Ling-3.0-flash vs Nemotron Nano 9B v2

    Comparison

    As of August 20, 2026, Nemotron Nano 9B v2 is 100% cheaper per million tokens than Ling-3.0-flash. Ling-3.0-flash is $0.06 / $0.18 per million input/output tokens versus Nemotron Nano 9B v2 at $0.00 / $0.00. Sources: https://developer.ant-ling.com/en/docs/models/ling/ and https://openrouter.ai/api/v1/models

    Sources: inclusionAI pricing (https://developer.ant-ling.com/en/docs/models/ling/); OpenRouter pricing (https://openrouter.ai/api/v1/models)

    Ling-3.0-flash

    inclusionAI

    $0.24blended / 1M

    Input

    $0.06

    Output

    $0.18

    262.1K ctx|Proprietary
    100%
    cheaper
    Better value

    Nemotron Nano 9B v2

    NVIDIA

    $0.00blended / 1M

    Input

    $0.00

    Output

    $0.00

    128K ctx|Open Source
    Save $0.24 per million tokens by choosing Nemotron Nano 9B v2 over Ling-3.0-flash.

    Ling-3.0-flash vs Nemotron Nano 9B v2 comparison

    Token pricing, specs, and benchmarks side by side

    Metric
    Ling-3.0-flash
    Nemotron Nano 9B v2
    Provider
    Provider
    inclusionAI
    NVIDIA
    License
    Proprietary
    Open Source
    Release Date
    2026-07-23
    2025-08-18
    Pricing (per 1M tokens)
    Input Price+∞%
    $0.06
    $0.00
    Output Price+∞%
    $0.18
    $0.00
    Blended (1M + 1M)
    $0.24
    $0.00
    Model Details
    Context Window
    262.1K
    128K
    Max Output Tokens
    32.8K
    N/A
    Knowledge Cutoff
    N/A
    2024-09-01
    Throughput
    1000 tok/s
    N/A
    Benchmarks
    64%
    90.3%
    72.1%
    97.8%

    Verdict

    Ling-3.0-flash vs Nemotron Nano 9B v2: the bottom line

    Both models are closely matched on benchmarks. Nemotron Nano 9B v2 has the pricing advantage, making it the better value unless Ling-3.0-flash's specific capabilities are critical to your workflow.

    Ling-3.0-flash vs Nemotron Nano 9B v2 FAQ

    Which is cheaper, Ling-3.0-flash or Nemotron Nano 9B v2?

    As of August 20, 2026, Nemotron Nano 9B v2 is 100% cheaper on blended LLM API pricing. Nemotron Nano 9B v2 costs $0.00 per million input tokens and $0.00 per million output tokens ($0.00 blended 1M-in + 1M-out). Ling-3.0-flash costs $0.06 / $0.18 per million tokens ($0.24 blended). Sources: https://developer.ant-ling.com/en/docs/models/ling/ and https://openrouter.ai/api/v1/models. The cheapest LLM for your app still depends on how many output tokens you generate.

    How much does Ling-3.0-flash vs Nemotron Nano 9B v2 cost per million tokens?

    Ling-3.0-flash inclusionAI API pricing is $0.06 input and $0.18 output per million tokens via inclusionAI. Nemotron Nano 9B v2 OpenRouter API pricing is $0.00 input and $0.00 output per million tokens via OpenRouter. Use those four numbers, not ChatGPT Plus or Claude Pro subscription prices, when you are comparing APIs.

    Which is better for coding, Ling-3.0-flash or Nemotron Nano 9B v2?

    Nemotron Nano 9B v2 has a published LiveCodeBench score of 71.1%. Ling-3.0-flash does not have that eval on this page yet.

    What is the context window for Ling-3.0-flash vs Nemotron Nano 9B v2?

    Ling-3.0-flash supports a 262K token context window, while Nemotron Nano 9B v2 supports 128K tokens. Ling-3.0-flash 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, Ling-3.0-flash or Nemotron Nano 9B v2?

    Shared benchmark scores for Ling-3.0-flash and Nemotron Nano 9B v2 are still limited. Check the comparison table for the evals each model has published. 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 Ling-3.0-flash or Nemotron Nano 9B v2 better for production use?

    Both Ling-3.0-flash and Nemotron Nano 9B v2 are production API models. For cost-sensitive production traffic, Nemotron Nano 9B v2 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 Ling-3.0-flash and Nemotron Nano 9B v2 in my app?

    Yes. Call Ling-3.0-flash through inclusionAI and Nemotron Nano 9B v2 through OpenRouter 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 Ling-3.0-flash vs Nemotron Nano 9B v2 pricing data?

    List rates are the latest published inclusionAI API pricing and OpenRouter API pricing, quoted per million tokens. Official rate sheets: https://developer.ant-ling.com/en/docs/models/ling/ and https://openrouter.ai/api/v1/models. 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 Ling-3.0-flash and Nemotron Nano 9B v2?

    Ling-3.0-flash supports up to 33K output tokens per request, while Nemotron Nano 9B v2 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, Ling-3.0-flash or Nemotron Nano 9B v2?

    Ling-3.0-flash has a measured throughput of approximately 1000 tokens/second. Throughput data for Nemotron Nano 9B v2 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 Ling-3.0-flash vs Nemotron Nano 9B v2 comparison?

    Use the model pickers at the top of this LLM comparison. Search any model in the index and the URL updates. Open Ling-3.0-flash or Nemotron Nano 9B v2 from the sidebar for the single-model API pricing page, or go back to the LLM pricing table to sort by cheapest blended cost.

    Ling-3.0-flash vs Nemotron Nano 9B v2 pricing

    This comparison covers API pricing, context window, throughput, and benchmark scores. Ling-3.0-flash costs $0.06/M input and $0.18/M output. Nemotron Nano 9B v2 costs $0.00/M input and $0.00/M output via OpenRouter.

    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

    0 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

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