Llama 4 Scout vs Ministral 3 (14B Reasoning 2512)

    Comparison

    As of August 25, 2026, Llama 4 Scout is 5% cheaper per million tokens than Ministral 3 (14B Reasoning 2512). Llama 4 Scout is $0.08 / $0.30 per million input/output tokens versus Ministral 3 (14B Reasoning 2512) at $0.20 / $0.20. Sources: https://llama.meta.com/ and https://docs.mistral.ai/platform/pricing/

    Sources: Meta pricing (https://llama.meta.com/); Mistral AI pricing (https://docs.mistral.ai/platform/pricing/)

    Better value

    Llama 4 Scout

    Meta

    $0.38blended / 1M

    Input

    $0.08

    Output

    $0.30

    10M ctx|Open Source
    5%
    cheaper

    Ministral 3 (14B Reasoning 2512)

    Mistral

    $0.40blended / 1M

    Input

    $0.20

    Output

    $0.20

    262.1K ctx|Open Source
    Save $0.02 per million tokens by choosing Llama 4 Scout over Ministral 3 (14B Reasoning 2512).

    Llama 4 Scout vs Ministral 3 (14B Reasoning 2512) comparison

    Token pricing, specs, and benchmarks side by side

    Shared benchmarks

    Each bar is share of the current leader on that eval. Click a row to open the board.

    Llama 4 ScoutMinistral 3 (14B Reasoning 2512)

    Score vs price

    GPQA. Left is cheaper. Up is a higher score. The line is the best score you can buy at each price.

    Best score at each priceLlama 4 ScoutMinistral 3 (14B Reasoning 2512)
    Metric
    Llama 4 Scout
    Ministral 3 (14B Reasoning 2512)
    Provider
    Provider
    Meta
    Mistral
    License
    Open Source
    Open Source
    Release Date
    2025-04-05
    2025-12-04
    Pricing (per 1M tokens)
    Input Price-60%
    $0.08
    $0.20
    Output Price+50%
    $0.30
    $0.20
    Blended (1M + 1M)
    $0.38
    $0.40
    Model Details
    Context Window
    10M
    262.1K
    Max Output Tokens
    10M
    262.1K
    Knowledge Cutoff
    N/A
    N/A
    Throughput
    76.1 tok/s
    128.6 tok/s
    Benchmarks
    57.2%
    71.2%
    57.2%
    32.8%
    64.6%
    17.0%
    85%
    89.8%
    79.6%
    69.4%
    50.3%
    88.8%
    0%
    94.4%
    70.7%
    67.8%
    90.6%
    74.3%
    31.5%
    Benchmark Wins
    Llama 4 Scout 0|2 Ministral 3 (14B Reasoning 2512)

    Verdict

    Llama 4 Scout vs Ministral 3 (14B Reasoning 2512): the bottom line

    Llama 4 Scout offers significantly lower pricing, while Ministral 3 (14B Reasoning 2512) leads on benchmark performance. Your choice depends on whether cost efficiency or raw capability matters more for your use case.

    Llama 4 Scout vs Ministral 3 (14B Reasoning 2512) FAQ

    Which is cheaper, Llama 4 Scout or Ministral 3 (14B Reasoning 2512)?

    As of August 25, 2026, Llama 4 Scout is 5% cheaper on blended LLM API pricing. Llama 4 Scout costs $0.08 per million input tokens and $0.30 per million output tokens ($0.38 blended 1M-in + 1M-out). Ministral 3 (14B Reasoning 2512) costs $0.20 / $0.20 per million tokens ($0.40 blended). Sources: https://llama.meta.com/ and https://docs.mistral.ai/platform/pricing/. The cheapest LLM for your app still depends on how many output tokens you generate.

    How much does Llama 4 Scout vs Ministral 3 (14B Reasoning 2512) cost per million tokens?

    Llama 4 Scout Meta API pricing is $0.08 input and $0.30 output per million tokens via Meta. Ministral 3 (14B Reasoning 2512) Mistral API pricing is $0.20 input and $0.20 output per million tokens via Mistral AI. Use those four numbers, not ChatGPT Plus or Claude Pro subscription prices, when you are comparing APIs.

    Which is better for coding, Llama 4 Scout or Ministral 3 (14B Reasoning 2512)?

    Ministral 3 (14B Reasoning 2512) leads on LiveCodeBench: Llama 4 Scout at 32.8% vs Ministral 3 (14B Reasoning 2512) at 64.6%. SWE-bench measures real GitHub fixes; LiveCodeBench measures contest programming.

    What is the context window for Llama 4 Scout vs Ministral 3 (14B Reasoning 2512)?

    Llama 4 Scout supports a 10M token context window, while Ministral 3 (14B Reasoning 2512) supports 262K tokens. Llama 4 Scout 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, Llama 4 Scout or Ministral 3 (14B Reasoning 2512)?

    Ministral 3 (14B Reasoning 2512) leads on 2 of 2 shared benchmarks versus Llama 4 Scout'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 Llama 4 Scout or Ministral 3 (14B Reasoning 2512) better for production use?

    Both Llama 4 Scout and Ministral 3 (14B Reasoning 2512) are production API models. For cost-sensitive production traffic, Llama 4 Scout 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 Llama 4 Scout and Ministral 3 (14B Reasoning 2512) in my app?

    Yes. Call Llama 4 Scout through Meta and Ministral 3 (14B Reasoning 2512) through Mistral AI 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 Llama 4 Scout vs Ministral 3 (14B Reasoning 2512) pricing data?

    List rates are the latest published Meta API pricing and Mistral API pricing, quoted per million tokens. Official rate sheets: https://llama.meta.com/ and https://docs.mistral.ai/platform/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 Llama 4 Scout and Ministral 3 (14B Reasoning 2512)?

    Llama 4 Scout supports up to 10M output tokens per request, while Ministral 3 (14B Reasoning 2512) supports up to 262K 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, Llama 4 Scout or Ministral 3 (14B Reasoning 2512)?

    Llama 4 Scout runs at approximately 76.1 tokens/second while Ministral 3 (14B Reasoning 2512) runs at 128.6 tokens/second. Ministral 3 (14B Reasoning 2512) 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 Llama 4 Scout vs Ministral 3 (14B Reasoning 2512) comparison?

    Use the model pickers at the top of this LLM comparison. Search any model in the index and the URL updates. Open Llama 4 Scout or Ministral 3 (14B Reasoning 2512) from the sidebar for the single-model API pricing page, or go back to the LLM pricing table to sort by cheapest blended cost.

    Llama 4 Scout vs Ministral 3 (14B Reasoning 2512) pricing

    This comparison covers API pricing, context window, throughput, and benchmark scores. Llama 4 Scout costs $0.08/M input and $0.30/M output. Ministral 3 (14B Reasoning 2512) costs $0.20/M input and $0.20/M output via Mistral AI.

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

    The index

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