GPT-5.6 Sol vs Qwen3.7 Max
Pricing & Specs
OpenAI vs Qwen (Alibaba), side by side from a live registry. Specs below, then benchmark both on your own task.
TL;DR: On a typical task (1K input + 500 output tokens), Qwen3.7 Max is about 6.4x cheaper than GPT-5.6 Sol. But per-token price is not cost per result: a cheaper model that needs more tokens, retries, or hand-holding can end up more expensive on your workload. The specs below are facts; which one is better at YOUR task is measurable, not guessable.
API Pricing: GPT-5.6 Sol vs Qwen3.7 Max
| Tokens | GPT-5.6 Sol | Qwen3.7 Max |
|---|---|---|
| Input | $5 / 1M | $1.25 / 1M |
| Output | $30 / 1M | $3.75 / 1M |
| Cached input | $0.5 / 1M | $0.13 / 1M |
What that means in practice (1K input + 500 output tokens)
Specs Compared
| Spec | GPT-5.6 Sol | Qwen3.7 Max |
|---|---|---|
| Context window | 1.05M tokens | 1M tokens |
| Max output tokens | 128K tokens | - |
| Input modalities | text, image | text |
| Knowledge cutoff | February 16, 2026 | - |
| Latency (measured) | - | - |
| Reasoning model | Yes | Yes |
| Tool / function calling | Yes | Yes |
| JSON mode | Yes | Yes |
| Prompt caching | Yes | Yes |
When to Choose Which
FAQ
Which is cheaper, GPT-5.6 Sol or Qwen3.7 Max?
GPT-5.6 Sol costs $5/$30 per 1M input/output tokens; Qwen3.7 Max costs $1.25/$3.75. On a typical task (1K input + 500 output tokens), Qwen3.7 Max is about 6.4x cheaper than GPT-5.6 Sol.
Which has the bigger context window, GPT-5.6 Sol or Qwen3.7 Max?
GPT-5.6 Sol has a 1.05M-token context window; Qwen3.7 Max has 1M tokens.
Is GPT-5.6 Sol better than Qwen3.7 Max?
It depends on the task. Generic leaderboards won't tell you which one wins on YOUR workload. OpenMark lets you benchmark GPT-5.6 Sol and Qwen3.7 Max head to head on your own task with real API calls, no API keys needed, free tier available.
GPT-5.6 Sol or Qwen3.7 Max for YOUR Task?
Spec tables can't answer that. Run both head to head on your actual workload:
real API calls, ranked results with accuracy, cost, and latency. Free tier available.