Mistral Small 3.1 24B Base vs Qwen2.5 7B Instruct

    Comparison

    As of August 25, 2026, Mistral Small 3.1 24B Base is 33% cheaper per million tokens than Qwen2.5 7B Instruct. Mistral Small 3.1 24B Base is $0.10 / $0.30 per million input/output tokens versus Qwen2.5 7B Instruct at $0.30 / $0.30. Sources: https://docs.mistral.ai/platform/pricing/ and https://bailian.console.aliyun.com/

    Sources: Mistral AI pricing (https://docs.mistral.ai/platform/pricing/); Qwen pricing (https://bailian.console.aliyun.com/)

    Better value

    Mistral Small 3.1 24B Base

    Mistral

    $0.40blended / 1M

    Input

    $0.10

    Output

    $0.30

    128K ctx|Open Source
    33%
    cheaper

    Qwen2.5 7B Instruct

    Qwen

    $0.60blended / 1M

    Input

    $0.30

    Output

    $0.30

    131.1K ctx|Open Source
    Save $0.20 per million tokens by choosing Mistral Small 3.1 24B Base over Qwen2.5 7B Instruct.

    Mistral Small 3.1 24B Base vs Qwen2.5 7B Instruct 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.

    Mistral Small 3.1 24B BaseQwen2.5 7B Instruct

    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 priceMistral Small 3.1 24B BaseQwen2.5 7B Instruct
    Metric
    Mistral Small 3.1 24B Base
    Qwen2.5 7B Instruct
    Provider
    Provider
    Mistral
    Qwen
    License
    Open Source
    Open Source
    Release Date
    2025-03-17
    2024-09-19
    Pricing (per 1M tokens)
    Input Price-67%
    $0.10
    $0.30
    Output Price0%
    $0.30
    $0.30
    Blended (1M + 1M)
    $0.40
    $0.60
    Model Details
    Context Window
    128K
    131.1K
    Max Output Tokens
    128K
    8.2K
    Knowledge Cutoff
    N/A
    N/A
    Throughput
    137.1 tok/s
    138 tok/s
    Benchmarks
    37.5%
    36.4%
    71.2%
    81.0%
    72.9%
    59.3%
    84.8%
    75.5%
    73.3%
    91.6%
    35.9%
    79.2%
    56.0%
    56.3%
    75.4%
    87.5%
    70.4%
    80.5%
    Benchmark Wins
    Mistral Small 3.1 24B Base 2|1 Qwen2.5 7B Instruct

    Verdict

    Mistral Small 3.1 24B Base vs Qwen2.5 7B Instruct: the bottom line

    Mistral Small 3.1 24B Base offers both lower pricing and stronger benchmark performance across the board, making it the clear value leader in this comparison.

    Mistral Small 3.1 24B Base vs Qwen2.5 7B Instruct FAQ

    Which is cheaper, Mistral Small 3.1 24B Base or Qwen2.5 7B Instruct?

    As of August 25, 2026, Mistral Small 3.1 24B Base is 33% cheaper on blended LLM API pricing. Mistral Small 3.1 24B Base costs $0.10 per million input tokens and $0.30 per million output tokens ($0.40 blended 1M-in + 1M-out). Qwen2.5 7B Instruct costs $0.30 / $0.30 per million tokens ($0.60 blended). Sources: https://docs.mistral.ai/platform/pricing/ and https://bailian.console.aliyun.com/. The cheapest LLM for your app still depends on how many output tokens you generate.

    How much does Mistral Small 3.1 24B Base vs Qwen2.5 7B Instruct cost per million tokens?

    Mistral Small 3.1 24B Base Mistral API pricing is $0.10 input and $0.30 output per million tokens via Mistral AI. Qwen2.5 7B Instruct Qwen API pricing is $0.30 input and $0.30 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, Mistral Small 3.1 24B Base or Qwen2.5 7B Instruct?

    Qwen2.5 7B Instruct has a published LiveCodeBench score of 28.7%. Mistral Small 3.1 24B Base does not have that eval on this page yet.

    What is the context window for Mistral Small 3.1 24B Base vs Qwen2.5 7B Instruct?

    Mistral Small 3.1 24B Base supports a 128K token context window, while Qwen2.5 7B Instruct supports 131K tokens. Qwen2.5 7B Instruct 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, Mistral Small 3.1 24B Base or Qwen2.5 7B Instruct?

    Mistral Small 3.1 24B Base leads on 2 of 3 shared benchmarks versus Qwen2.5 7B Instruct'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 Mistral Small 3.1 24B Base or Qwen2.5 7B Instruct better for production use?

    Both Mistral Small 3.1 24B Base and Qwen2.5 7B Instruct are production API models. For cost-sensitive production traffic, Mistral Small 3.1 24B Base 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 Mistral Small 3.1 24B Base and Qwen2.5 7B Instruct in my app?

    Yes. Call Mistral Small 3.1 24B Base through Mistral AI and Qwen2.5 7B Instruct 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 Mistral Small 3.1 24B Base vs Qwen2.5 7B Instruct pricing data?

    List rates are the latest published Mistral API pricing and Qwen API pricing, quoted per million tokens. Official rate sheets: https://docs.mistral.ai/platform/pricing/ and https://bailian.console.aliyun.com/. 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 Mistral Small 3.1 24B Base and Qwen2.5 7B Instruct?

    Mistral Small 3.1 24B Base supports up to 128K output tokens per request, while Qwen2.5 7B Instruct supports up to 8K 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, Mistral Small 3.1 24B Base or Qwen2.5 7B Instruct?

    Mistral Small 3.1 24B Base runs at approximately 137.1 tokens/second while Qwen2.5 7B Instruct runs at 138 tokens/second. Qwen2.5 7B Instruct 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 Mistral Small 3.1 24B Base vs Qwen2.5 7B Instruct comparison?

    Use the model pickers at the top of this LLM comparison. Search any model in the index and the URL updates. Open Mistral Small 3.1 24B Base or Qwen2.5 7B 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.

    Mistral Small 3.1 24B Base vs Qwen2.5 7B Instruct pricing

    This comparison covers API pricing, context window, throughput, and benchmark scores. Mistral Small 3.1 24B Base costs $0.10/M input and $0.30/M output via Mistral AI. Qwen2.5 7B Instruct costs $0.30/M input and $0.30/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

    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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