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Llama 3.1 Nemotron Ultra 253B API: Endpoint & 30% Discount

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.

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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.

Can you self-host Llama 3.1 Nemotron Ultra 253B?

No. We found no public weights for Llama 3.1 Nemotron Ultra 253B on Hugging Face, so there is nothing to download, quantize or serve on your own GPUs: no VRAM budget, no vLLM or GGUF build to plan for. The only way to run it is over an API.

Not on LLM.API yet

We do not route this model through our API at the moment. Browse the models you can call today — most workloads have a close match already live.

Browse available models

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

InputOutput
nebius$0.6 in
$1.8 out

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

ProviderPricingContextCapabilities
nebius30% offin $0.6; out $1.8 per 1M tokens128K tokenstools, streaming, JSON, structured

Prices and availability from the LLMAPI catalogue, updated nightly. Last updated 27 Sept 2026.

Try this model

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

Llama 3.1 Nemotron Ultra 253B
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Not available on LLM API yet

We do not route this model through our API at the moment, so there is no endpoint or code snippet for it yet. Browse the models you can call today — most workloads have a close match already live.

Browse available models

Llama 3.1 Nemotron Ultra 253B in production

What the model is good at.

  • 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.

What you get when you call Llama 3.1 Nemotron Ultra 253B through LLM.API.

  • Unified AI Routing

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

    One endpoint, every model.

  • Cost Control

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

    More performance, less spend.

  • Reliability Layer

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

    Never go dark on users.

  • Observability

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

    See every token, everywhere.

  • Drop-in SDKs

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

    Think tasks, not models.

  • Model Breadth

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

    Scale from 1 to millions.

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

LLM API rating for Llama 3.1 Nemotron Ultra 253B

★ 3.2/ 5.0LLM API rating
50% production adoption · 30% category benchmark · 20% tooling & valueEstimated from published specs
3.5Production adoptionActive open-weight community usage
2.8Benchmark qualityNo public Arena rank — scored on declared reasoning support
3.1Developer ecosystemContext window, tool and JSON support, price against the category median
Reasoning & chat 3.2Coding 3.7Tool & function calling 3.7
How is this rating calculated?

Every model gets a separate 1.0–5.0 score for each category it can be used in, so a model can rate high for coding and lower for vision. The score combines three parts:

  1. Production adoption — 50%. How widely the model is actually used in production: provider traffic, LiteLLM and gateway usage, open-weight downloads and its LMArena rank. Proven, widely used models score highest.
  2. Category benchmark — 30%. The public benchmark that matters for that category — the Artificial Analysis Intelligence Index and LMArena Elo for reasoning, LMArena coding Elo for coding, image and document support plus vision Elo for vision, tool and JSON support for function calling, measured speed for voice.
  3. Tooling & value — 20%. Context window, support for tools, structured outputs and streaming, and price compared with the category median.

Scores of 4.0 and above are shown in green, 3.0–3.9 in yellow, below 3.0 in red. When a model has no public data for a part, it gets a neutral value instead of an invented number.

A “Verified benchmark” mark (✓) means an independent lab — LMArena or Artificial Analysis — has actually tested that model, and the source figure is shown. Models without that mark are labelled “Estimated from published specs”: the score comes from the published context window, tool and schema support, price and adoption only, because no independent lab has tested them yet.

One exception: a brand-new top-tier model that scores very high on the independent benchmarks but has no usage history yet is rated on the benchmark (60%) and tooling & value (40%) alone, so a missing adoption figure can't hold it back. All inputs come from public sources and are refreshed weekly.

Adoption and benchmark inputs come from public sources — LMArena, Artificial Analysis Intelligence Index and published model specs. Updated weekly.

COMMUNITY

What developers say about Llama models

LMArena—Speed—Sources: LMArena, Artificial Analysis

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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