Head to head
Any two models from the board, on the same tasks and graders.
Qwen3.8 27B leads by 16 points and wins 8 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.
TaskALaguna S 2.1BQwen3.8 27BLead
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
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, Laguna S 2.1 passes 19% of test cases and Qwen3.8 27B passes 29%.
TierALaguna S 2.1BQwen3.8 27BLead
Baseline
53
86
Hard
29
57
Impossible
19
29
Thinking spend
Qwen3.8 27B spends 1.8× as many thinking tokens per test case.
2.5Ktokens
Per test case, 76% of it thinking
3.4Ktokens
Per test case, 98% of it thinking
TaskALaguna S 2.1BQwen3.8 27B
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
What you'd run
The build behind each score. The better value in each row is highlighted.
SpecALaguna S 2.1BQwen3.8 27B
Speed
48 tok/s (better)
45 tok/s
Memory
—
—
Context
262.1K
—
Cost per run
$0
$0
Quantization
—
—
Harness
openrouter
openai