GPT-5.6 Luna vs Mistral Small 3.2 24B Instruct

    Comparison

    As of August 20, 2026, Mistral Small 3.2 24B Instruct is 80% cheaper per million tokens than GPT-5.6 Luna. GPT-5.6 Luna is $0.20 / $1.20 per million input/output tokens versus Mistral Small 3.2 24B Instruct at $0.07 / $0.20. Sources: https://developers.openai.com/api/docs/pricing and https://openrouter.ai/api/v1/models

    Sources: OpenAI API pricing (https://developers.openai.com/api/docs/pricing); OpenRouter pricing (https://openrouter.ai/api/v1/models)

    GPT-5.6 Luna

    OpenAI

    $1.40blended / 1M

    Input

    $0.20

    Output

    $1.20

    1.1M ctx|Proprietary
    80%
    cheaper
    Better value

    Mistral Small 3.2 24B Instruct

    Mistral

    $0.28blended / 1M

    Input

    $0.07

    Output

    $0.20

    128K ctx|Open Source
    Save $1.13 per million tokens by choosing Mistral Small 3.2 24B Instruct over GPT-5.6 Luna.

    GPT-5.6 Luna vs Mistral Small 3.2 24B Instruct comparison

    Token pricing, specs, and benchmarks side by side

    Metric
    GPT-5.6 Luna
    Mistral Small 3.2 24B Instruct
    Provider
    Provider
    OpenAI
    Mistral
    License
    Proprietary
    Open Source
    Release Date
    2026-07-09
    2025-06-20
    Pricing (per 1M tokens)
    Input Price+167%
    $0.20
    $0.07
    Output Price+500%
    $1.20
    $0.20
    Blended (1M + 1M)
    $1.40
    $0.28
    Model Details
    Context Window
    1.1M
    128K
    Max Output Tokens
    128K
    N/A
    Knowledge Cutoff
    2026-02-16
    2023-10-01
    Throughput
    48.45216448188169 tok/s
    N/A
    Benchmarks
    92.3%
    46.1%
    63.6%
    67.2%
    67.2%
    52.5%
    1522.94
    83.3%
    41.7%
    12.1%
    59.5%
    53.4%
    78.4%
    78.6%
    40%
    80.5%
    85.0%
    62.5%
    69.4%
    92.9%
    0.2%
    43.1%
    63.1%
    87.4%
    64.2%
    20.6%
    83.9%
    94.9%
    67.1%
    33.2%
    12.4%
    39.8%
    22.7%
    55.8%
    84.8%
    72.9%
    22.4%
    51.2%
    67.1%
    78.3%
    30.4%
    42.4%
    84.4%
    86.0%
    69.1%
    41.3%
    1.7%
    45.6%
    41.9%
    44.2%
    46.8%
    60.5%
    76.2%
    65.3%
    Benchmark Wins
    GPT-5.6 Luna 4|0 Mistral Small 3.2 24B Instruct

    Verdict

    GPT-5.6 Luna vs Mistral Small 3.2 24B Instruct: the bottom line

    Mistral Small 3.2 24B Instruct offers significantly lower pricing, while GPT-5.6 Luna leads on benchmark performance. Your choice depends on whether cost efficiency or raw capability matters more for your use case.

    GPT-5.6 Luna vs Mistral Small 3.2 24B Instruct FAQ

    Which is cheaper, GPT-5.6 Luna or Mistral Small 3.2 24B Instruct?

    As of August 20, 2026, Mistral Small 3.2 24B Instruct is 80% cheaper on blended LLM API pricing. Mistral Small 3.2 24B Instruct costs $0.07 per million input tokens and $0.20 per million output tokens ($0.28 blended 1M-in + 1M-out). GPT-5.6 Luna costs $0.20 / $1.20 per million tokens ($1.40 blended). Sources: https://developers.openai.com/api/docs/pricing 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 GPT-5.6 Luna vs Mistral Small 3.2 24B Instruct cost per million tokens?

    GPT-5.6 Luna OpenAI API pricing is $0.20 input and $1.20 output per million tokens via OpenAI. Mistral Small 3.2 24B Instruct Mistral API pricing is $0.07 input and $0.20 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, GPT-5.6 Luna or Mistral Small 3.2 24B Instruct?

    GPT-5.6 Luna has a published SWE-bench Verified score of 93%. Mistral Small 3.2 24B Instruct does not have that eval on this page yet.

    What is the context window for GPT-5.6 Luna vs Mistral Small 3.2 24B Instruct?

    GPT-5.6 Luna supports a 1M token context window, while Mistral Small 3.2 24B Instruct 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 Mistral Small 3.2 24B Instruct?

    GPT-5.6 Luna leads on 4 of 4 shared benchmarks versus Mistral Small 3.2 24B 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 GPT-5.6 Luna or Mistral Small 3.2 24B Instruct better for production use?

    Both GPT-5.6 Luna and Mistral Small 3.2 24B Instruct are production API models. For cost-sensitive production traffic, Mistral Small 3.2 24B 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 GPT-5.6 Luna and Mistral Small 3.2 24B Instruct in my app?

    Yes. Call GPT-5.6 Luna through OpenAI and Mistral Small 3.2 24B Instruct 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 GPT-5.6 Luna vs Mistral Small 3.2 24B Instruct pricing data?

    List rates are the latest published OpenAI API pricing and Mistral API pricing, quoted per million tokens. Official rate sheets: https://developers.openai.com/api/docs/pricing 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 GPT-5.6 Luna and Mistral Small 3.2 24B Instruct?

    GPT-5.6 Luna supports up to 128K output tokens per request, while Mistral Small 3.2 24B Instruct 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, GPT-5.6 Luna or Mistral Small 3.2 24B Instruct?

    GPT-5.6 Luna has a measured throughput of approximately 48.45216448188169 tokens/second. Throughput data for Mistral Small 3.2 24B Instruct 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 GPT-5.6 Luna vs Mistral Small 3.2 24B Instruct 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 Mistral Small 3.2 24B 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.

    GPT-5.6 Luna vs Mistral Small 3.2 24B Instruct 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. Mistral Small 3.2 24B Instruct costs $0.07/M input and $0.20/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

    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

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