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

    Comparison

    As of August 30, 2026, Qwen2.5-Omni-7B is 69% 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-Omni-7B at $0.10 / $0.40. Sources: https://anotherwrapper.com/tools/llm-pricing and https://www.alibabacloud.com/help/en/model-studio/pricing

    Sources: AnotherWrapper LLM pricing (https://anotherwrapper.com/tools/llm-pricing); Qwen pricing (https://www.alibabacloud.com/help/en/model-studio/pricing)

    K-EXAONE-236B-A23B

    LG AI Research

    $1.60blended / 1M

    Input

    $0.60

    Output

    $1.00

    32.8K ctx|Proprietary
    69%
    cheaper
    Better value

    Qwen2.5-Omni-7B

    Qwen

    $0.50blended / 1M

    Input

    $0.10

    Output

    $0.40

    32.8K ctx|Open Source
    Save $1.10 per million tokens by choosing Qwen2.5-Omni-7B over K-EXAONE-236B-A23B.

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

    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-Omni-7B
    Metric
    K-EXAONE-236B-A23B
    Qwen2.5-Omni-7B
    Provider
    Provider
    LG AI Research
    Qwen
    License
    Proprietary
    Open Source
    Release Date
    2025-12-31
    2025-03-27
    Pricing (per 1M tokens)
    Input Price+500%
    $0.60
    $0.10
    Output Price+150%
    $1.00
    $0.40
    Blended (1M + 1M)
    $1.60
    $0.50
    Model Details
    Context Window
    32.8K
    32.8K
    Max Output Tokens
    32.8K
    N/A
    Knowledge Cutoff
    2025-10-01
    N/A
    Throughput
    50 tok/s
    N/A
    Benchmarks
    30.8%
    67.3%
    36.6%
    85.7%
    92.8%
    59.2%
    78.7%
    71.5%
    83.2%
    85.3%
    76.5%
    95.2%
    68.6%
    95.9%
    88.7%
    29.6%
    67.9%
    73.2%
    57%
    65.6%
    69.2%
    67.9%
    59.8%
    81.8%
    83.8%
    47%
    64%
    59.2%
    65.8%
    32.8%
    70.3%
    4.5%
    57.8%
    42.4%
    56.1%
    70.3%
    73.2%
    84.4%
    93.9%
    Benchmark Wins
    K-EXAONE-236B-A23B 1|0 Qwen2.5-Omni-7B

    Verdict

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

    Qwen2.5-Omni-7B 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-Omni-7B FAQ

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

    As of August 30, 2026, Qwen2.5-Omni-7B is 69% cheaper on blended LLM API pricing. Qwen2.5-Omni-7B costs $0.10 per million input tokens and $0.40 per million output tokens ($0.50 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://www.alibabacloud.com/help/en/model-studio/pricing. 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-Omni-7B 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-Omni-7B Qwen API pricing is $0.10 input and $0.40 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-Omni-7B?

    Qwen2.5-Omni-7B has a published HumanEval score of 78.7%. 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-Omni-7B?

    K-EXAONE-236B-A23B supports a 33K token context window, while Qwen2.5-Omni-7B supports 33K tokens. Both models have the same context window size. 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-Omni-7B?

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

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

    Yes. Call K-EXAONE-236B-A23B through LG AI Research and Qwen2.5-Omni-7B 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-Omni-7B 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://www.alibabacloud.com/help/en/model-studio/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 K-EXAONE-236B-A23B and Qwen2.5-Omni-7B?

    K-EXAONE-236B-A23B supports up to 33K output tokens per request, while Qwen2.5-Omni-7B 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, K-EXAONE-236B-A23B or Qwen2.5-Omni-7B?

    K-EXAONE-236B-A23B has a measured throughput of approximately 50 tokens/second. Throughput data for Qwen2.5-Omni-7B 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 K-EXAONE-236B-A23B vs Qwen2.5-Omni-7B 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-Omni-7B 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-Omni-7B 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-Omni-7B costs $0.10/M input and $0.40/M output.

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

    The index

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