As of August 20, 2026, o4-mini is 31% cheaper per million tokens than Qwen3.8 Max. o4-mini is $1.10 / $4.40 per million input/output tokens versus Qwen3.8 Max at $2.00 / $6.00. Sources: https://developers.openai.com/api/docs/pricing and https://www.alibabacloud.com/help/en/model-studio/pricing
Sources: OpenAI API pricing (https://developers.openai.com/api/docs/pricing); Qwen pricing (https://www.alibabacloud.com/help/en/model-studio/pricing)
o4-mini
OpenAI
Input
$1.10
Output
$4.40
Qwen3.8 Max
Qwen
Input
$2.00
Output
$6.00
Token pricing, specs, and benchmarks side by side
o4-miniQwen3.8 MaxVerdict
o4-mini offers significantly lower pricing, while Qwen3.8 Max leads on benchmark performance. Your choice depends on whether cost efficiency or raw capability matters more for your use case.
As of August 20, 2026, o4-mini is 31% cheaper on blended LLM API pricing. o4-mini costs $1.10 per million input tokens and $4.40 per million output tokens ($5.50 blended 1M-in + 1M-out). Qwen3.8 Max costs $2.00 / $6.00 per million tokens ($8.00 blended). Sources: https://developers.openai.com/api/docs/pricing and https://www.alibabacloud.com/help/en/model-studio/pricing. The cheapest LLM for your app still depends on how many output tokens you generate.
o4-mini OpenAI API pricing is $1.10 input and $4.40 output per million tokens via OpenAI. Qwen3.8 Max Qwen API pricing is $2.00 input and $6.00 output per million tokens via Qwen. Use those four numbers, not ChatGPT Plus or Claude Pro subscription prices, when you are comparing APIs.
Qwen3.8 Max leads on SWE-bench Verified: o4-mini at 68.1% vs Qwen3.8 Max at 85.6%. SWE-bench measures real GitHub fixes; LiveCodeBench measures contest programming.
o4-mini supports a 200K token context window, while Qwen3.8 Max supports 1M tokens. Qwen3.8 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.
Qwen3.8 Max leads on 15 of 15 shared benchmarks versus o4-mini'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.
Both o4-mini and Qwen3.8 Max are production API models. For cost-sensitive production traffic, o4-mini 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 o4-mini through OpenAI and Qwen3.8 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 OpenAI API pricing and Qwen API pricing, quoted per million tokens. Official rate sheets: https://developers.openai.com/api/docs/pricing and https://www.alibabacloud.com/help/en/model-studio/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.
o4-mini supports up to 100K output tokens per request, while Qwen3.8 Max supports up to an unspecified number of output tokens. Output tokens are usually the expensive half of API pricing, so a higher max output cap is a capability, not a discount.
o4-mini has a measured throughput of approximately 115 tokens/second. Throughput data for Qwen3.8 Max 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.
Use the model pickers at the top of this LLM comparison. Search any model in the index and the URL updates. Open o4-mini or Qwen3.8 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. o4-mini costs $1.10/M input and $4.40/M output. Qwen3.8 Max costs $2.00/M input and $6.00/M output.
Rank both on the LLM leaderboard, SWE-bench, and Humanity's Last Exam.
The index
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