K-EXAONE-236B-A23B vs Qwen2-VL-72B-Instruct

    Comparison

    As of August 30, 2026, K-EXAONE-236B-A23B is 11% cheaper per million tokens than Qwen2-VL-72B-Instruct. K-EXAONE-236B-A23B is $0.60 / $1.00 per million input/output tokens versus Qwen2-VL-72B-Instruct at $0.80 / $1.00. Sources: https://anotherwrapper.com/tools/llm-pricing and https://openrouter.ai/qwen/qwen2.5-vl-72b-instruct

    Sources: AnotherWrapper LLM pricing (https://anotherwrapper.com/tools/llm-pricing); OpenRouter pricing (https://openrouter.ai/qwen/qwen2.5-vl-72b-instruct)

    Better value

    K-EXAONE-236B-A23B

    LG AI Research

    $1.60blended / 1M

    Input

    $0.60

    Output

    $1.00

    32.8K ctx|Proprietary
    11%
    cheaper

    Qwen2-VL-72B-Instruct

    Qwen

    $1.80blended / 1M

    Input

    $0.80

    Output

    $1.00

    131.1K ctx|Open Source
    Save $0.20 per million tokens by choosing K-EXAONE-236B-A23B over Qwen2-VL-72B-Instruct.

    K-EXAONE-236B-A23B vs Qwen2-VL-72B-Instruct comparison

    Token pricing, specs, and benchmarks side by side

    Metric
    K-EXAONE-236B-A23B
    Qwen2-VL-72B-Instruct
    Provider
    Provider
    LG AI Research
    Qwen
    License
    Proprietary
    Open Source
    Release Date
    2025-12-31
    2024-08-29
    Pricing (per 1M tokens)
    Input Price-25%
    $0.60
    $0.80
    Output Price0%
    $1.00
    $1.00
    Blended (1M + 1M)
    $1.60
    $1.80
    Model Details
    Context Window
    32.8K
    131.1K
    Max Output Tokens
    32.8K
    N/A
    Knowledge Cutoff
    2025-10-01
    2023-06-30
    Throughput
    50 tok/s
    N/A
    Benchmarks
    67.3%
    46.2%
    85.7%
    92.8%
    88.3%
    96.5%
    77.9%
    84.5%
    70.5%
    86.5%
    83.8%
    64.5%
    30.9%
    73.6%
    87.7%
    77.8%
    73.2%
    85.5%
    91.9%
    71.2%

    Verdict

    K-EXAONE-236B-A23B vs Qwen2-VL-72B-Instruct: the bottom line

    Both models are closely matched on benchmarks. K-EXAONE-236B-A23B has the pricing advantage, making it the better value unless Qwen2-VL-72B-Instruct's specific capabilities are critical to your workflow.

    K-EXAONE-236B-A23B vs Qwen2-VL-72B-Instruct FAQ

    Which is cheaper, K-EXAONE-236B-A23B or Qwen2-VL-72B-Instruct?

    As of August 30, 2026, K-EXAONE-236B-A23B is 11% cheaper on blended LLM API pricing. K-EXAONE-236B-A23B costs $0.60 per million input tokens and $1.00 per million output tokens ($1.60 blended 1M-in + 1M-out). Qwen2-VL-72B-Instruct costs $0.80 / $1.00 per million tokens ($1.80 blended). Sources: https://anotherwrapper.com/tools/llm-pricing and https://openrouter.ai/qwen/qwen2.5-vl-72b-instruct. The cheapest LLM for your app still depends on how many output tokens you generate.

    How much does K-EXAONE-236B-A23B vs Qwen2-VL-72B-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-VL-72B-Instruct OpenRouter API pricing is $0.80 input and $1.00 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, K-EXAONE-236B-A23B or Qwen2-VL-72B-Instruct?

    Neither K-EXAONE-236B-A23B nor Qwen2-VL-72B-Instruct has a published SWE-bench or LiveCodeBench score on this page yet. Use the comparison table for the evals that do exist.

    What is the context window for K-EXAONE-236B-A23B vs Qwen2-VL-72B-Instruct?

    K-EXAONE-236B-A23B supports a 33K token context window, while Qwen2-VL-72B-Instruct supports 131K tokens. Qwen2-VL-72B-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-VL-72B-Instruct?

    Shared benchmark scores for K-EXAONE-236B-A23B and Qwen2-VL-72B-Instruct are still limited. Check the comparison table for the evals each model has published. 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-VL-72B-Instruct better for production use?

    Both K-EXAONE-236B-A23B and Qwen2-VL-72B-Instruct are production API models. For cost-sensitive production traffic, K-EXAONE-236B-A23B 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-VL-72B-Instruct in my app?

    Yes. Call K-EXAONE-236B-A23B through LG AI Research and Qwen2-VL-72B-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 K-EXAONE-236B-A23B vs Qwen2-VL-72B-Instruct pricing data?

    List rates are the latest published LG AI Research API pricing and OpenRouter API pricing, quoted per million tokens. Official rate sheets: https://anotherwrapper.com/tools/llm-pricing and https://openrouter.ai/qwen/qwen2.5-vl-72b-instruct. 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-VL-72B-Instruct?

    K-EXAONE-236B-A23B supports up to 33K output tokens per request, while Qwen2-VL-72B-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, K-EXAONE-236B-A23B or Qwen2-VL-72B-Instruct?

    K-EXAONE-236B-A23B has a measured throughput of approximately 50 tokens/second. Throughput data for Qwen2-VL-72B-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 K-EXAONE-236B-A23B vs Qwen2-VL-72B-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-VL-72B-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-VL-72B-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-VL-72B-Instruct costs $0.80/M input and $1.00/M output via OpenRouter.

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

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