GPT-5.6 Luna vs LongCat-Flash-Thinking-2601

    Comparison

    As of August 20, 2026, GPT-5.6 Luna is 7% cheaper per million tokens than LongCat-Flash-Thinking-2601. GPT-5.6 Luna is $0.20 / $1.20 per million input/output tokens versus LongCat-Flash-Thinking-2601 at $0.30 / $1.20. Sources: https://developers.openai.com/api/docs/pricing and https://anotherwrapper.com/tools/llm-pricing

    Sources: OpenAI API pricing (https://developers.openai.com/api/docs/pricing); AnotherWrapper LLM pricing (https://anotherwrapper.com/tools/llm-pricing)

    Better value

    GPT-5.6 Luna

    OpenAI

    $1.40blended / 1M

    Input

    $0.20

    Output

    $1.20

    1.1M ctx|Proprietary
    7%
    cheaper

    LongCat-Flash-Thinking-2601

    Meituan

    $1.50blended / 1M

    Input

    $0.30

    Output

    $1.20

    128K ctx|Open Source
    Save $0.10 per million tokens by choosing GPT-5.6 Luna over LongCat-Flash-Thinking-2601.

    GPT-5.6 Luna vs LongCat-Flash-Thinking-2601 comparison

    Token pricing, specs, and benchmarks side by side

    Metric
    GPT-5.6 Luna
    LongCat-Flash-Thinking-2601
    Provider
    Provider
    OpenAI
    Meituan
    License
    Proprietary
    Open Source
    Release Date
    2026-07-09
    2026-01-14
    Pricing (per 1M tokens)
    Input Price-33%
    $0.20
    $0.30
    Output Price0%
    $1.20
    $1.20
    Blended (1M + 1M)
    $1.40
    $1.50
    Model Details
    Context Window
    1.1M
    128K
    Max Output Tokens
    128K
    128K
    Knowledge Cutoff
    2026-02-16
    N/A
    Throughput
    48.45216448188169 tok/s
    100 tok/s
    Benchmarks
    25.2%
    92.3%
    80.5%
    63.6%
    67.2%
    67.2%
    52.5%
    1522.94
    83.3%
    56.6%
    41.7%
    59.5%
    53.4%
    78.4%
    78.6%
    40%
    99.6%
    85.0%
    0.2%
    63.1%
    64.2%
    20.6%
    83.9%
    67.1%
    33.2%
    12.4%
    39.8%
    22.7%
    55.8%
    72.9%
    22.4%
    51.2%
    30.4%
    42.4%
    84.4%
    86.0%
    41.3%
    1.7%
    45.6%
    41.9%
    44.2%
    46.8%
    60.5%
    76.2%
    Benchmark Wins
    GPT-5.6 Luna 3|1 LongCat-Flash-Thinking-2601

    Verdict

    GPT-5.6 Luna vs LongCat-Flash-Thinking-2601: the bottom line

    GPT-5.6 Luna offers both lower pricing and stronger benchmark performance across the board, making it the clear value leader in this comparison.

    GPT-5.6 Luna vs LongCat-Flash-Thinking-2601 FAQ

    Which is cheaper, GPT-5.6 Luna or LongCat-Flash-Thinking-2601?

    As of August 20, 2026, GPT-5.6 Luna is 7% cheaper on blended LLM API pricing. GPT-5.6 Luna costs $0.20 per million input tokens and $1.20 per million output tokens ($1.40 blended 1M-in + 1M-out). LongCat-Flash-Thinking-2601 costs $0.30 / $1.20 per million tokens ($1.50 blended). Sources: https://developers.openai.com/api/docs/pricing and https://anotherwrapper.com/tools/llm-pricing. The cheapest LLM for your app still depends on how many output tokens you generate.

    How much does GPT-5.6 Luna vs LongCat-Flash-Thinking-2601 cost per million tokens?

    GPT-5.6 Luna OpenAI API pricing is $0.20 input and $1.20 output per million tokens via OpenAI. LongCat-Flash-Thinking-2601 Meituan API pricing is $0.30 input and $1.20 output per million tokens via Meituan. Use those four numbers, not ChatGPT Plus or Claude Pro subscription prices, when you are comparing APIs.

    Which is better for coding, GPT-5.6 Luna or LongCat-Flash-Thinking-2601?

    GPT-5.6 Luna leads on SWE-bench Verified: GPT-5.6 Luna at 93% vs LongCat-Flash-Thinking-2601 at 70%. SWE-bench measures real GitHub fixes; LiveCodeBench measures contest programming.

    What is the context window for GPT-5.6 Luna vs LongCat-Flash-Thinking-2601?

    GPT-5.6 Luna supports a 1M token context window, while LongCat-Flash-Thinking-2601 supports 128K tokens. GPT-5.6 Luna 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-5.6 Luna or LongCat-Flash-Thinking-2601?

    GPT-5.6 Luna leads on 3 of 4 shared benchmarks versus LongCat-Flash-Thinking-2601's 1 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-5.6 Luna or LongCat-Flash-Thinking-2601 better for production use?

    Both GPT-5.6 Luna and LongCat-Flash-Thinking-2601 are production API models. For cost-sensitive production traffic, GPT-5.6 Luna 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-5.6 Luna and LongCat-Flash-Thinking-2601 in my app?

    Yes. Call GPT-5.6 Luna through OpenAI and LongCat-Flash-Thinking-2601 through Meituan 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-5.6 Luna vs LongCat-Flash-Thinking-2601 pricing data?

    List rates are the latest published OpenAI API pricing and Meituan API pricing, quoted per million tokens. Official rate sheets: https://developers.openai.com/api/docs/pricing and https://anotherwrapper.com/tools/llm-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 GPT-5.6 Luna and LongCat-Flash-Thinking-2601?

    GPT-5.6 Luna supports up to 128K output tokens per request, while LongCat-Flash-Thinking-2601 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, GPT-5.6 Luna or LongCat-Flash-Thinking-2601?

    GPT-5.6 Luna runs at approximately 48.45216448188169 tokens/second while LongCat-Flash-Thinking-2601 runs at 100 tokens/second. LongCat-Flash-Thinking-2601 is faster in raw throughput. 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-5.6 Luna vs LongCat-Flash-Thinking-2601 comparison?

    Use the model pickers at the top of this LLM comparison. Search any model in the index and the URL updates. Open GPT-5.6 Luna or LongCat-Flash-Thinking-2601 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-5.6 Luna vs LongCat-Flash-Thinking-2601 pricing

    This comparison covers API pricing, context window, throughput, and benchmark scores. GPT-5.6 Luna costs $0.20/M input and $1.20/M output. LongCat-Flash-Thinking-2601 costs $0.30/M input and $1.20/M output.

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

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