Llama 3.1 Nemotron Nano 8B V1 vs MAI-Thinking-1

    Comparison

    As of August 30, 2026, Llama 3.1 Nemotron Nano 8B V1 is 73% cheaper per million tokens than MAI-Thinking-1. Llama 3.1 Nemotron Nano 8B V1 is $0.04 / $0.16 per million input/output tokens versus MAI-Thinking-1 at $0.15 / $0.60. Sources: https://build.nvidia.com/nvidia/llama-3.1-nemotron-nano-8b-v1 and https://azure.microsoft.com/pricing/details/azure-openai-service/

    Sources: NVIDIA pricing (https://build.nvidia.com/nvidia/llama-3.1-nemotron-nano-8b-v1); Microsoft pricing (https://azure.microsoft.com/pricing/details/azure-openai-service/)

    Better value

    Llama 3.1 Nemotron Nano 8B V1

    NVIDIA

    $0.20blended / 1M

    Input

    $0.04

    Output

    $0.16

    128K ctx|Open Source
    73%
    cheaper

    MAI-Thinking-1

    Microsoft

    $0.75blended / 1M

    Input

    $0.15

    Output

    $0.60

    128K ctx|Proprietary
    Save $0.55 per million tokens by choosing Llama 3.1 Nemotron Nano 8B V1 over MAI-Thinking-1.

    Llama 3.1 Nemotron Nano 8B V1 vs MAI-Thinking-1 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.

    Llama 3.1 Nemotron Nano 8B V1MAI-Thinking-1

    Score vs price

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

    Best score at each priceLlama 3.1 Nemotron Nano 8B V1MAI-Thinking-1
    Metric
    Llama 3.1 Nemotron Nano 8B V1
    MAI-Thinking-1
    Provider
    Provider
    NVIDIA
    Microsoft
    License
    Open Source
    Proprietary
    Release Date
    2025-03-18
    2026-06-02
    Pricing (per 1M tokens)
    Input Price-73%
    $0.04
    $0.15
    Output Price-73%
    $0.16
    $0.60
    Blended (1M + 1M)
    $0.20
    $0.75
    Model Details
    Context Window
    128K
    128K
    Max Output Tokens
    N/A
    N/A
    Knowledge Cutoff
    2023-12-31
    N/A
    Throughput
    N/A
    N/A
    Benchmark Wins
    Llama 3.1 Nemotron Nano 8B V1 0|2 MAI-Thinking-1

    Verdict

    Llama 3.1 Nemotron Nano 8B V1 vs MAI-Thinking-1: the bottom line

    Llama 3.1 Nemotron Nano 8B V1 offers significantly lower pricing, while MAI-Thinking-1 leads on benchmark performance. Your choice depends on whether cost efficiency or raw capability matters more for your use case.

    Llama 3.1 Nemotron Nano 8B V1 vs MAI-Thinking-1 FAQ

    Which is cheaper, Llama 3.1 Nemotron Nano 8B V1 or MAI-Thinking-1?

    As of August 30, 2026, Llama 3.1 Nemotron Nano 8B V1 is 73% cheaper on blended LLM API pricing. Llama 3.1 Nemotron Nano 8B V1 costs $0.04 per million input tokens and $0.16 per million output tokens ($0.20 blended 1M-in + 1M-out). MAI-Thinking-1 costs $0.15 / $0.60 per million tokens ($0.75 blended). Sources: https://build.nvidia.com/nvidia/llama-3.1-nemotron-nano-8b-v1 and https://azure.microsoft.com/pricing/details/azure-openai-service/. The cheapest LLM for your app still depends on how many output tokens you generate.

    How much does Llama 3.1 Nemotron Nano 8B V1 vs MAI-Thinking-1 cost per million tokens?

    Llama 3.1 Nemotron Nano 8B V1 NVIDIA API pricing is $0.04 input and $0.16 output per million tokens via NVIDIA. MAI-Thinking-1 Microsoft API pricing is $0.15 input and $0.60 output per million tokens via Microsoft. Use those four numbers, not ChatGPT Plus or Claude Pro subscription prices, when you are comparing APIs.

    Which is better for coding, Llama 3.1 Nemotron Nano 8B V1 or MAI-Thinking-1?

    MAI-Thinking-1 has a published SWE-bench Verified score of 73.5%. Llama 3.1 Nemotron Nano 8B V1 does not have that eval on this page yet.

    What is the context window for Llama 3.1 Nemotron Nano 8B V1 vs MAI-Thinking-1?

    Llama 3.1 Nemotron Nano 8B V1 supports a 128K token context window, while MAI-Thinking-1 supports 128K tokens. Both models have the same context window size. 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, Llama 3.1 Nemotron Nano 8B V1 or MAI-Thinking-1?

    MAI-Thinking-1 leads on 2 of 2 shared benchmarks versus Llama 3.1 Nemotron Nano 8B V1'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 Llama 3.1 Nemotron Nano 8B V1 or MAI-Thinking-1 better for production use?

    Both Llama 3.1 Nemotron Nano 8B V1 and MAI-Thinking-1 are production API models. For cost-sensitive production traffic, Llama 3.1 Nemotron Nano 8B 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 Llama 3.1 Nemotron Nano 8B V1 and MAI-Thinking-1 in my app?

    Yes. Call Llama 3.1 Nemotron Nano 8B V1 through NVIDIA and MAI-Thinking-1 through Microsoft 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 Llama 3.1 Nemotron Nano 8B V1 vs MAI-Thinking-1 pricing data?

    List rates are the latest published NVIDIA API pricing and Microsoft API pricing, quoted per million tokens. Official rate sheets: https://build.nvidia.com/nvidia/llama-3.1-nemotron-nano-8b-v1 and https://azure.microsoft.com/pricing/details/azure-openai-service/. 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 Llama 3.1 Nemotron Nano 8B V1 and MAI-Thinking-1?

    Llama 3.1 Nemotron Nano 8B V1 supports up to an unspecified number of output tokens per request, while MAI-Thinking-1 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, Llama 3.1 Nemotron Nano 8B V1 or MAI-Thinking-1?

    Neither Llama 3.1 Nemotron Nano 8B V1 nor MAI-Thinking-1 has published throughput data on this page yet. 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 Llama 3.1 Nemotron Nano 8B V1 vs MAI-Thinking-1 comparison?

    Use the model pickers at the top of this LLM comparison. Search any model in the index and the URL updates. Open Llama 3.1 Nemotron Nano 8B V1 or MAI-Thinking-1 from the sidebar for the single-model API pricing page, or go back to the LLM pricing table to sort by cheapest blended cost.

    Llama 3.1 Nemotron Nano 8B V1 vs MAI-Thinking-1 pricing

    This comparison covers API pricing, context window, throughput, and benchmark scores. Llama 3.1 Nemotron Nano 8B V1 costs $0.04/M input and $0.16/M output. MAI-Thinking-1 costs $0.15/M input and $0.60/M output.

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

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