K-EXAONE-236B-A23B vs Qwen2.5 7B Instruct

    Comparison

    As of August 25, 2026, Qwen2.5 7B Instruct is 63% cheaper per million tokens than K-EXAONE-236B-A23B. K-EXAONE-236B-A23B is $0.60 / $1.00 per million input/output tokens versus Qwen2.5 7B Instruct at $0.30 / $0.30. Sources: https://anotherwrapper.com/tools/llm-pricing and https://bailian.console.aliyun.com/

    Sources: AnotherWrapper LLM pricing (https://anotherwrapper.com/tools/llm-pricing); Qwen pricing (https://bailian.console.aliyun.com/)

    K-EXAONE-236B-A23B

    LG AI Research

    $1.60blended / 1M

    Input

    $0.60

    Output

    $1.00

    32.8K ctx|Proprietary
    63%
    cheaper
    Better value

    Qwen2.5 7B Instruct

    Qwen

    $0.60blended / 1M

    Input

    $0.30

    Output

    $0.30

    131.1K ctx|Open Source
    Save $1.00 per million tokens by choosing Qwen2.5 7B Instruct over K-EXAONE-236B-A23B.

    K-EXAONE-236B-A23B 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.

    K-EXAONE-236B-A23BQwen2.5 7B Instruct

    Score vs price

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

    Best score at each priceK-EXAONE-236B-A23BQwen2.5 7B Instruct
    Metric
    K-EXAONE-236B-A23B
    Qwen2.5 7B Instruct
    Provider
    Provider
    LG AI Research
    Qwen
    License
    Proprietary
    Open Source
    Release Date
    2025-12-31
    2024-09-19
    Pricing (per 1M tokens)
    Input Price+100%
    $0.60
    $0.30
    Output Price+233%
    $1.00
    $0.30
    Blended (1M + 1M)
    $1.60
    $0.60
    Model Details
    Context Window
    32.8K
    131.1K
    Max Output Tokens
    32.8K
    8.2K
    Knowledge Cutoff
    2025-10-01
    N/A
    Throughput
    50 tok/s
    138 tok/s
    Benchmarks
    36.4%
    71.2%
    67.3%
    85.7%
    92.8%
    72.9%
    84.8%
    75.5%
    73.3%
    91.6%
    35.9%
    79.2%
    83.8%
    56.3%
    75.4%
    87.5%
    70.4%
    73.2%
    Benchmark Wins
    K-EXAONE-236B-A23B 1|0 Qwen2.5 7B Instruct

    Verdict

    K-EXAONE-236B-A23B vs Qwen2.5 7B Instruct: the bottom line

    Qwen2.5 7B Instruct offers significantly lower pricing, while K-EXAONE-236B-A23B leads on benchmark performance. Your choice depends on whether cost efficiency or raw capability matters more for your use case.

    K-EXAONE-236B-A23B vs Qwen2.5 7B Instruct FAQ

    Which is cheaper, K-EXAONE-236B-A23B or Qwen2.5 7B Instruct?

    As of August 25, 2026, Qwen2.5 7B Instruct is 63% cheaper on blended LLM API pricing. Qwen2.5 7B Instruct costs $0.30 per million input tokens and $0.30 per million output tokens ($0.60 blended 1M-in + 1M-out). K-EXAONE-236B-A23B costs $0.60 / $1.00 per million tokens ($1.60 blended). Sources: https://anotherwrapper.com/tools/llm-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 K-EXAONE-236B-A23B vs Qwen2.5 7B Instruct cost per million tokens?

    K-EXAONE-236B-A23B LG AI Research API pricing is $0.60 input and $1.00 output per million tokens via LG AI Research. 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, K-EXAONE-236B-A23B or Qwen2.5 7B Instruct?

    Qwen2.5 7B Instruct has a published LiveCodeBench score of 28.7%. K-EXAONE-236B-A23B does not have that eval on this page yet.

    What is the context window for K-EXAONE-236B-A23B vs Qwen2.5 7B Instruct?

    K-EXAONE-236B-A23B supports a 33K 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, K-EXAONE-236B-A23B or Qwen2.5 7B Instruct?

    K-EXAONE-236B-A23B leads on 1 of 1 shared benchmarks versus Qwen2.5 7B 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 K-EXAONE-236B-A23B or Qwen2.5 7B Instruct better for production use?

    Both K-EXAONE-236B-A23B and Qwen2.5 7B Instruct are production API models. For cost-sensitive production traffic, Qwen2.5 7B 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 K-EXAONE-236B-A23B and Qwen2.5 7B Instruct in my app?

    Yes. Call K-EXAONE-236B-A23B through LG AI Research 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 K-EXAONE-236B-A23B vs Qwen2.5 7B Instruct pricing data?

    List rates are the latest published LG AI Research API pricing and Qwen API pricing, quoted per million tokens. Official rate sheets: https://anotherwrapper.com/tools/llm-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 K-EXAONE-236B-A23B and Qwen2.5 7B Instruct?

    K-EXAONE-236B-A23B supports up to 33K 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, K-EXAONE-236B-A23B or Qwen2.5 7B Instruct?

    K-EXAONE-236B-A23B runs at approximately 50 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 K-EXAONE-236B-A23B 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 K-EXAONE-236B-A23B 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.

    K-EXAONE-236B-A23B vs Qwen2.5 7B Instruct pricing

    This comparison covers API pricing, context window, throughput, and benchmark scores. K-EXAONE-236B-A23B costs $0.60/M input and $1.00/M output. 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

    0 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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