GPT-4o vs Llama 3.1 Nemotron Ultra 253B v1

    Comparison

    As of August 30, 2026, Llama 3.1 Nemotron Ultra 253B v1 is 81% cheaper per million tokens than GPT-4o. GPT-4o is $2.50 / $10.00 per million input/output tokens versus Llama 3.1 Nemotron Ultra 253B v1 at $0.60 / $1.80. Sources: https://developers.openai.com/api/docs/pricing and https://build.nvidia.com/nvidia/llama-3_1-nemotron-ultra-253b-v1

    Sources: OpenAI API pricing (https://developers.openai.com/api/docs/pricing); NVIDIA pricing (https://build.nvidia.com/nvidia/llama-3_1-nemotron-ultra-253b-v1)

    GPT-4o

    OpenAI

    $12.50blended / 1M

    Input

    $2.50

    Output

    $10.00

    128K ctx|Proprietary
    81%
    cheaper
    Better value

    Llama 3.1 Nemotron Ultra 253B v1

    NVIDIA

    $2.40blended / 1M

    Input

    $0.60

    Output

    $1.80

    131.1K ctx|Open Source
    Save $10.10 per million tokens by choosing Llama 3.1 Nemotron Ultra 253B v1 over GPT-4o.

    GPT-4o vs Llama 3.1 Nemotron Ultra 253B v1 comparison

    Token pricing, specs, and benchmarks side by side

    Shared benchmarks

    Each bar is share of the current leader on that eval. Click a row to open the board.

    Score vs price

    AIME 2025. Left is cheaper. Up is a higher score. The line is the best score you can buy at each price.

    Best score at each priceGPT-4oLlama 3.1 Nemotron Ultra 253B v1
    Metric
    GPT-4o
    Llama 3.1 Nemotron Ultra 253B v1
    Provider
    Provider
    OpenAI
    NVIDIA
    License
    Proprietary
    Open Source
    Release Date
    2024-08-06
    2025-04-07
    Pricing (per 1M tokens)
    Input Price+317%
    $2.50
    $0.60
    Output Price+456%
    $10.00
    $1.80
    Blended (1M + 1M)
    $12.50
    $2.40
    Model Details
    Context Window
    128K
    131.1K
    Max Output Tokens
    16.4K
    N/A
    Knowledge Cutoff
    October 2023
    2023-12-01
    Throughput
    99 tok/s
    N/A
    Benchmarks
    5.3%
    70.1%
    76.0%
    49.2%
    38.2%
    81%
    89.5%
    59.9%
    81.4%
    58.8%
    6.4%
    72.5%
    13.1%
    75.2%
    97%
    10%
    85.7%
    72.2%
    53.3%
    61.9%
    94.2%
    74.1%
    85.7%
    85.3%
    61%
    39.4%
    92.8%
    72.2%
    35.2%
    55.3%
    61.4%
    88.2%
    90.7%
    74.7%
    60.9%
    17.8%
    32.6%
    71.1%
    71.9%
    61.2%
    Benchmark Wins
    GPT-4o 0|4 Llama 3.1 Nemotron Ultra 253B v1

    Verdict

    GPT-4o vs Llama 3.1 Nemotron Ultra 253B v1: the bottom line

    Llama 3.1 Nemotron Ultra 253B v1 offers both lower pricing and stronger benchmark performance across the board, making it the clear value leader in this comparison.

    GPT-4o vs Llama 3.1 Nemotron Ultra 253B v1 FAQ

    Which is cheaper, GPT-4o or Llama 3.1 Nemotron Ultra 253B v1?

    As of August 30, 2026, Llama 3.1 Nemotron Ultra 253B v1 is 81% cheaper on blended LLM API pricing. Llama 3.1 Nemotron Ultra 253B v1 costs $0.60 per million input tokens and $1.80 per million output tokens ($2.40 blended 1M-in + 1M-out). GPT-4o costs $2.50 / $10.00 per million tokens ($12.50 blended). Sources: https://developers.openai.com/api/docs/pricing and https://build.nvidia.com/nvidia/llama-3_1-nemotron-ultra-253b-v1. The cheapest LLM for your app still depends on how many output tokens you generate.

    How much does GPT-4o vs Llama 3.1 Nemotron Ultra 253B v1 cost per million tokens?

    GPT-4o OpenAI API pricing is $2.50 input and $10.00 output per million tokens via OpenAI. Llama 3.1 Nemotron Ultra 253B v1 NVIDIA API pricing is $0.60 input and $1.80 output per million tokens via NVIDIA. Use those four numbers, not ChatGPT Plus or Claude Pro subscription prices, when you are comparing APIs.

    Which is better for coding, GPT-4o or Llama 3.1 Nemotron Ultra 253B v1?

    GPT-4o has a published SWE-bench Verified score of 33.2%. Llama 3.1 Nemotron Ultra 253B v1 does not have that eval on this page yet.

    What is the context window for GPT-4o vs Llama 3.1 Nemotron Ultra 253B v1?

    GPT-4o supports a 128K token context window, while Llama 3.1 Nemotron Ultra 253B v1 supports 131K tokens. Llama 3.1 Nemotron Ultra 253B v1 offers a larger context window. Filling a larger window bills more input tokens, so the cheaper-per-million model can still cost more on long documents.

    Which model performs better on benchmarks, GPT-4o or Llama 3.1 Nemotron Ultra 253B v1?

    Llama 3.1 Nemotron Ultra 253B v1 leads on 4 of 4 shared benchmarks versus GPT-4o's 0 wins. Check the comparison table for GPQA Diamond, SWE-bench, MMLU, HLE, and the other evals we track. Token price and benchmark score together are the usual LLM comparison, not either number alone.

    Is GPT-4o or Llama 3.1 Nemotron Ultra 253B v1 better for production use?

    Both GPT-4o and Llama 3.1 Nemotron Ultra 253B v1 are production API models. For cost-sensitive production traffic, Llama 3.1 Nemotron Ultra 253B v1 has better economics on the blended 1M-in + 1M-out scale. For maximum capability, weight the benchmark table for your domain. Many production stacks route cheap models for drafts and a frontier model for the hard turn, which is usually cheaper than sending everything to the expensive API.

    Can I switch between GPT-4o and Llama 3.1 Nemotron Ultra 253B v1 in my app?

    Yes. Call GPT-4o through OpenAI and Llama 3.1 Nemotron Ultra 253B v1 through NVIDIA with separate API keys, or through a gateway that already wraps both. Keep prompts in tokens, not characters, when you estimate the invoice. AnotherWrapper templates can swap providers without rewriting auth and billing.

    How accurate is this GPT-4o vs Llama 3.1 Nemotron Ultra 253B v1 pricing data?

    List rates are the latest published OpenAI API pricing and NVIDIA API pricing, quoted per million tokens. Official rate sheets: https://developers.openai.com/api/docs/pricing and https://build.nvidia.com/nvidia/llama-3_1-nemotron-ultra-253b-v1. Prompt caching, batch APIs, and committed-use discounts can change the invoice. Benchmark scores are from official publications and independent evals, updated as new numbers land.

    What is the output token limit for GPT-4o and Llama 3.1 Nemotron Ultra 253B v1?

    GPT-4o supports up to 16K output tokens per request, while Llama 3.1 Nemotron Ultra 253B v1 supports up to an unspecified number of output tokens. Output tokens are usually the expensive half of API pricing, so a higher max output cap is a capability, not a discount.

    Which model has better throughput, GPT-4o or Llama 3.1 Nemotron Ultra 253B v1?

    GPT-4o has a measured throughput of approximately 99 tokens/second. Throughput data for Llama 3.1 Nemotron Ultra 253B v1 is not yet available. Throughput (tokens per second) and time-to-first-token are why two models with the same per-million-token price can still feel different in chat and agents.

    How do I switch the models in this GPT-4o vs Llama 3.1 Nemotron Ultra 253B v1 comparison?

    Use the model pickers at the top of this LLM comparison. Search any model in the index and the URL updates. Open GPT-4o or Llama 3.1 Nemotron Ultra 253B v1 from the sidebar for the single-model API pricing page, or go back to the LLM pricing table to sort by cheapest blended cost.

    GPT-4o vs Llama 3.1 Nemotron Ultra 253B v1 pricing

    This comparison covers API pricing, context window, throughput, and benchmark scores. GPT-4o costs $2.50/M input and $10.00/M output. Llama 3.1 Nemotron Ultra 253B v1 costs $0.60/M input and $1.80/M output.

    Rank both on the LLM leaderboard, SWE-bench, and Humanity's Last Exam.

    The index

    All Large Language Models

    343 models across 36 providers. Search or jump to a lab — every model page stays linked here.

    Baidu

    2 models

    Inception

    1 models

    inclusionAI

    1 models

    LG AI Research

    1 models

    Liquid AI

    2 models

    Nous Research

    1 models

    OpenBMB

    1 models

    Sakana AI

    1 models

    Sarvam AI

    2 models

    Tencent

    1 models

    Thinking Machines

    1 models

    Unisound

    1 models

    Upstage

    1 models

    Next step

    You found the model. Now ship the product.

    Auth, billing, and the API layer are already decided. Fork 8 finished AI apps, or have us build the first version with you.