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Llama 3.1 Nemotron Ultra 253B

Up to 30%

Call Llama 3.1 Nemotron Ultra 253B through LLM.API when you want Meta-family text generation with unified auth, provider choice, and production-friendly defaults.

Start Using API

What is Llama 3.1 Nemotron Ultra 253B?

On LLM.API, Llama 3.1 Nemotron Ultra 253B (llama-3.1-nemotron-ultra-253b) serves as a Meta conversational model for products that need 128K tokens context windows and predictable token pricing. llama-3.1-nemotron-ultra-253b provided by nebius. It is wired for API access through LLM.API with OpenAI-compatible patterns.

Providers

LLM.API routes Llama 3.1 Nemotron Ultra 253B to the providers below, with discounted effective rates versus list price.

List price by provider ($ / 1M tokens)

InputOutput
nebius$0.6 in
$1.8 out

Provider list prices; the LLM.API discount applies on top.

ProviderPricingContextCapabilities
nebius30% offin $600; out $1800 per 1M tokens128K tokenstools, streaming, JSON, structured

Prices and availability from the LLMAPI catalogue, updated nightly. Last updated 21 Sept 2026.

Try this model

Test Llama 3.1 Nemotron Ultra 253B right here — free to start.

Llama 3.1 Nemotron Ultra 253B
Hi! Want to test the model?

Suggestions for your first prompt

Code snippet

Call Llama 3.1 Nemotron Ultra 253B through the OpenAI-compatible API — POST /v1/chat/completions.

python
from openai import OpenAI

client = OpenAI(
    api_key="YOUR_LLMAP_KEY",
    base_url="https://api.llmapi.ai/v1",
)

resp = client.chat.completions.create(
    model="llama-3.1-nemotron-ultra-253b",
    messages=[
        {"role": "system", "content": "You are a precise product assistant."},
        {"role": "user", "content": "Give me three crisp launch checklist items."},
    ],
)
print(resp.choices[0].message.content)
{
  "model": "llama-3.1-nemotron-ultra-253b",
  "messages": [
    {"role": "system", "content": "You are a precise product assistant."},
    {"role": "user", "content": "Give me three crisp launch checklist items."}
  ]
}

5 Core Capabilities

  • Tool-ready dialogue

    Works well in agent loops that call functions, browsers, or retrieval APIs. Grounded in the model's chat role rather than generic chat claims.

  • Conversational UX

    Maintains coherent multi-turn assistant behavior for product chat surfaces. Tuned to how teams typically call Llama 3.1 Nemotron Ultra 253B.

  • Instruction following

    Follows detailed system and user instructions with strong adherence to format and tone. Relevant for `llama-3.1-nemotron-ultra-253b` workloads on LLM.API.

  • Code assistance

    Helps write, explain, refactor, and debug application code across common languages. Grounded in the model's chat role rather than generic chat claims.

  • Multi-step reasoning

    Breaks down complex problems into intermediate steps before answering. Reflects Meta positioning for this endpoint.

6 Most Valuable Use Cases

  • Policy Q&A bots with careful refusal behavior with Llama 3.1 Nemotron Ultra 253B
  • Data extraction into JSON for downstream systems
  • Sales and success email drafting with CRM context with Llama 3.1 Nemotron Ultra 253B
  • Customer support copilots that draft accurate, on-brand replies
  • Multilingual localization drafts for UX copy with Llama 3.1 Nemotron Ultra 253B
  • Research synthesis across long documents and tickets

Why Build on LLM.API?

One unified API. Every major model. Built-in reliability, cost control, and observability.

  • Intelligent AI Routing

    Automatically route each request to the best model across providers based on latency, cost, and quality—without changing your integration or redeploying code.

    One endpoint, every model.

  • Cost-Aware Execution

    Control spend with per-request cost estimation, smart model selection, and centralized quotas so teams can experiment fast without runaway bills or manual tracking.

    More performance, less spend.

  • Resilient Fallback Flows

    Define automatic, provider-agnostic fallbacks to keep your app up during outages, rate limits, or timeouts—no brittle failover logic scattered through your codebase.

    Never go dark on users.

  • Deep LLM Observability

    Trace every call across providers with logs, metrics, and request replay so you can debug, tune prompts, and optimize model choices from one unified dashboard.

    See every token, everywhere.

  • Task-Level Orchestration

    Describe tasks, not models. LLM.API maps them to the right tools, models, and prompts so you ship complex AI workflows with minimal glue code.

    Think tasks, not models.

  • High-Throughput Batch APIs

    Process millions of inferences efficiently with optimized batch pipelines, concurrency controls, and retry logic—all behind the same simple interface you use for single calls.

    Scale from 1 to millions.

Why run Llama 3.1 Nemotron Ultra 253B on LLM.API?

  • Unified AI Routing

    Practical: Reach Llama 3.1 Nemotron Ultra 253B and sibling models through one OpenAI-compatible endpoint.

  • Cost Control

    Compare provider price points and keep spend visible as you scale Llama 3.1 Nemotron Ultra 253B.

  • Reliability Layer

    Production: Retry and route across configured providers when a single upstream blips.

  • Observability

    Production: Trace prompts, tokens, and errors for Llama 3.1 Nemotron Ultra 253B alongside the rest of your stack.

  • Drop-in SDKs

    Production: Keep using familiar OpenAI client patterns with base URL https://api.llmapi.ai/v1.

  • Model Breadth

    Practical: Swap Llama 3.1 Nemotron Ultra 253B for chat, media, or embedding alternatives without rewriting auth.

When to Use — When NOT to Use

Use it if...

  • You want OpenAI-compatible chat completions through a single LLM.API key (Llama 3.1 Nemotron Ultra 253B)
  • Your prompts benefit from the model's family strengths (reasoning, speed, or cost) (Llama 3.1 Nemotron Ultra 253B)
  • You need a general-purpose text model for assistants, agents, or content workflows (Llama 3.1 Nemotron Ultra 253B)
  • You need provider failover options exposed for this model id (Llama 3.1 Nemotron Ultra 253B)

Avoid if...

  • You need guaranteed real-time hard latency SLAs without benchmarking the provider
  • You require on-prem only deployment with no cloud inference
  • You need pure embedding, OCR, or media generation instead of chat
  • Your use case depends on unpublished proprietary benchmarks not listed here

COMMUNITY

What developers say about Llama models

Summarised from publicly published developer and community reviews of this model family. Opinions are the sources’, not LLM.API’s, and may not be specific to Llama 3.1 Nemotron Ultra 253B.

  • Independent testers were underwhelmed by Llama 4 coding performance relative to the launch messaging around its very long context window.
  • The architecture shift to mixture-of-experts and native multimodality is seen as the real story for teams self-hosting open weights.
  • Most reviewers position Llama as an integration and deployment choice rather than a benchmark leader.

SOURCES

Frequently Asked Questions

  • Is Llama 3.1 Nemotron Ultra 253B a chat model?

    Yes—Llama 3.1 Nemotron Ultra 253B is exposed as a chat/completions-style endpoint on LLM.API.

  • How is Llama 3.1 Nemotron Ultra 253B priced on LLM.API?

    Listed pricing metadata shows: In $0.6 / 1M tokens · Out $1.8 / 1M tokens. LLM.API may offer discounted effective rates (illustrative ~30% callout vs list when available).. Confirm live rates in the LLM.API dashboard or docs before production budgeting.

  • How do I call Llama 3.1 Nemotron Ultra 253B via API?

    Send OpenAI-compatible requests to https://api.llmapi.ai/v1 with model "llama-3.1-nemotron-ultra-253b" and your LLM.API key. See the code snippet on this page.

  • What modalities does Llama 3.1 Nemotron Ultra 253B support?

    Llama 3.1 Nemotron Ultra 253B accepts text and produces text according to its architecture metadata on LLM.API.

  • What are limitations of Llama 3.1 Nemotron Ultra 253B?

    Like other API models, Llama 3.1 Nemotron Ultra 253B can be wrong, incomplete, or uneven on edge cases. Validate outputs for high-stakes use. Media/OCR/STT models additionally depend on input quality.

  • Where is the canonical page for Llama 3.1 Nemotron Ultra 253B?

    https://llmapi.ai/models/meta-llama-llama-3-1-nemotron-ultra-253b/

  • What is Llama 3.1 Nemotron Ultra 253B?

    llama-3.1-nemotron-ultra-253b provided by nebius. It is wired for API access through LLM.API with OpenAI-compatible patterns. On LLM.API it is addressed as `llama-3.1-nemotron-ultra-253b`.

  • When should I choose Llama 3.1 Nemotron Ultra 253B?

    You need a general-purpose text model for assistants, agents, or content workflows — especially when you specifically need Llama 3.1 Nemotron Ultra 253B.

  • Can I use tools or structured outputs with Llama 3.1 Nemotron Ultra 253B?

    Tool and/or structured-output flags appear on one or more providers for this model—confirm in the providers table.

  • Does Llama 3.1 Nemotron Ultra 253B support streaming?

    Yes—at least one listed provider advertises streaming.

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