Nemotron 3.5 Lightning (30B A3B) vs Phi-3.5-mini-instruct

    Comparison

    As of August 20, 2026, Phi-3.5-mini-instruct is 20% cheaper per million tokens than Nemotron 3.5 Lightning (30B A3B). Nemotron 3.5 Lightning (30B A3B) is $0.05 / $0.20 per million input/output tokens versus Phi-3.5-mini-instruct at $0.10 / $0.10. Sources: https://build.nvidia.com and https://azure.microsoft.com/en-us/pricing/details/cognitive-services/openai-service/

    Sources: NVIDIA pricing (https://build.nvidia.com); Microsoft pricing (https://azure.microsoft.com/en-us/pricing/details/cognitive-services/openai-service/)

    Nemotron 3.5 Lightning (30B A3B)

    NVIDIA

    $0.25blended / 1M

    Input

    $0.05

    Output

    $0.20

    262.1K ctx|Open Source
    20%
    cheaper
    Better value

    Phi-3.5-mini-instruct

    Microsoft

    $0.20blended / 1M

    Input

    $0.10

    Output

    $0.10

    128K ctx|Open Source
    Save $0.05 per million tokens by choosing Phi-3.5-mini-instruct over Nemotron 3.5 Lightning (30B A3B).

    Nemotron 3.5 Lightning (30B A3B) vs Phi-3.5-mini-instruct comparison

    Token pricing, specs, and benchmarks side by side

    Metric
    Nemotron 3.5 Lightning (30B A3B)
    Phi-3.5-mini-instruct
    Provider
    Provider
    NVIDIA
    Microsoft
    License
    Open Source
    Open Source
    Release Date
    2026-08-11
    2024-08-23
    Pricing (per 1M tokens)
    Input Price-50%
    $0.05
    $0.10
    Output Price+100%
    $0.20
    $0.10
    Blended (1M + 1M)
    $0.25
    $0.20
    Model Details
    Context Window
    262.1K
    128K
    Max Output Tokens
    262.1K
    128K
    Knowledge Cutoff
    N/A
    N/A
    Throughput
    N/A
    23 tok/s
    Benchmarks
    11.7%
    75.4%
    30.4%
    32.6%
    37.0%
    71.9%
    52%
    55.4%
    69%
    69.4%
    62.8%
    48.5%
    84.6%
    78%
    25.9%
    86.2%
    69.6%
    61.7%
    62.2%
    46.5%
    63.1%
    47.9%
    81.9%
    47.4%
    17.5%
    79.2%
    85.4%
    81%
    41.9%
    21.3%
    77%
    84.1%
    74.7%
    24.3%
    68.5%
    Benchmark Wins
    Nemotron 3.5 Lightning (30B A3B) 2|0 Phi-3.5-mini-instruct

    Verdict

    Nemotron 3.5 Lightning (30B A3B) vs Phi-3.5-mini-instruct: the bottom line

    Phi-3.5-mini-instruct offers significantly lower pricing, while Nemotron 3.5 Lightning (30B A3B) leads on benchmark performance. Your choice depends on whether cost efficiency or raw capability matters more for your use case.

    Nemotron 3.5 Lightning (30B A3B) vs Phi-3.5-mini-instruct FAQ

    Which is cheaper, Nemotron 3.5 Lightning (30B A3B) or Phi-3.5-mini-instruct?

    As of August 20, 2026, Phi-3.5-mini-instruct is 20% cheaper on blended LLM API pricing. Phi-3.5-mini-instruct costs $0.10 per million input tokens and $0.10 per million output tokens ($0.20 blended 1M-in + 1M-out). Nemotron 3.5 Lightning (30B A3B) costs $0.05 / $0.20 per million tokens ($0.25 blended). Sources: https://build.nvidia.com and https://azure.microsoft.com/en-us/pricing/details/cognitive-services/openai-service/. The cheapest LLM for your app still depends on how many output tokens you generate.

    How much does Nemotron 3.5 Lightning (30B A3B) vs Phi-3.5-mini-instruct cost per million tokens?

    Nemotron 3.5 Lightning (30B A3B) NVIDIA API pricing is $0.05 input and $0.20 output per million tokens via NVIDIA. Phi-3.5-mini-instruct Microsoft API pricing is $0.10 input and $0.10 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, Nemotron 3.5 Lightning (30B A3B) or Phi-3.5-mini-instruct?

    Nemotron 3.5 Lightning (30B A3B) has a published SWE-bench Verified score of 51.6%. Phi-3.5-mini-instruct does not have that eval on this page yet.

    What is the context window for Nemotron 3.5 Lightning (30B A3B) vs Phi-3.5-mini-instruct?

    Nemotron 3.5 Lightning (30B A3B) supports a 262K token context window, while Phi-3.5-mini-instruct supports 128K tokens. Nemotron 3.5 Lightning (30B A3B) 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, Nemotron 3.5 Lightning (30B A3B) or Phi-3.5-mini-instruct?

    Nemotron 3.5 Lightning (30B A3B) leads on 2 of 2 shared benchmarks versus Phi-3.5-mini-instruct'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 Nemotron 3.5 Lightning (30B A3B) or Phi-3.5-mini-instruct better for production use?

    Both Nemotron 3.5 Lightning (30B A3B) and Phi-3.5-mini-instruct are production API models. For cost-sensitive production traffic, Phi-3.5-mini-instruct 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 Nemotron 3.5 Lightning (30B A3B) and Phi-3.5-mini-instruct in my app?

    Yes. Call Nemotron 3.5 Lightning (30B A3B) through NVIDIA and Phi-3.5-mini-instruct 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 Nemotron 3.5 Lightning (30B A3B) vs Phi-3.5-mini-instruct 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 and https://azure.microsoft.com/en-us/pricing/details/cognitive-services/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 Nemotron 3.5 Lightning (30B A3B) and Phi-3.5-mini-instruct?

    Nemotron 3.5 Lightning (30B A3B) supports up to 262K output tokens per request, while Phi-3.5-mini-instruct supports up to 128K 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, Nemotron 3.5 Lightning (30B A3B) or Phi-3.5-mini-instruct?

    Phi-3.5-mini-instruct has a measured throughput of approximately 23 tokens/second. Throughput data for Nemotron 3.5 Lightning (30B A3B) 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 Nemotron 3.5 Lightning (30B A3B) vs Phi-3.5-mini-instruct comparison?

    Use the model pickers at the top of this LLM comparison. Search any model in the index and the URL updates. Open Nemotron 3.5 Lightning (30B A3B) or Phi-3.5-mini-instruct from the sidebar for the single-model API pricing page, or go back to the LLM pricing table to sort by cheapest blended cost.

    Nemotron 3.5 Lightning (30B A3B) vs Phi-3.5-mini-instruct pricing

    This comparison covers API pricing, context window, throughput, and benchmark scores. Nemotron 3.5 Lightning (30B A3B) costs $0.05/M input and $0.20/M output. Phi-3.5-mini-instruct costs $0.10/M input and $0.10/M output.

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

    The index

    All Large Language Models

    280 models across 33 providers. Search or jump to a lab — every model page stays linked here.

    Baidu

    1 models

    Inception

    1 models

    inclusionAI

    1 models

    LG AI Research

    1 models

    Nous Research

    1 models

    Sakana AI

    1 models

    StepFun

    1 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.