OPENAI VS ALIBABA
GPT-5.6 Sol vs Qwen3 Max
Qwen3 Max is about 4.7x cheaper than GPT-5.6 Sol on a blended 3:1 input:output rate — the same 10K-in/2K-out request costs $0.024 vs $0.11. GPT-5.6 Sol has the larger context window (1,047,576 vs 252,000 tokens).
Pricing verified
API pricing per 1M tokens
| Model | Input / 1M tokens | Output / 1M tokens | Blended (3:1 mix) |
|---|---|---|---|
| GPT-5.6 Sol | $5.00 | $30.00 | $11.25 |
| Qwen3 Max | $1.20 | $6.00 | $2.40 |
Rates from official OpenAI pricing and official Alibaba pricing, checked 2026-08-11.
What a real workload costs
Example: one request with 10,000 input tokens and 2,000 output tokens, then that request at 100,000 runs per month.
| Model | Per request (10K in / 2K out) | Per month (100K requests) | Monthly delta |
|---|---|---|---|
| GPT-5.6 Sol | $0.11 | $11,000 | +$8,600 |
| Qwen3 Max | $0.024 | $2,400 | — |
Model your own prompt sizes and volumes in the token cost analyzer, or check caching savings with the prompt caching calculator.
Specs side by side
| Spec | GPT-5.6 Sol | Qwen3 Max |
|---|---|---|
| Provider | OpenAI | Alibaba |
| Context window | 1,047,576 tokens | 252,000 tokens |
| Model class | General text | Reasoning |
| Tokenizer | o200k_base (exact, public) | qwen (exact, public) |
Count tokens for each model on its own page: GPT-5.6 Sol token counter and Qwen3 Max token counter. All OpenAI models are on the OpenAI Token Counter. All Alibaba models are on the Qwen Token Counter.
FAQ
GPT-5.6 Sol vs Qwen3 Max FAQ
Which is cheaper, GPT-5.6 Sol or Qwen3 Max?
Qwen3 Max is cheaper. At rates checked 2026-08-11, GPT-5.6 Sol costs $5.00 input / $30.00 output per 1M tokens, while Qwen3 Max costs $1.20 input / $6.00 output — about a 4.7x difference on a typical 3:1 input-heavy workload.
How much does a real request cost on GPT-5.6 Sol vs Qwen3 Max?
A request with 10,000 input tokens and 2,000 output tokens costs about $0.11 on GPT-5.6 Sol and $0.024 on Qwen3 Max. At 100,000 such requests per month that is $11,000 vs $2,400 — a difference of $8,600 per month.
Which has the bigger context window, GPT-5.6 Sol or Qwen3 Max?
GPT-5.6 Sol. It supports 1,047,576 tokens of context versus 252,000 tokens — roughly 786,000 English words in one request.
Do GPT-5.6 Sol and Qwen3 Max count tokens the same way?
Both use published tokenizers (o200k_base and qwen), so the same text can produce slightly different token counts on each. Paste your prompt into each model's counter page to compare real counts.