Head-to-head showdown: Qwen3.8 27B (OpenRouter) ($0.42 in / $3.00 out per 1M) vs GPT-5.4 mini ($0.75 in / $4.50 out per 1M). Qwen3.8 27B (OpenRouter) is 1.5× cheaper across standard token mixes, with 1M vs 256K context windows.
qwen3.8-27b · qwen
gpt-5.4-mini · openai
Benchmarks
Qwen3.8 27B (OpenRouter)
No verified third-party composite score published.
GPT-5.4 mini
Third-party composite indices via OpenRouter's live catalog — source and verification date on each model page.
Cost by Volume
| Workload Scenario | Qwen3.8 27B (OpenRouter) | GPT-5.4 mini | Price Delta |
|---|---|---|---|
| 1M input tokens (raw text) | $0.42 | $0.75 | −$0.33 |
| 1M output tokens (generation) | $3.00 | $4.50 | −$1.50 |
| 1M tokens · 70% input / 30% output mix | $1.194 | $1.875 | −$0.681 |
| Standard chat turn (4K in / 800 out, 50% cached) | $0.00408 | $0.00525 | −$0.00117 |
| Monthly scale (10K requests / day) | $1,224.00 | $1,575.00 | −$351.00 |
Negative difference = Qwen3.8 27B (OpenRouter) is cheaper. Positive = GPT-5.4 mini is cheaper.
Best For
Fit score = weighted composite blend for each use case; value = fit ÷ cost per 1,000 requests. Scoreboard: Qwen3.8 27B (OpenRouter) 0 – 8 GPT-5.4 mini.
| Use case | Fit — Qwen3.8 27B (OpenRouter) | Fit — GPT-5.4 mini | Cost / 1K — Qwen3.8 27B (OpenRouter) | Cost / 1K — GPT-5.4 mini | Winner |
|---|---|---|---|---|---|
| Customer support chatbot | — | 38.7 | $2.52 | $2.546 | GPT-5.4 mini — only scored model |
| RAG / search-augmented answers | — | 41.1 | $4.86 | $5.55 | GPT-5.4 mini — only scored model |
| AI coding assistant | — | 49.1 | $11.04 | $13.14 | GPT-5.4 mini — only scored model |
| Document summarization | — | 39.6 | $12.30 | $19.763 | GPT-5.4 mini — only scored model |
| Agentic workflow | — | 38.3 | $21.30 | $19.20 | GPT-5.4 mini — only scored model |
| Content generation | — | 39.6 | $3.936 | $5.838 | GPT-5.4 mini — only scored model |
| Data extraction & tagging | — | 45.1 | $1.59 | $2.355 | GPT-5.4 mini — only scored model |
| Translation | — | 40.5 | $18.60 | $27.994 | GPT-5.4 mini — only scored model |
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-5.4 mini: 256K) may justify the premium for your task.
FAQ
On input, Qwen3.8 27B (OpenRouter) is cheaper ($0.42/M vs $0.75/M). On output, Qwen3.8 27B (OpenRouter) is cheaper ($3.00/M vs $4.50/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 $0.00525 on GPT-5.4 mini — Qwen3.8 27B (OpenRouter) is 1.3× cheaper for that workload.
Qwen3.8 27B (OpenRouter) supports 1,000,000 tokens (131.1K max output); GPT-5.4 mini supports 256,000 (32.8K max output). Qwen3.8 27B (OpenRouter) fits 3.9× more context, which matters for long documents and agents.