Qwen vs Claude. Price, context and when to switch.
Qwen3.8 27B is a dense, Apache 2.0 model small enough for one data-center GPU, with thinking on by default. Claude Sonnet 5 is Anthropic's closed model. Here is what the same work costs on each.
Side by side.
Claude Sonnet 5 at Anthropic's list price as of October 11, 2026. Open models at OpenRelay's current rates.
| Spec | Claude Sonnet 5 | Qwen3.8 27B |
|---|---|---|
| Developer | Anthropic | Alibaba |
| Weights | Closed | Open |
| Context window | 1M | 256K |
| Input | Text, images | Text |
| Input / 1M tokens | $2.00 | $0.42 |
| Cached input / 1M | $0.20 | $0.085 |
| Output / 1M tokens | $10.00 | $3.00 |
Monthly cost on common workloads.
100,000 requests a month at realtime rates. Token counts are typical sizes; open any row in the calculator to use your own.
Open the calculator| Workload | Claude Sonnet 5 | Qwen3.8 27B |
|---|---|---|
| Record matching2,500 in · 150 out | $650.00 | $150.004.3x cheaper |
| Classification400 in · 20 out | $100.00 | $22.804.4x cheaper |
| Data extraction1,500 in · 300 out | $600.00 | $153.003.9x cheaper |
| Support chat3,000 in · 400 out · 50% cached | $730.00 | $195.753.7x cheaper |
| RAG answers6,000 in · 500 out · 20% cached | $1,484 | $361.804.1x cheaper |
| Agent step20,000 in · 1,500 out · 80% cached | $2,620 | $754.003.5x cheaper |
Pick Qwen3.8 27B for
- High-volume work where the token bill dominates.
- Long prompts up to 256K tokens at open-model rates.
- A path to self-hosting on a single GPU. The weights are Apache 2.0.
Pick Claude Sonnet 5 for
- Prompts over 256K tokens. Sonnet 5 takes 1M.
- Image input. This Qwen endpoint is text only.
- Tasks where your own evals show Sonnet 5 ahead by enough to pay for the gap.
Questions
Is Qwen3.8 27B cheaper than Claude Sonnet 5?
Per token, yes. Claude Sonnet 5 lists at $2.00 input and $10.00 output per 1M tokens (as of October 11, 2026). A million record-matching calls a month at 2,500 input and 150 output tokens cost $6,500 on it. Qwen3.8 27B lists at $0.42 input and $3.00 output per 1M tokens, and runs the same job for $1,500.
Why does Qwen3.8 generate more output tokens?
Thinking is on by default, so Qwen writes a reasoning trace before it answers, and the trace bills as output. Put the full generated length in the calculator's output field.
Can I run Qwen3.8 27B myself?
Yes. At 27B parameters it fits on a single data-center GPU, and the Apache 2.0 weights are on Hugging Face.
How should I compare quality?
Take a few hundred real requests where you already know the right answer, run them on both models, and score the outputs the same way. Then divide cost by the share each model gets right. That number, cost per correct answer, is the one to decide on.
Price your own workload.
Your token counts and volume, every model side by side.