프트웨어 엔지니어링, 에이전트 워크플로에서 안정적인 작업을 돕습니다. 특히 정확도, 문맥, 제어가 중요한 경우에 잘 맞으며, 안정적인 출력, 유연한 배포, 확장성을 중시하는 팀에 실용적입니다. 안정적인 응답, 넓은 문맥 처리, 그리고 시제품부터 운영까지 이어지는 유연성이 필요할 때 유용합니다. 안정적인 응답, 넓은 문맥 처리, 그리고 시제품부터 운영까지 이어지는 유연성이 필요할 때 유용합니다.

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.

  • gpqa_diamond

    72

  • math

    97.4

  • aime_2024

    87.5

  • aime_2025

    82.7

  • livecodebench

    73.6

  • aa_intelligence_index

    14

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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