Ling-3.0-flash vs Qwen3.8-2.4T-A95B

    Comparison

    As of August 20, 2026, Ling-3.0-flash is 97% cheaper per million tokens than Qwen3.8-2.4T-A95B. Ling-3.0-flash is $0.06 / $0.18 per million input/output tokens versus Qwen3.8-2.4T-A95B at $2.00 / $6.00. Sources: https://developer.ant-ling.com/en/docs/models/ling/ and https://www.alibabacloud.com/help/en/model-studio/pricing

    Sources: inclusionAI pricing (https://developer.ant-ling.com/en/docs/models/ling/); Qwen pricing (https://www.alibabacloud.com/help/en/model-studio/pricing)

    Better value

    Ling-3.0-flash

    inclusionAI

    $0.24blended / 1M

    Input

    $0.06

    Output

    $0.18

    262.1K ctx|Proprietary
    97%
    cheaper

    Qwen3.8-2.4T-A95B

    Qwen

    $8.00blended / 1M

    Input

    $2.00

    Output

    $6.00

    1M ctx|Open Source
    Save $7.76 per million tokens by choosing Ling-3.0-flash over Qwen3.8-2.4T-A95B.

    Ling-3.0-flash vs Qwen3.8-2.4T-A95B comparison

    Token pricing, specs, and benchmarks side by side

    Metric
    Ling-3.0-flash
    Qwen3.8-2.4T-A95B
    Provider
    Provider
    inclusionAI
    Qwen
    License
    Proprietary
    Open Source
    Release Date
    2026-07-23
    2026-08-12
    Pricing (per 1M tokens)
    Input Price-97%
    $0.06
    $2.00
    Output Price-97%
    $0.18
    $6.00
    Blended (1M + 1M)
    $0.24
    $8.00
    Model Details
    Context Window
    262.1K
    1M
    Max Output Tokens
    32.8K
    N/A
    Knowledge Cutoff
    N/A
    N/A
    Throughput
    1000 tok/s
    N/A

    Verdict

    Ling-3.0-flash vs Qwen3.8-2.4T-A95B: the bottom line

    Both models are closely matched on benchmarks. Ling-3.0-flash has the pricing advantage, making it the better value unless Qwen3.8-2.4T-A95B's specific capabilities are critical to your workflow.

    Ling-3.0-flash vs Qwen3.8-2.4T-A95B FAQ

    Which is cheaper, Ling-3.0-flash or Qwen3.8-2.4T-A95B?

    As of August 20, 2026, Ling-3.0-flash is 97% cheaper on blended LLM API pricing. Ling-3.0-flash costs $0.06 per million input tokens and $0.18 per million output tokens ($0.24 blended 1M-in + 1M-out). Qwen3.8-2.4T-A95B costs $2.00 / $6.00 per million tokens ($8.00 blended). Sources: https://developer.ant-ling.com/en/docs/models/ling/ and https://www.alibabacloud.com/help/en/model-studio/pricing. The cheapest LLM for your app still depends on how many output tokens you generate.

    How much does Ling-3.0-flash vs Qwen3.8-2.4T-A95B cost per million tokens?

    Ling-3.0-flash inclusionAI API pricing is $0.06 input and $0.18 output per million tokens via inclusionAI. Qwen3.8-2.4T-A95B Qwen API pricing is $2.00 input and $6.00 output per million tokens via Qwen. 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 Qwen3.8-2.4T-A95B?

    Neither Ling-3.0-flash nor Qwen3.8-2.4T-A95B has a published SWE-bench or LiveCodeBench score on this page yet. Use the comparison table for the evals that do exist.

    What is the context window for Ling-3.0-flash vs Qwen3.8-2.4T-A95B?

    Ling-3.0-flash supports a 262K token context window, while Qwen3.8-2.4T-A95B supports 1M tokens. Qwen3.8-2.4T-A95B 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 Qwen3.8-2.4T-A95B?

    Shared benchmark scores for Ling-3.0-flash and Qwen3.8-2.4T-A95B 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 Qwen3.8-2.4T-A95B better for production use?

    Both Ling-3.0-flash and Qwen3.8-2.4T-A95B are production API models. For cost-sensitive production traffic, Ling-3.0-flash 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 Qwen3.8-2.4T-A95B in my app?

    Yes. Call Ling-3.0-flash through inclusionAI and Qwen3.8-2.4T-A95B through Qwen 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 Qwen3.8-2.4T-A95B pricing data?

    List rates are the latest published inclusionAI API pricing and Qwen API pricing, quoted per million tokens. Official rate sheets: https://developer.ant-ling.com/en/docs/models/ling/ and https://www.alibabacloud.com/help/en/model-studio/pricing. 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 Qwen3.8-2.4T-A95B?

    Ling-3.0-flash supports up to 33K output tokens per request, while Qwen3.8-2.4T-A95B 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 Qwen3.8-2.4T-A95B?

    Ling-3.0-flash has a measured throughput of approximately 1000 tokens/second. Throughput data for Qwen3.8-2.4T-A95B 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 Qwen3.8-2.4T-A95B 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 Qwen3.8-2.4T-A95B 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 Qwen3.8-2.4T-A95B 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. Qwen3.8-2.4T-A95B costs $2.00/M input and $6.00/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

    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

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