Head-to-head showdown: Qwen3.8 27B (OpenRouter) ($0.42 in / $3.00 out per 1M) vs GPT-5.6 Cyber ($12.50 in / $75.00 out per 1M). Qwen3.8 27B (OpenRouter) is 25.6× cheaper across standard token mixes, with 1M vs 1.1M context windows.
qwen3.8-27b · qwen
gpt-5.6-cyber · openai
Cost by Volume
| Workload Scenario | Qwen3.8 27B (OpenRouter) | GPT-5.6 Cyber | Price Delta |
|---|---|---|---|
| 1M input tokens (raw text) | $0.42 | $12.50 | −$12.08 |
| 1M output tokens (generation) | $3.00 | $75.00 | −$72.00 |
| 1M tokens · 70% input / 30% output mix | $1.194 | $31.25 | −$30.056 |
| Standard chat turn (4K in / 800 out, 50% cached) | $0.00408 | $0.0875 | −$0.0834 |
| Monthly scale (10K requests / day) | $1,224.00 | $26,250.00 | −$25,026.00 |
Negative difference = Qwen3.8 27B (OpenRouter) is cheaper. Positive = GPT-5.6 Cyber is cheaper.
Best For
Fit score = weighted composite blend for each use case; value = fit ÷ cost per 1,000 requests.
| Use case | Fit — Qwen3.8 27B (OpenRouter) | Fit — GPT-5.6 Cyber | Cost / 1K — Qwen3.8 27B (OpenRouter) | Cost / 1K — GPT-5.6 Cyber | Winner |
|---|---|---|---|---|---|
| Customer support chatbot | — | — | $2.52 | $42.438 | no data |
| RAG / search-augmented answers | — | — | $4.86 | $92.50 | no data |
| AI coding assistant | — | — | $11.04 | $219.00 | no data |
| Document summarization | — | — | $12.30 | $329.375 | no data |
| Agentic workflow | — | — | $21.30 | $320.00 | no data |
| Content generation | — | — | $3.936 | $97.30 | no data |
| Data extraction & tagging | — | — | $1.59 | $39.25 | no data |
| Translation | — | — | $18.60 | $466.563 | no data |
Costs use each use case's typical token mix and cacheable share. Fit weights are documented on the methodology page.
Scaling Curve
Total cost of a token volume at 70/30 input/output split (uncached). Log-log scale.
Verdict
Qwen3.8 27B (OpenRouter) is cheaper on both input and output rates, so it costs less at every input/output mix. Price alone still isn't the whole decision: capability, latency and context limits (Qwen3.8 27B (OpenRouter): 1M, GPT-5.6 Cyber: 1.1M) may justify the premium for your task.
FAQ
On input, Qwen3.8 27B (OpenRouter) is cheaper ($0.42/M vs $12.50/M). On output, Qwen3.8 27B (OpenRouter) is cheaper ($3.00/M vs $75.00/M). The same model is cheaper on both sides, so it wins at every mix.
A chat-style request (4,000 input + 800 output tokens, 50% cached) costs $0.00408 on Qwen3.8 27B (OpenRouter) and $0.0875 on GPT-5.6 Cyber — Qwen3.8 27B (OpenRouter) is 21.4× cheaper for that workload.
Qwen3.8 27B (OpenRouter) supports 1,000,000 tokens (131.1K max output); GPT-5.6 Cyber supports 1,050,000 (128K max output). GPT-5.6 Cyber fits 1.1× more context, which matters for long documents and agents.