Qwen2.5-Coder 32B Instruct vs Qwen3 VL 8B Thinking

    Comparison

    As of August 25, 2026, Qwen2.5-Coder 32B Instruct is 92% cheaper per million tokens than Qwen3 VL 8B Thinking. Qwen2.5-Coder 32B Instruct is $0.09 / $0.09 per million input/output tokens versus Qwen3 VL 8B Thinking at $0.18 / $2.09. Source: https://bailian.console.aliyun.com/

    Source: Qwen pricing (https://bailian.console.aliyun.com/)

    Better value

    Qwen2.5-Coder 32B Instruct

    Qwen

    $0.18blended / 1M

    Input

    $0.09

    Output

    $0.09

    128K ctx|Open Source
    92%
    cheaper

    Qwen3 VL 8B Thinking

    Qwen

    $2.27blended / 1M

    Input

    $0.18

    Output

    $2.09

    262.1K ctx|Open Source
    Save $2.09 per million tokens by choosing Qwen2.5-Coder 32B Instruct over Qwen3 VL 8B Thinking.

    Qwen2.5-Coder 32B Instruct vs Qwen3 VL 8B Thinking 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.

    Qwen2.5-Coder 32B InstructQwen3 VL 8B Thinking

    Score vs price

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

    Best score at each priceQwen2.5-Coder 32B InstructQwen3 VL 8B Thinking
    Metric
    Qwen2.5-Coder 32B Instruct
    Qwen3 VL 8B Thinking
    Provider
    Provider
    Qwen
    Qwen
    License
    Open Source
    Open Source
    Release Date
    2024-09-19
    2025-09-22
    Pricing (per 1M tokens)
    Input Price-50%
    $0.09
    $0.18
    Output Price-96%
    $0.09
    $2.09
    Blended (1M + 1M)
    $0.18
    $2.27
    Model Details
    Context Window
    128K
    262.1K
    Max Output Tokens
    128K
    262.1K
    Knowledge Cutoff
    N/A
    N/A
    Throughput
    42 tok/s
    N/A
    Benchmarks
    69.9%
    49.6%
    83.2%
    33.9%
    60.4%
    53%
    80.3%
    75.1%
    85.2%
    83%
    92.7%
    57.2%
    84.9%
    70.5%
    63%
    68.7%
    76.3%
    59.9%
    85.9%
    95.3%
    46.8%
    91.1%
    60.6%
    69.5%
    46.2%
    55.8%
    62.7%
    90.2%
    75.1%
    87.5%
    50.4%
    77.3%
    70.7%
    77.5%
    88.8%
    74.1%
    75.3%
    76.8%
    75.1%
    69%
    81.9%
    39.8%
    47.5%
    73.5%
    93.6%
    51.2%
    43.1%
    54.2%
    71.8%
    72.8%
    80.8%
    85.5%
    Benchmark Wins
    Qwen2.5-Coder 32B Instruct 0|3 Qwen3 VL 8B Thinking

    Verdict

    Qwen2.5-Coder 32B Instruct vs Qwen3 VL 8B Thinking: the bottom line

    Qwen2.5-Coder 32B Instruct offers significantly lower pricing, while Qwen3 VL 8B Thinking leads on benchmark performance. Your choice depends on whether cost efficiency or raw capability matters more for your use case.

    Qwen2.5-Coder 32B Instruct vs Qwen3 VL 8B Thinking FAQ

    Which is cheaper, Qwen2.5-Coder 32B Instruct or Qwen3 VL 8B Thinking?

    As of August 25, 2026, Qwen2.5-Coder 32B Instruct is 92% cheaper on blended LLM API pricing. Qwen2.5-Coder 32B Instruct costs $0.09 per million input tokens and $0.09 per million output tokens ($0.18 blended 1M-in + 1M-out). Qwen3 VL 8B Thinking costs $0.18 / $2.09 per million tokens ($2.27 blended). Sources: https://bailian.console.aliyun.com/ and https://bailian.console.aliyun.com/. The cheapest LLM for your app still depends on how many output tokens you generate.

    How much does Qwen2.5-Coder 32B Instruct vs Qwen3 VL 8B Thinking cost per million tokens?

    Qwen2.5-Coder 32B Instruct Qwen API pricing is $0.09 input and $0.09 output per million tokens via Qwen. Qwen3 VL 8B Thinking Qwen API pricing is $0.18 input and $2.09 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, Qwen2.5-Coder 32B Instruct or Qwen3 VL 8B Thinking?

    Qwen2.5-Coder 32B Instruct has a published SWE-bench Verified score of 9%. Qwen3 VL 8B Thinking does not have that eval on this page yet.

    What is the context window for Qwen2.5-Coder 32B Instruct vs Qwen3 VL 8B Thinking?

    Qwen2.5-Coder 32B Instruct supports a 128K token context window, while Qwen3 VL 8B Thinking supports 262K tokens. Qwen3 VL 8B Thinking 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, Qwen2.5-Coder 32B Instruct or Qwen3 VL 8B Thinking?

    Qwen3 VL 8B Thinking leads on 3 of 3 shared benchmarks versus Qwen2.5-Coder 32B 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 Qwen2.5-Coder 32B Instruct or Qwen3 VL 8B Thinking better for production use?

    Both Qwen2.5-Coder 32B Instruct and Qwen3 VL 8B Thinking are production API models. For cost-sensitive production traffic, Qwen2.5-Coder 32B 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 Qwen2.5-Coder 32B Instruct and Qwen3 VL 8B Thinking in my app?

    Yes. Call Qwen2.5-Coder 32B Instruct through Qwen and Qwen3 VL 8B Thinking 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 Qwen2.5-Coder 32B Instruct vs Qwen3 VL 8B Thinking pricing data?

    List rates are the latest published Qwen API pricing and Qwen API pricing, quoted per million tokens. Official rate sheets: https://bailian.console.aliyun.com/ 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 Qwen2.5-Coder 32B Instruct and Qwen3 VL 8B Thinking?

    Qwen2.5-Coder 32B Instruct supports up to 128K output tokens per request, while Qwen3 VL 8B Thinking 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, Qwen2.5-Coder 32B Instruct or Qwen3 VL 8B Thinking?

    Qwen2.5-Coder 32B Instruct has a measured throughput of approximately 42 tokens/second. Throughput data for Qwen3 VL 8B Thinking 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 Qwen2.5-Coder 32B Instruct vs Qwen3 VL 8B Thinking comparison?

    Use the model pickers at the top of this LLM comparison. Search any model in the index and the URL updates. Open Qwen2.5-Coder 32B Instruct or Qwen3 VL 8B Thinking from the sidebar for the single-model API pricing page, or go back to the LLM pricing table to sort by cheapest blended cost.

    Qwen2.5-Coder 32B Instruct vs Qwen3 VL 8B Thinking pricing

    This comparison covers API pricing, context window, throughput, and benchmark scores. Qwen2.5-Coder 32B Instruct costs $0.09/M input and $0.09/M output. Qwen3 VL 8B Thinking costs $0.18/M input and $2.09/M output.

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

    The index

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