Qwen3-Coder vs Step-3.5-Flash

    Comparison

    As of August 25, 2026, Qwen3-Coder is 28% cheaper per million tokens than Step-3.5-Flash. Qwen3-Coder is $0.18 / $0.18 per million input/output tokens versus Step-3.5-Flash at $0.10 / $0.40. Sources: https://bailian.console.aliyun.com/ and https://anotherwrapper.com/tools/llm-pricing

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

    Better value

    Qwen3-Coder

    Qwen

    $0.36blended / 1M

    Input

    $0.18

    Output

    $0.18

    256K ctx|Open Source
    28%
    cheaper

    Step-3.5-Flash

    StepFun

    $0.50blended / 1M

    Input

    $0.10

    Output

    $0.40

    65.5K ctx|Open Source
    Save $0.14 per million tokens by choosing Qwen3-Coder over Step-3.5-Flash.

    Qwen3-Coder vs Step-3.5-Flash comparison

    Token pricing, specs, and benchmarks side by side

    Metric
    Qwen3-Coder
    Step-3.5-Flash
    Provider
    Provider
    Qwen
    StepFun
    License
    Open Source
    Open Source
    Release Date
    2025-01-01
    2026-02-02
    Pricing (per 1M tokens)
    Input Price+80%
    $0.18
    $0.10
    Output Price-55%
    $0.18
    $0.40
    Blended (1M + 1M)
    $0.36
    $0.50
    Model Details
    Context Window
    256K
    65.5K
    Max Output Tokens
    256K
    8.2K
    Knowledge Cutoff
    N/A
    N/A
    Throughput
    N/A
    150 tok/s

    Verdict

    Qwen3-Coder vs Step-3.5-Flash: the bottom line

    Both models are closely matched on benchmarks. Qwen3-Coder has the pricing advantage, making it the better value unless Step-3.5-Flash's specific capabilities are critical to your workflow.

    Qwen3-Coder vs Step-3.5-Flash FAQ

    Which is cheaper, Qwen3-Coder or Step-3.5-Flash?

    As of August 25, 2026, Qwen3-Coder is 28% cheaper on blended LLM API pricing. Qwen3-Coder costs $0.18 per million input tokens and $0.18 per million output tokens ($0.36 blended 1M-in + 1M-out). Step-3.5-Flash costs $0.10 / $0.40 per million tokens ($0.50 blended). Sources: https://bailian.console.aliyun.com/ and https://anotherwrapper.com/tools/llm-pricing. The cheapest LLM for your app still depends on how many output tokens you generate.

    How much does Qwen3-Coder vs Step-3.5-Flash cost per million tokens?

    Qwen3-Coder Qwen API pricing is $0.18 input and $0.18 output per million tokens via Qwen. Step-3.5-Flash StepFun API pricing is $0.10 input and $0.40 output per million tokens via StepFun. Use those four numbers, not ChatGPT Plus or Claude Pro subscription prices, when you are comparing APIs.

    Which is better for coding, Qwen3-Coder or Step-3.5-Flash?

    Step-3.5-Flash has a published SWE-bench Verified score of 74.4%. Qwen3-Coder does not have that eval on this page yet.

    What is the context window for Qwen3-Coder vs Step-3.5-Flash?

    Qwen3-Coder supports a 256K token context window, while Step-3.5-Flash supports 66K tokens. Qwen3-Coder 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, Qwen3-Coder or Step-3.5-Flash?

    Shared benchmark scores for Qwen3-Coder and Step-3.5-Flash 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 Qwen3-Coder or Step-3.5-Flash better for production use?

    Both Qwen3-Coder and Step-3.5-Flash are production API models. For cost-sensitive production traffic, Qwen3-Coder 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 Qwen3-Coder and Step-3.5-Flash in my app?

    Yes. Call Qwen3-Coder through Qwen and Step-3.5-Flash through StepFun 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 Qwen3-Coder vs Step-3.5-Flash pricing data?

    List rates are the latest published Qwen API pricing and StepFun API pricing, quoted per million tokens. Official rate sheets: https://bailian.console.aliyun.com/ and https://anotherwrapper.com/tools/llm-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 Qwen3-Coder and Step-3.5-Flash?

    Qwen3-Coder supports up to 256K output tokens per request, while Step-3.5-Flash 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, Qwen3-Coder or Step-3.5-Flash?

    Step-3.5-Flash has a measured throughput of approximately 150 tokens/second. Throughput data for Qwen3-Coder 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 Qwen3-Coder vs Step-3.5-Flash comparison?

    Use the model pickers at the top of this LLM comparison. Search any model in the index and the URL updates. Open Qwen3-Coder or Step-3.5-Flash from the sidebar for the single-model API pricing page, or go back to the LLM pricing table to sort by cheapest blended cost.

    Qwen3-Coder vs Step-3.5-Flash pricing

    This comparison covers API pricing, context window, throughput, and benchmark scores. Qwen3-Coder costs $0.18/M input and $0.18/M output. Step-3.5-Flash 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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