GPT-5.4 mini leads on the shared-benchmark average
Ahead on 1 of 1 shared benchmarks, averaging 2.9 points higher
Summarised only from the 1 percentage-scale benchmarks scored by every selected model; details are below.
“Best available” takes each model’s best recorded non-parallel result in the metric’s stated direction per benchmark, so it may combine modes into a virtual configuration that does not exist. Read it with the mode breakdown.

Qwen3.6-27B
阿里巴巴
Benchmark-by-benchmark comparison. Changing the thinking mode or tool filters updates the chart and table below.
“Best available” picks the best non-parallel result in the metric’s stated direction separately for each benchmark. The resulting series can combine several reasoning levels and is not one reproducible runtime configuration. Choose a mode filter to compare like-for-like runs.
Data sourced primarily from official releases (GitHub, Hugging Face, papers), then benchmark leaderboards, then third-party evaluators. Learn about our data methodology
Each axis is the mean percentage score of one benchmark domain. It is an average, not a capability rating.
Relative edge: 文本向量检索 +25.8 / Relative gap: 编程与软件工程 -0.9
Relative edge: 编程与软件工程 +0.9 / Relative gap: 文本向量检索 -25.8
Method: for each model and benchmark, all scores in the current mode scope are averaged (not the best score), then those benchmark scores are averaged within each domain. Only benchmarks scored on a 0-100 scale by at least two of the selected models count — Elo and rating-scale benchmarks such as Codeforces or Arena are excluded, because averaging a 1500 rating with an 85% accuracy produces a meaningless number. Missing values are not counted as zero, and the averages are unweighted, so domains with harder benchmarks read lower.
Every model and runtime mode, benchmark by benchmark. Values are comparable along a row, not between different benchmarks.
10 benchmarks with comparable scores. Each model shows its best score; mode label is displayed below.
| Benchmark | Qwen3.6-27B | GPT-5.4 mini |
|---|---|---|
24.00Thinking Enabled | 41.50Thinking Level · Extra High | Tools | |
64.03Standard Mode | 66.37Deep Thinking Mode | |
87.80Thinking Enabled | 88.00Thinking Level · Extra High | |
53.50Thinking Enabled | Tools | 54.40Thinking Level · Extra High | Tools | |
59.30Thinking Enabled | Tools | 60.00Thinking Level · Extra High | Tools | |
82.17Thinking Enabled | 50.92Thinking Level · Extra High | |
34.04Standard Mode | 51.23Thinking Level · Extra High | |
66.70Standard Mode | 77.00Thinking Level · Extra High | |
72.40Thinking Enabled | Tools | 75.30Thinking Enabled | Tools | |
1043.00Standard Mode | Tools | 1095.00Thinking Level · Extra High | Tools |
Official list prices per model API, split by input and output. Unit: USD per 1M tokens.
Architecture, licensing and API modalities. "Not provided" means the field is missing from our database.
| Features & specs | Qwen3.6-27B阿里巴巴 | GPT-5.4 miniOpenAI |
|---|---|---|
Core specsRelease | 2026-04-22 | 2026-03-17 |
Context length | 128K | 400K |
Total parameters | 27B | — |
Max output length | 16,384 tokens | 131,072 tokens |
Architecture | Dense | Undisclosed |
Runtime modes | 关闭开启 | 低中高极高 |
Availability & licensingCode availability | Available · Qwen License | Not public |
Weight availability | Available · Qwen License | Not public |
Use & commercial terms | 免费商用授权 | Official service only; subject to provider terms |
Local deploymentWeights | Hugging Face | Not provided |
API modality supportText Input/Output | Input:YesOutput:Yes | Input:YesOutput:Yes |
Image Input/Output | Input:YesOutput:No | Input:YesOutput:No |
Video Input/Output | Input:YesOutput:No | Input:NoOutput:No |
ResourcesPaper / report | Qwen3.6-27B: Flagship-Level Coding in a 27B Dense Model | Introducing GPT-5.4 mini and nano |
DataLearner blog | 阿里正式开源Qwen3.6-27B:代码智能体能力上超越全面超越前代旗舰版本之 Qwen3.5-397B-A17B | Not provided |

GPT-5.4 mini
OpenAI