Head to head

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

Wins 0 tasks, 16 test cases

vs
Overall
54

Wins 9 tasks, 70 test cases

Qwen3.8 Flash leads by 22 points and wins 9 of 9 tasks.

Task by task

Qwen3.8 Flash wins 9 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
54
Tool Calling
60
79
Structured Output
30
47
RAG / Retrieval QA
19
41
Context Recall
50
89
Coding
54
75
Reasoning & Math
11
32
Instruction Following
4
25
Classification
17
38
Summarization
41
60

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.

Laguna S 2.1Qwen3.8 Flash
025507510050100150200Perfect run3152

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.

16 won by Laguna S 2.170 won by Qwen3.8 Flash152 tied

Where it breaks

238 shared test cases

On the impossible tier, Laguna S 2.1 passes 19% of test cases and Qwen3.8 Flash passes 35%.

TierAB
Baseline
36 test cases
53%
89%
Hard
69 test cases
29%
57%
Impossible
133 test cases
19%
35%

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

Both models spend about the same on thinking per test case.

Laguna S 2.1
2.5Ktokens
Per test case, 76% of it thinking
Qwen3.8 Flash
3Ktokens
Per test case, 70% of it thinking
TaskAB
Tool Calling
4.2K74% thinking
6.7K66% thinking
Structured Output
1.4K97% thinking
1.9K67% thinking
RAG / Retrieval QA
1.5K79% thinking
2.4K66% thinking
Context Recall
66683% thinking
55595% thinking
Coding
2.9K42% thinking
5.2K71% thinking
Reasoning & Math
5.6K87% thinking
4.3K73% thinking
Instruction Following
1.8K34% thinking
2.3K69% thinking
Classification
2.8K100% thinking
1.8K72% thinking
Summarization
51393% thinking
1.4K70% 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
64 tok/s (better)
Memory
—
—
Context
262.1K
1M (better)
Cost per run
$0 (better)
$0.5705
Quantization
—
—
Harness
openrouter
openrouter

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