As of August 25, 2026, Qwen3.7 Max is 38% cheaper per million tokens than Pixtral Large. Pixtral Large is $2.00 / $6.00 per million input/output tokens versus Qwen3.7 Max at $1.25 / $3.75. 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/)
Pixtral Large
Mistral
Input
$2.00
Output
$6.00
Qwen3.7 Max
Qwen
Input
$1.25
Output
$3.75
Token pricing, specs, and benchmarks side by side
Pixtral LargeQwen3.7 MaxVerdict
Both models are closely matched on benchmarks. Qwen3.7 Max has the pricing advantage, making it the better value unless Pixtral Large's specific capabilities are critical to your workflow.
As of August 25, 2026, Qwen3.7 Max is 38% cheaper on blended LLM API pricing. Qwen3.7 Max costs $1.25 per million input tokens and $3.75 per million output tokens ($5.00 blended 1M-in + 1M-out). Pixtral Large costs $2.00 / $6.00 per million tokens ($8.00 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.
Pixtral Large Mistral API pricing is $2.00 input and $6.00 output per million tokens via Mistral AI. Qwen3.7 Max Qwen API pricing is $1.25 input and $3.75 output per million tokens via Qwen. Use those four numbers, not ChatGPT Plus or Claude Pro subscription prices, when you are comparing APIs.
Qwen3.7 Max has a published SWE-bench Verified score of 80.4%. Pixtral Large does not have that eval on this page yet.
Pixtral Large supports a 128K token context window, while Qwen3.7 Max supports 1M tokens. Qwen3.7 Max 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.
Shared benchmark scores for Pixtral Large and Qwen3.7 Max 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.
Both Pixtral Large and Qwen3.7 Max are production API models. For cost-sensitive production traffic, Qwen3.7 Max 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.
Yes. Call Pixtral Large through Mistral AI and Qwen3.7 Max 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.
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.
Pixtral Large supports up to 128K output tokens per request, while Qwen3.7 Max supports up to 66K output tokens. Output tokens are usually the expensive half of API pricing, so a higher max output cap is a capability, not a discount.
Pixtral Large runs at approximately 0.1 tokens/second while Qwen3.7 Max runs at 5.7 tokens/second. Qwen3.7 Max is faster in raw throughput. 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.
Use the model pickers at the top of this LLM comparison. Search any model in the index and the URL updates. Open Pixtral Large or Qwen3.7 Max from the sidebar for the single-model API pricing page, or go back to the LLM pricing table to sort by cheapest blended cost.
This comparison covers API pricing, context window, throughput, and benchmark scores. Pixtral Large costs $2.00/M input and $6.00/M output via Mistral AI. Qwen3.7 Max costs $1.25/M input and $3.75/M output.
Rank both on the LLM leaderboard, SWE-bench, and Humanity's Last Exam.
The index
280 models across 33 providers. Search or jump to a lab — every model page stays linked here.
Next step
Auth, billing, and the API layer are already decided. Fork 8 finished AI apps, or have us build the first version with you.
