Inkling-Small vs Qwen3 VL 4B Thinking

    Comparison

    As of August 20, 2026, Qwen3 VL 4B Thinking is 27% cheaper per million tokens than Inkling-Small. Inkling-Small is $0.30 / $1.20 per million input/output tokens versus Qwen3 VL 4B Thinking at $0.10 / $1.00. Sources: https://thinkingmachines.ai and https://bailian.console.aliyun.com/

    Sources: Thinking Machines Lab pricing (https://thinkingmachines.ai); Qwen pricing (https://bailian.console.aliyun.com/)

    Inkling-Small

    Thinking Machines

    $1.50blended / 1M

    Input

    $0.30

    Output

    $1.20

    256K ctx|Open Source
    27%
    cheaper
    Better value

    Qwen3 VL 4B Thinking

    Qwen

    $1.10blended / 1M

    Input

    $0.10

    Output

    $1.00

    262.1K ctx|Open Source
    Save $0.40 per million tokens by choosing Qwen3 VL 4B Thinking over Inkling-Small.

    Inkling-Small vs Qwen3 VL 4B Thinking comparison

    Token pricing, specs, and benchmarks side by side

    Metric
    Inkling-Small
    Qwen3 VL 4B Thinking
    Provider
    Provider
    Thinking Machines
    Qwen
    License
    Open Source
    Open Source
    Release Date
    2026-07-30
    2025-09-22
    Pricing (per 1M tokens)
    Input Price+200%
    $0.30
    $0.10
    Output Price+20%
    $1.20
    $1.00
    Blended (1M + 1M)
    $1.50
    $1.10
    Model Details
    Context Window
    256K
    262.1K
    Max Output Tokens
    256K
    262.1K
    Knowledge Cutoff
    N/A
    N/A
    Throughput
    N/A
    N/A
    Benchmarks
    31.6%
    89.5%
    64.1%
    88.5%
    48.7%
    77.4%
    19.5%
    82.6%
    82.2%
    40.1%
    31.4%
    54.4%
    79.6%
    74%
    57%
    77.4%
    50.3%
    90%
    74.5%
    81.5%
    30.6%
    84.9%
    95.5%
    84%
    67.3%
    63.4%
    73.8%
    83.9%
    69.6%
    8.3%
    68.8%
    94.2%
    31.8%
    47.3%
    42.3%
    53.1%
    64.6%
    53.5%
    37.9%
    84.1%
    75.7%
    77%
    86.7%
    85.6%
    73.6%
    65%
    70.8%
    73.2%
    75%
    73.6%
    69.3%
    80.8%
    39.4%
    44.6%
    73.2%
    32.7%
    92.9%
    33.6%
    46.8%
    15.5%
    75.5%
    69.4%
    Benchmark Wins
    Inkling-Small 5|0 Qwen3 VL 4B Thinking

    Verdict

    Inkling-Small vs Qwen3 VL 4B Thinking: the bottom line

    Qwen3 VL 4B Thinking offers significantly lower pricing, while Inkling-Small leads on benchmark performance. Your choice depends on whether cost efficiency or raw capability matters more for your use case.

    Inkling-Small vs Qwen3 VL 4B Thinking FAQ

    Which is cheaper, Inkling-Small or Qwen3 VL 4B Thinking?

    As of August 20, 2026, Qwen3 VL 4B Thinking is 27% cheaper on blended LLM API pricing. Qwen3 VL 4B Thinking costs $0.10 per million input tokens and $1.00 per million output tokens ($1.10 blended 1M-in + 1M-out). Inkling-Small costs $0.30 / $1.20 per million tokens ($1.50 blended). Sources: https://thinkingmachines.ai and https://bailian.console.aliyun.com/. The cheapest LLM for your app still depends on how many output tokens you generate.

    How much does Inkling-Small vs Qwen3 VL 4B Thinking cost per million tokens?

    Inkling-Small Thinking Machines Lab API pricing is $0.30 input and $1.20 output per million tokens via Thinking Machines Lab. Qwen3 VL 4B Thinking Qwen API pricing is $0.10 input and $1.00 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, Inkling-Small or Qwen3 VL 4B Thinking?

    Inkling-Small has a published SWE-bench Verified score of 80.2%. Qwen3 VL 4B Thinking does not have that eval on this page yet.

    What is the context window for Inkling-Small vs Qwen3 VL 4B Thinking?

    Inkling-Small supports a 256K token context window, while Qwen3 VL 4B Thinking supports 262K tokens. Qwen3 VL 4B 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, Inkling-Small or Qwen3 VL 4B Thinking?

    Inkling-Small leads on 5 of 5 shared benchmarks versus Qwen3 VL 4B Thinking'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 Inkling-Small or Qwen3 VL 4B Thinking better for production use?

    Both Inkling-Small and Qwen3 VL 4B Thinking are production API models. For cost-sensitive production traffic, Qwen3 VL 4B Thinking 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 Inkling-Small and Qwen3 VL 4B Thinking in my app?

    Yes. Call Inkling-Small through Thinking Machines Lab and Qwen3 VL 4B 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 Inkling-Small vs Qwen3 VL 4B Thinking pricing data?

    List rates are the latest published Thinking Machines Lab API pricing and Qwen API pricing, quoted per million tokens. Official rate sheets: https://thinkingmachines.ai 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 Inkling-Small and Qwen3 VL 4B Thinking?

    Inkling-Small supports up to 256K output tokens per request, while Qwen3 VL 4B 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, Inkling-Small or Qwen3 VL 4B Thinking?

    Neither Inkling-Small nor Qwen3 VL 4B Thinking has published throughput data on this page yet. 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 Inkling-Small vs Qwen3 VL 4B Thinking comparison?

    Use the model pickers at the top of this LLM comparison. Search any model in the index and the URL updates. Open Inkling-Small or Qwen3 VL 4B 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.

    Inkling-Small vs Qwen3 VL 4B Thinking pricing

    This comparison covers API pricing, context window, throughput, and benchmark scores. Inkling-Small costs $0.30/M input and $1.20/M output via Thinking Machines Lab. Qwen3 VL 4B Thinking costs $0.10/M input and $1.00/M output.

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

    The index

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