Head to head

Any two models from the board, on the same tasks and graders.

Side A

Profile

Hostedinclusionai264 tok/sopenrouter

Side B

Profile

Hostedopenai45 tok/sopenai

Overall

Wins 3 tasks, 15 test cases

Overall

Wins 5 tasks, 39 test cases

Qwen3.8 27B leads by 9 points and wins 5 of 9 tasks.

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Task by task

Qwen3.8 27B wins 5 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.

TaskALing-3.0 flashBQwen3.8 27BLead

Overall

Tool Calling

Right tool, right args, right sequence?

Structured Output

Valid JSON matching the schema, correct fields?

+11

RAG / Retrieval QA

A correct answer grounded in the given context, with nothing made up?

+29

Context Recall

Finds the one fact buried in a long context?

Coding

Working code that passes hidden unit tests?

Reasoning & Math

Multi-step math and logic with the exact right answer?

Even

Instruction Following

Obeys format, length, and content constraints to the letter?

+18

Classification

Correct label from a fixed set?

Summarization

Compact summary that keeps the facts and invents none?

+28

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.

Ling-3.0 flashQwen3.8 27B

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.

Tool Calling56

Structured Output14

RAG / Retrieval QA19

Context Recall12

Coding21

Reasoning & Math11

Instruction Following05

Classification31

Summarization110

15 won by Ling-3.0 flash39 won by Qwen3.8 27B184 tied

Where it breaks

238 shared test cases

On the impossible tier, Ling-3.0 flash passes 20% of test cases and Qwen3.8 27B passes 29%.

TierALing-3.0 flashBQwen3.8 27BLead

Baseline

36 test cases

75%

86%

+11 pts

Hard

69 test cases

46%

57%

+11 pts

Impossible

133 test cases

20%

29%

+9 pts

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 1.4× as many thinking tokens per test case.

Ling-3.0 flash

4.1Ktokens

Per test case, 55% of it thinking

Qwen3.8 27B

3.4Ktokens

Per test case, 98% of it thinking

TaskALing-3.0 flashBQwen3.8 27B

Tool Calling

6.7K40% thinking

4.8K88% thinking

Structured Output

3K46% thinking

2.6K99% thinking

RAG / Retrieval QA

3.3K54% thinking

2.5K100% thinking

Context Recall

87459% thinking

50398% thinking

Coding

8K79% thinking

6.2K100% thinking

Reasoning & Math

6.2K52% thinking

5.4K100% thinking

Instruction Following

3.2K54% thinking

2.9K100% thinking

Classification

2.8K50% thinking

2.7K100% thinking

Summarization

2K49% 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.

SpecALing-3.0 flashBQwen3.8 27B

Speed

264 tok/s

45 tok/s

Memory

—

Context

262.1K

—

Cost per run

Quantization

—

Harness

openrouter

openai

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