NVIDIA: Llama 3.3 Nemotron Super 49B V1.5

Public pricingIntelligence 78/100Medium memory深度思考工具调用

NVIDIA: Llama 3.3 Nemotron Super 49B V1.5 是一款文本模型，适合编码、软件工程和智能体工作流。它结合了强大的编码能力、可靠的工具调用与智能体表现、131K tokens上下文和低成本定位，可在编码、软件工程和智能体工作流中提供可靠表现。它适合重视准确性、上下文与控制的团队，能带来稳定输出、灵活部署与扩展空间。 它适合需要稳定回答、较长上下文、清晰结构和可扩展部署的团队。 它适合需要稳定回答、较长上下文、清晰结构和可扩展部署的团队。 它适合需要稳定回答、较长上下文、清晰结构和可扩展部署的团队。 它适合需要稳定回答、较长上下文、清晰结构和可扩展部署的团队。 它适合需要稳定回答、较长上下文、清晰结构和可扩展部署的团队。 它适合需要稳定回答、较长上下文、清晰结构和可扩展部署的团队。

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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