Head to head
Any two models from the board, on the same tasks and graders.
Qwen3.8 27B leads by 8 points and wins 6 of 9 tasks.
Task by task
Average score on each task, best build on each side. The higher score is highlighted. Hover a score for the test cases behind it.
TaskADots3-Note PreviewBQwen3.8 27BLead
Overall
40
48
Tool Calling
66
65
Structured Output
30
48
RAG / Retrieval QA
22
59
Context Recall
89
94
Coding
4
7
Reasoning & Math
32
32
Instruction Following
25
25
Classification
31
38
Summarization
58
62
The race
Score piled up over the 238 test cases both models ran, as a share of the suite's maximum. The dashed line is a perfect run.
Every test case
One square per test case, in suite order. A square takes the color of the model that scored higher on it.
Tool Calling
Structured Output
RAG / Retrieval QA
Context Recall
Coding
Reasoning & Math
Instruction Following
Classification
Summarization
Where it breaks
On the impossible tier, Dots3-Note Preview passes 23% of test cases and Qwen3.8 27B passes 29%.
TierADots3-Note PreviewBQwen3.8 27BLead
Baseline
86
86
Hard
38
57
Impossible
23
29
Thinking spend
Qwen3.8 27B spends 1.2× as many thinking tokens per test case.
4.5Ktokens
Per test case, 62% of it thinking
3.4Ktokens
Per test case, 98% of it thinking
TaskADots3-Note PreviewBQwen3.8 27B
Tool Calling
8.8K52% thinking
4.8K88% thinking
Structured Output
2.9K49% thinking
2.6K99% thinking
RAG / Retrieval QA
3.4K58% thinking
2.5K100% thinking
Context Recall
1.7K65% thinking
50398% thinking
Coding
8K88% thinking
6.2K100% thinking
Reasoning & Math
6.2K57% thinking
5.4K100% thinking
Instruction Following
3.4K59% thinking
2.9K100% thinking
Classification
3.1K58% thinking
2.7K100% thinking
Summarization
2.5K61% thinking
1.9K99% thinking
What you'd run
The build behind each score. The better value in each row is highlighted.
SpecADots3-Note PreviewBQwen3.8 27B
Speed
75 tok/s (better)
45 tok/s
Memory
—
—
Context
512K
—
Cost per run
$0
$0
Quantization
—
—
Harness
openrouter
openai