Head to head

Any two models from the board, on the same tasks and graders.
Side A
Profile
Side B
Profile
Overall
32

Wins 1 task, 26 test cases

vs
Overall
48

Wins 8 tasks, 56 test cases

Qwen3.8 27B leads by 16 points and wins 8 of 9 tasks.

Task by task

Qwen3.8 27B wins 8 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
32
48
Tool Calling
60
65
Structured Output
30
48
RAG / Retrieval QA
19
59
Context Recall
50
94
Coding
54
7
Reasoning & Math
11
32
Instruction Following
4
25
Classification
17
38
Summarization
41
62

The race

3 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.

Laguna S 2.1Qwen3.8 27B
025507510050100150200Perfect run3146

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.

26 won by Laguna S 2.156 won by Qwen3.8 27B156 tied

Where it breaks

238 shared test cases

On the impossible tier, Laguna S 2.1 passes 19% of test cases and Qwen3.8 27B passes 29%.

TierAB
Baseline
36 test cases
53%
86%
Hard
69 test cases
29%
57%
Impossible
133 test cases
19%
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 1.8× as many thinking tokens per test case.

Laguna S 2.1
2.5Ktokens
Per test case, 76% of it thinking
Qwen3.8 27B
3.4Ktokens
Per test case, 98% of it thinking
TaskAB
Tool Calling
4.2K74% thinking
4.8K88% thinking
Structured Output
1.4K97% thinking
2.6K99% thinking
RAG / Retrieval QA
1.5K79% thinking
2.5K100% thinking
Context Recall
66683% thinking
50398% thinking
Coding
2.9K42% thinking
6.2K100% thinking
Reasoning & Math
5.6K87% thinking
5.4K100% thinking
Instruction Following
1.8K34% thinking
2.9K100% thinking
Classification
2.8K100% thinking
2.7K100% thinking
Summarization
51393% 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
48 tok/s (better)
45 tok/s
Memory
—
—
Context
262.1K
—
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.