AIモデルインテリジェンス

Llama-3.1-Nemotron-Ultra-253B-v1

nebius/llama-3-1-nemotron-ultra-253b-v1

提供： nebius · リリース 2025-01-15 · 知識カットオフ: 2024-12

⚠ これはコミュニティのファインチューン / 派生モデルで、ベンダーの公式リリースではありません。

$0.600
入力 / 100万トークン
$1.80
出力 / 100万トークン
128K
コンテキスト長
4K
最大出力

Prices in USD per 1M tokens. Unknown means the provider does not publish per-token pricing.

機能一覧

✓ ツール呼び出し✗ 推論✓ 構造化出力✗ 添付✓ オープンウェイト✓ 温度制御
モダリティ: 入力 text · 出力 text

Model fit scores

0–100 · higher is better

These scores reward declared capabilities, context size, price and provider availability — they are not benchmark results. Use them as a directional signal alongside your own evaluation.

Coding63
  • Tool calling40/40
  • Structured output20/20
  • Reasoning0/10
  • Context window (100K → 1M)2/20
  • Provider availability1/10
Agents61
  • Tool calling35/35
  • Structured output25/25
  • Reasoning0/15
  • Output token limit0/15
  • Provider availability1/10
JSON / structured output95
  • Structured output / JSON mode50/50
  • Tool calling20/20
  • Temperature control10/10
  • Price-friendly for high-volume15/20
Cost efficiency58
  • Headline price (log-scaled)53/95
  • Has prompt-cache pricing5/5
Long context45
  • Context window (100K → 2M)35/90
  • Has published price for full window10/10
Production-readiness50
  • Number of independent providers5/40
  • Has published per-token price20/20
  • Context window ≥ 8K15/15
  • No data inconsistencies across providers10/10
  • Official model (not derivative)0/15

Cost Efficiency Index

Open full calculator →

Estimated cost using the recommended provider's headline rate. Each scenario fixes average input/output tokens — the assumptions are shown in the third column.

ScenarioCostAssumption
RAG answer
per 1,000 RAG answers
$3.90
< $0.01 per request
5K input tokens (query + 4 retrieved chunks of ~1K each) and a 500-token answer. Typical SaaS knowledge-base bot.
Support ticket triage
per 10,000 tickets
$7.80
< $0.01 per request
1K input tokens (ticket body + system prompt) and a 100-token JSON classification reply. High-volume customer support.
Data extraction
per 1,000 documents
$2.10
< $0.01 per request
2K input tokens (a single document page) and a 500-token JSON extraction. ETL / invoice / form pipelines.
Code review
per 1,000 PRs
$6.60
< $0.01 per request
8K input tokens (diff + surrounding files) and a 1K-token review comment. PR-bot workloads.
Agent step
per 1,000 steps
$8.28
< $0.01 per request
12K input tokens (long-running tool history) and a 600-token tool-call decision. Cost per agent step.

料金詳細

推奨料金 (提供元): nebius · nvidia/Llama-3_1-Nemotron-Ultra-253B-v1

$0.600
入力
$1.80
出力
$0.060
キャッシュ読み取り
$0.750
キャッシュ書き込み

1 か所で利用可能

プロバイダープロバイダーモデルID入力 / 1M出力 / 1Mコンテキストリリース日
Nebius Token Factory
nebius
nvidia/Llama-3_1-Nemotron-Ultra-253B-v1$0.600$1.80128K2025-01-15

Frequently asked questions

How much does Llama-3.1-Nemotron-Ultra-253B-v1 cost?

Llama-3.1-Nemotron-Ultra-253B-v1 costs $0.600 per 1M input tokens and $1.80 per 1M output tokens, sourced from nebius. Cache reads, audio tokens and >200K-context tiers (where applicable) are listed in the Pricing detail block above.

What is the context window of Llama-3.1-Nemotron-Ultra-253B-v1?

Llama-3.1-Nemotron-Ultra-253B-v1 has a context window of 128K tokens, with a max output of 4K tokens per reply. This is the total combined size of prompt + completion.

Does Llama-3.1-Nemotron-Ultra-253B-v1 support tool calling?

Yes. Llama-3.1-Nemotron-Ultra-253B-v1 supports tool calling (function calling). This makes it suitable for production agent and automation workloads where the model has to invoke external functions reliably.

Does Llama-3.1-Nemotron-Ultra-253B-v1 support structured output / JSON mode?

Yes. Llama-3.1-Nemotron-Ultra-253B-v1 supports structured output / JSON-schema-constrained decoding. This makes it suitable for production agent and automation workloads where the model has to invoke external functions reliably.

Can Llama-3.1-Nemotron-Ultra-253B-v1 accept image input?

No. Llama-3.1-Nemotron-Ultra-253B-v1 only accepts text as input. If you need image input, see our /capabilities/vision list for current vision-capable models.

Is Llama-3.1-Nemotron-Ultra-253B-v1 open-weight?

Yes. Llama-3.1-Nemotron-Ultra-253B-v1's weights are publicly available, so you can self-host or fine-tune. Note that open weights ≠ open source — the training data and code are typically not released.

What are the best alternatives to Llama-3.1-Nemotron-Ultra-253B-v1?

If Llama-3.1-Nemotron-Ultra-253B-v1 doesn't fit, consider Hermes-4-70B, Hermes-4-405B, INTELLECT-3. Each one targets the same use case — see the Related links below for direct head-to-head pages.

Where does this data come from?

All numbers come from the public models.dev API and are normalised into a single canonical model record. We re-pull daily and write any changes (price, context, capability) to the /changelog page.

Explore more

More nebius models

Capability lists this model is in

See also

最終更新：

Data is sourced from models.dev and normalized for comparison. Prices and capabilities may change. Always verify critical production decisions with the provider's official documentation.