Mistral Medium 3.5 vs Qwen3.5-122B-A10B

    Comparison

    As of August 25, 2026, Qwen3.5-122B-A10B is 60% cheaper per million tokens than Mistral Medium 3.5. Mistral Medium 3.5 is $1.50 / $7.50 per million input/output tokens versus Qwen3.5-122B-A10B at $0.40 / $3.20. Sources: https://docs.mistral.ai/platform/pricing/ and https://bailian.console.aliyun.com/

    Sources: Mistral AI pricing (https://docs.mistral.ai/platform/pricing/); Qwen pricing (https://bailian.console.aliyun.com/)

    Mistral Medium 3.5

    Mistral

    $9.00blended / 1M

    Input

    $1.50

    Output

    $7.50

    256K ctx|Open Source
    60%
    cheaper
    Better value

    Qwen3.5-122B-A10B

    Qwen

    $3.60blended / 1M

    Input

    $0.40

    Output

    $3.20

    262.1K ctx|Open Source
    Save $5.40 per million tokens by choosing Qwen3.5-122B-A10B over Mistral Medium 3.5.

    Mistral Medium 3.5 vs Qwen3.5-122B-A10B 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.

    Score vs price

    SWE-bench Verified. Left is cheaper. Up is a higher score. The line is the best score you can buy at each price.

    Best score at each priceMistral Medium 3.5Qwen3.5-122B-A10B
    Metric
    Mistral Medium 3.5
    Qwen3.5-122B-A10B
    Provider
    Provider
    Mistral
    Qwen
    License
    Open Source
    Open Source
    Release Date
    2026-04-29
    2026-02-24
    Pricing (per 1M tokens)
    Input Price+275%
    $1.50
    $0.40
    Output Price+134%
    $7.50
    $3.20
    Blended (1M + 1M)
    $9.00
    $3.60
    Model Details
    Context Window
    256K
    262.1K
    Max Output Tokens
    256K
    64K
    Knowledge Cutoff
    N/A
    N/A
    Throughput
    1 tok/s
    N/A
    Benchmarks
    47.5%
    86.6%
    34.9%
    39.6%
    48.6%
    63.8%
    93.4%
    69%
    76.1%
    66.9%
    76.9%
    86.7%
    77.2%
    86.3%
    83.9%
    93.3%
    40.2%
    66.9%
    72.2%
    91.9%
    81.8%
    85.1%
    95.8%
    58.8%
    0%
    85.9%
    11.2%
    62%
    88.4%
    91.4%
    90.3%
    12.7%
    82.8%
    80.8%
    60.2%
    74.4%
    86.2%
    87.9%
    33.8%
    67.7%
    67.3%
    87.3%
    92.8%
    75.3%
    86.7%
    82.2%
    82.9%
    74.7%
    76.6%
    58.6%
    15.4%
    92.1%
    44.5%
    39.5%
    63.3%
    68.9%
    85.1%
    91.3%
    37.6%
    44.1%
    61.7%
    81.6%
    36.2%
    67.1%
    79.5%
    13.4%
    76.1%
    91.4%
    68.0%
    53.2%
    93.2%
    82%
    33.6%
    96.7%
    60.5%
    78.3%
    Benchmark Wins
    Mistral Medium 3.5 1|5 Qwen3.5-122B-A10B

    Verdict

    Mistral Medium 3.5 vs Qwen3.5-122B-A10B: the bottom line

    Qwen3.5-122B-A10B offers both lower pricing and stronger benchmark performance across the board, making it the clear value leader in this comparison.

    Mistral Medium 3.5 vs Qwen3.5-122B-A10B FAQ

    Which is cheaper, Mistral Medium 3.5 or Qwen3.5-122B-A10B?

    As of August 25, 2026, Qwen3.5-122B-A10B is 60% cheaper on blended LLM API pricing. Qwen3.5-122B-A10B costs $0.40 per million input tokens and $3.20 per million output tokens ($3.60 blended 1M-in + 1M-out). Mistral Medium 3.5 costs $1.50 / $7.50 per million tokens ($9.00 blended). Sources: https://docs.mistral.ai/platform/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 Mistral Medium 3.5 vs Qwen3.5-122B-A10B cost per million tokens?

    Mistral Medium 3.5 Mistral API pricing is $1.50 input and $7.50 output per million tokens via Mistral AI. Qwen3.5-122B-A10B Qwen API pricing is $0.40 input and $3.20 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, Mistral Medium 3.5 or Qwen3.5-122B-A10B?

    Mistral Medium 3.5 leads on SWE-bench Verified: Mistral Medium 3.5 at 77.6% vs Qwen3.5-122B-A10B at 72%. SWE-bench measures real GitHub fixes; LiveCodeBench measures contest programming.

    What is the context window for Mistral Medium 3.5 vs Qwen3.5-122B-A10B?

    Mistral Medium 3.5 supports a 256K token context window, while Qwen3.5-122B-A10B supports 262K tokens. Qwen3.5-122B-A10B 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, Mistral Medium 3.5 or Qwen3.5-122B-A10B?

    Qwen3.5-122B-A10B leads on 5 of 6 shared benchmarks versus Mistral Medium 3.5's 1 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 Mistral Medium 3.5 or Qwen3.5-122B-A10B better for production use?

    Both Mistral Medium 3.5 and Qwen3.5-122B-A10B are production API models. For cost-sensitive production traffic, Qwen3.5-122B-A10B 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 Mistral Medium 3.5 and Qwen3.5-122B-A10B in my app?

    Yes. Call Mistral Medium 3.5 through Mistral AI and Qwen3.5-122B-A10B 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 Mistral Medium 3.5 vs Qwen3.5-122B-A10B pricing data?

    List rates are the latest published Mistral API pricing and Qwen API pricing, quoted per million tokens. Official rate sheets: https://docs.mistral.ai/platform/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 Mistral Medium 3.5 and Qwen3.5-122B-A10B?

    Mistral Medium 3.5 supports up to 256K output tokens per request, while Qwen3.5-122B-A10B supports up to 64K 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, Mistral Medium 3.5 or Qwen3.5-122B-A10B?

    Mistral Medium 3.5 has a measured throughput of approximately 1 tokens/second. Throughput data for Qwen3.5-122B-A10B 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 Mistral Medium 3.5 vs Qwen3.5-122B-A10B comparison?

    Use the model pickers at the top of this LLM comparison. Search any model in the index and the URL updates. Open Mistral Medium 3.5 or Qwen3.5-122B-A10B from the sidebar for the single-model API pricing page, or go back to the LLM pricing table to sort by cheapest blended cost.

    Mistral Medium 3.5 vs Qwen3.5-122B-A10B pricing

    This comparison covers API pricing, context window, throughput, and benchmark scores. Mistral Medium 3.5 costs $1.50/M input and $7.50/M output via Mistral AI. Qwen3.5-122B-A10B costs $0.40/M input and $3.20/M output.

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

    The index

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