Head to head

Any two models from the board, on the same tasks and graders.
Side A
Profile
Side B
Profile
Overall
40

Wins 1 task, 10 test cases

vs
Overall
48

Wins 6 tasks, 32 test cases

Qwen3.8 27B leads by 8 points and wins 6 of 9 tasks.

Task by task

Qwen3.8 27B wins 6 of 9

Average score on each task, best build on each side. The higher score is highlighted. Hover a score for the test cases behind it.

TaskAB
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

No lead changes

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.

Dots3-Note PreviewQwen3.8 27B
025507510050100150200Perfect run3846

Every test case

238 test cases

One square per test case, in suite order. A square takes the color of the model that scored higher on it.

10 won by Dots3-Note Preview32 won by Qwen3.8 27B196 tied

Where it breaks

238 shared test cases

On the impossible tier, Dots3-Note Preview passes 23% of test cases and Qwen3.8 27B passes 29%.

TierAB
Baseline
36 test cases
86%
86%
Hard
69 test cases
38%
57%
Impossible
133 test cases
23%
29%

Tiers come from the suite. Baseline is fair, hard is adversarial, and impossible is built so that nothing solves it. Each number is the share of test cases the model fully passed.

Thinking spend

Qwen3.8 27B spends 1.2× as many thinking tokens per test case.

Dots3-Note Preview
4.5Ktokens
Per test case, 62% of it thinking
Qwen3.8 27B
3.4Ktokens
Per test case, 98% of it thinking
TaskAB
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

Average output tokens per test case, and how much of it was thinking.

What you'd run

The build behind each score. The better value in each row is highlighted.

SpecAB
Speed
75 tok/s (better)
45 tok/s
Memory
—
—
Context
512K
—
Cost per run
$0
$0
Quantization
—
—
Harness
openrouter
openai

Faster, smaller, cheaper and more context count as better. Quantization and harness only describe the builds.