// head_to_head
Qwen3.6 Plus vs Qwen3.8 27B
Published LiveBench scores across all seven categories, live list pricing, context windows, and the measured cost of a point of capability — for both models, side by side.
Qwen3.8 27B scores higher, Qwen3.6 Plus costs less — it depends on your workload.
Qwen3.8 27B is ahead by 6.4 points overall, and Qwen3.6 Plus lists 1.6× cheaper per blended million tokens. Whether 6.4 points is worth that depends on how much a wrong answer costs you. The two cost measures disagree here, which is worth knowing: Qwen3.6 Plus has the lower sticker price, but Qwen3.8 27B earns each point of capability for less — $0.0556 against $0.1262 — because per-token rates do not predict how many tokens a model actually spends on a task.
qwen
Qwen3.6 Plus
- Blended / 1M
- $0.731
- Context
- 1M
- Released
- Apr 2, 2026
- Overall score
- 68.9
qwen
Qwen3.8 27B
- Blended / 1M
- $1.14
- Context
- 1M
- Released
- Aug 14, 2026
- Overall score
- 75.3
Specs and pricing
| Metric | Qwen3.6 Plus | Qwen3.8 27B |
|---|---|---|
| LiveBench overall Mean of the seven LiveBench category scores, 0–100. Higher is better. | 68.9 | 75.3win |
| Cost per point Measured benchmark spend divided by overall score — dollars per point of capability. | $0.1262 | $0.0556win |
| Blended price / 1M 3:1 input:output mix, the usual shape of production traffic. | $0.731win | $1.14 |
| Input price / 1M | $0.325win | $0.450 |
| Output price / 1M | $1.95win | $3.20 |
| Cached input / 1M Price of an input token served from the prompt cache, where the provider publishes one. | — | $0.050 |
| Context window | 1M | 1M |
| Max output tokens | 66K | 131Kwin |
Benchmarks by category
An overall score averages away the thing you probably care about. These are the seven LiveBench categories scored separately — Qwen3.6 Plus on top, Qwen3.8 27B below, both out of 100.
What each one costs to run
Per-token prices are hard to feel. These are monthly list costs for both models across five workload shapes, using each provider's published cached-input rate where there is one.
| Workload | Qwen3.6 Plus | Qwen3.8 27B |
|---|---|---|
| Support chatbot 1.2K in / 400 out × 200K requests | $234.00/mo | $335.20/mo |
| RAG assistant 8K in / 600 out × 100K requests | $377.00/mo | $392.00/mo |
| Coding agent 40K in / 4K out × 20K requests | $416.00/mo | $392.00/mo |
| Document extraction 20K in / 1.5K out × 50K requests | $471.25/mo | $670.00/mo |
| Bulk classification 500 in / 20 out × 5M requests | $1007.50/mo | $1245.00/mo |
Which should you pick?
You are running this at volume
Qwen3.8 27B
Lowest measured cost per point of capability at $0.0556 per point — the gap compounds with every request.
Quality matters more than the bill
Qwen3.8 27B
Highest overall LiveBench score of the two at 75.3.
The workload is coding or agentic work
Qwen3.8 27B
Leads on agentic coding — 61.4 against 41.4.
You are cost-constrained
Qwen3.6 Plus
Cheaper on blended list price at $0.731 per million tokens.
Qwen3.6 Plus vs Qwen3.8 27B FAQ
Which is better, Qwen3.6 Plus or Qwen3.8 27B?
Qwen3.8 27B scores higher, Qwen3.6 Plus costs less — it depends on your workload. Qwen3.8 27B is ahead by 6.4 points overall, and Qwen3.6 Plus lists 1.6× cheaper per blended million tokens. Whether 6.4 points is worth that depends on how much a wrong answer costs you. The two cost measures disagree here, which is worth knowing: Qwen3.6 Plus has the lower sticker price, but Qwen3.8 27B earns each point of capability for less — $0.0556 against $0.1262 — because per-token rates do not predict how many tokens a model actually spends on a task.
Is Qwen3.6 Plus cheaper than Qwen3.8 27B?
Qwen3.6 Plus is cheaper. On a 3:1 input:output blend, Qwen3.6 Plus lists at $0.731 per million tokens and Qwen3.8 27B at $1.14 — Qwen3.6 Plus is 1.6× cheaper. Input and output are priced separately — Qwen3.6 Plus charges $0.325 in and $1.95 out, Qwen3.8 27B charges $0.450 and $3.20 — so the model that looks cheaper flips depending on how output-heavy your workload is.
Qwen3.6 Plus vs Qwen3.8 27B: which scores higher on benchmarks?
Qwen3.6 Plus scores 68.9 and Qwen3.8 27B scores 75.3 overall on LiveBench, the mean of its seven categories. That is a 6.4-point lead for Qwen3.8 27B. Category scores differ from the overall figure — a model can lead on reasoning and trail on coding, which the per-category table above breaks out.
Which gives better value for money, Qwen3.6 Plus or Qwen3.8 27B?
Qwen3.8 27B. Cost per point divides the measured dollars LiveBench spent running the benchmark by the score it earned, so it captures something token pricing misses: a reasoning model can emit many times more tokens than its per-token rate suggests. Qwen3.6 Plus works out at $0.1262 per point and Qwen3.8 27B at $0.0556.
Does Qwen3.6 Plus or Qwen3.8 27B have a bigger context window?
They are effectively the same — 1M for Qwen3.6 Plus and 1M for Qwen3.8 27B.
Do Qwen3.6 Plus and Qwen3.8 27B support prompt caching?
Qwen3.8 27B publishes a cached-input rate of $0.050 per million tokens against a full input rate of $0.450. The catalogue lists no separate cached rate for Qwen3.6 Plus, which means the provider does not price it separately here — not that caching is unavailable.
Related comparisons
How these numbers are produced
- Price — provider list price from OpenRouter, refreshed every 15 minutes. “Blended” is a 3:1 input:output mix.
- Scores — LiveBench release 2026-06-25, using their own category map. Each model shows its strongest published run. A blank means “not evaluated”, never “bad”.
- Cost per point — the measured dollars LiveBench spent on the run, divided by the score it earned.
- “Win” — awarded only past a threshold: one full point on a benchmark score, 10% on a price, 25% on a context window. Anything tighter reports as a tie, because effort settings alone move a LiveBench score by more than that.
Published benchmarks rank models on someone else's tasks. Before committing, see LLM & agent evaluation for building an eval on your own.