Gemini 1.0 Pro vs Qwen3-Coder

    Comparison

    As of August 20, 2026, Qwen3-Coder is 82% cheaper per million tokens than Gemini 1.0 Pro. Gemini 1.0 Pro is $0.50 / $1.50 per million input/output tokens versus Qwen3-Coder at $0.18 / $0.18. Sources: https://ai.google.dev/gemini-api/docs/pricing and https://bailian.console.aliyun.com/

    Sources: Gemini API pricing (https://ai.google.dev/gemini-api/docs/pricing); Qwen pricing (https://bailian.console.aliyun.com/)

    Gemini 1.0 Pro

    Google

    $2.00blended / 1M

    Input

    $0.50

    Output

    $1.50

    32.8K ctx|Proprietary
    82%
    cheaper
    Better value

    Qwen3-Coder

    Qwen

    $0.36blended / 1M

    Input

    $0.18

    Output

    $0.18

    256K ctx|Open Source
    Save $1.64 per million tokens by choosing Qwen3-Coder over Gemini 1.0 Pro.

    Gemini 1.0 Pro vs Qwen3-Coder comparison

    Token pricing, specs, and benchmarks side by side

    Metric
    Gemini 1.0 Pro
    Qwen3-Coder
    Provider
    Provider
    Google
    Qwen
    License
    Proprietary
    Open Source
    Release Date
    2024-02-15
    2025-01-01
    Pricing (per 1M tokens)
    Input Price+178%
    $0.50
    $0.18
    Output Price+733%
    $1.50
    $0.18
    Blended (1M + 1M)
    $2.00
    $0.36
    Model Details
    Context Window
    32.8K
    256K
    Max Output Tokens
    8.2K
    256K
    Knowledge Cutoff
    2024-02-01
    N/A
    Throughput
    120 tok/s
    N/A
    Benchmarks
    27.9%
    71.8%
    47.9%
    32.6%
    75%
    55.7%
    93.6%
    46.6%
    79.7%
    71.7%

    Verdict

    Gemini 1.0 Pro vs Qwen3-Coder: the bottom line

    Both models are closely matched on benchmarks. Qwen3-Coder has the pricing advantage, making it the better value unless Gemini 1.0 Pro's specific capabilities are critical to your workflow.

    Gemini 1.0 Pro vs Qwen3-Coder FAQ

    Which is cheaper, Gemini 1.0 Pro or Qwen3-Coder?

    As of August 20, 2026, Qwen3-Coder is 82% 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). Gemini 1.0 Pro costs $0.50 / $1.50 per million tokens ($2.00 blended). Sources: https://ai.google.dev/gemini-api/docs/pricing and https://bailian.console.aliyun.com/. The cheapest LLM for your app still depends on how many output tokens you generate.

    How much does Gemini 1.0 Pro vs Qwen3-Coder cost per million tokens?

    Gemini 1.0 Pro Gemini API pricing is $0.50 input and $1.50 output per million tokens via Google. Qwen3-Coder Qwen API pricing is $0.18 input and $0.18 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, Gemini 1.0 Pro or Qwen3-Coder?

    Neither Gemini 1.0 Pro nor Qwen3-Coder 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 Gemini 1.0 Pro vs Qwen3-Coder?

    Gemini 1.0 Pro supports a 33K token context window, while Qwen3-Coder supports 256K 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, Gemini 1.0 Pro or Qwen3-Coder?

    Shared benchmark scores for Gemini 1.0 Pro and Qwen3-Coder 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 Gemini 1.0 Pro or Qwen3-Coder better for production use?

    Both Gemini 1.0 Pro and Qwen3-Coder 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 Gemini 1.0 Pro and Qwen3-Coder in my app?

    Yes. Call Gemini 1.0 Pro through Google and Qwen3-Coder 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 Gemini 1.0 Pro vs Qwen3-Coder pricing data?

    List rates are the latest published Gemini API pricing and Qwen API pricing, quoted per million tokens. Official rate sheets: https://ai.google.dev/gemini-api/docs/pricing 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 Gemini 1.0 Pro and Qwen3-Coder?

    Gemini 1.0 Pro supports up to 8K output tokens per request, while Qwen3-Coder supports up to 256K 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, Gemini 1.0 Pro or Qwen3-Coder?

    Gemini 1.0 Pro has a measured throughput of approximately 120 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 Gemini 1.0 Pro vs Qwen3-Coder comparison?

    Use the model pickers at the top of this LLM comparison. Search any model in the index and the URL updates. Open Gemini 1.0 Pro or Qwen3-Coder from the sidebar for the single-model API pricing page, or go back to the LLM pricing table to sort by cheapest blended cost.

    Gemini 1.0 Pro vs Qwen3-Coder pricing

    This comparison covers API pricing, context window, throughput, and benchmark scores. Gemini 1.0 Pro costs $0.50/M input and $1.50/M output. Qwen3-Coder costs $0.18/M input and $0.18/M output.

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

    The index

    All Large Language Models

    280 models across 33 providers. Search or jump to a lab — every model page stays linked here.

    Baidu

    1 models

    Inception

    1 models

    inclusionAI

    1 models

    LG AI Research

    1 models

    Nous Research

    1 models

    Sakana AI

    1 models

    StepFun

    1 models

    Tencent

    1 models

    Thinking Machines

    1 models

    Unisound

    1 models

    Upstage

    1 models

    Next step

    You found the model. Now ship the product.

    Auth, billing, and the API layer are already decided. Fork 8 finished AI apps, or have us build the first version with you.