Mellum2.1 Thinking vs Qwen3.8 27B

Overall
9
vs
Overall
48

Qwen3.8 27B is clearly better. It wins 82 of the 85 test cases where they differ.

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Task by task

A score turns orange only when that model wins clearly more of the task's test cases. Under each score, the average time per test case on the machine it ran on. Mellum2.1 Thinking spends 1.2× as many thinking tokens per test case.

Thinking tokensAnswer tokens
TaskAB
Overall
91m 56s
10.3K, 63% thinking5.9K, 91% thinking
4833.3s
Agents
92m 3s
10.8K, 93% thinking5.2K, 78% thinking
5736.6s
Structured Extraction
51m 36s
8.3K, 51% thinking4.6K, 92% thinking
7320.6s
Coding
52m 11s
11.3K, 38% thinking9.3K, 94% thinking
3753.0s
Grounded Answers
131m 24s
7.3K, 62% thinking4.2K, 91% thinking
6131.6s
Instruction Following
283m 10s
17.3K, 63% thinking6.9K, 93% thinking
6733.6s
Business Logic
01m 39s
9K, 50% thinking7.6K, 98% thinking
3632.9s
Security & permissions
81m 40s
9.1K, 75% thinking3.7K, 85% thinking
5122.6s
Diagnosis & investigation
01m 15s
6.8K, 98% thinking5.9K, 85% thinking
040.0s

What you'd run

The build behind each score. Orange marks the faster, smaller, cheaper or longer-context side.

SpecAB
Speed
90 tok/s
196 tok/s
Machine
Apple M5 Pro, 48 GB
Hosted
Memory at 32K
12.9 GB
—
Context
128K
256K (better)
Cost per run
$2.46 est.
$1.28 (better)
Cost per case
$0.016 est.
$0.0083 (better)
Time per case
1m 56s
33.3s (better)
Quantization
Q8_0
FP8
Harness
llama.cpp
openrouter

The race

No lead changes

Each model's running score as the test cases go by. The dashed line is a perfect run.

Mellum2.1 ThinkingQwen3.8 27B
025507510050100150Perfect run948

Every test case

153 test cases

Each square is one test case, colored by the model that scored higher.

3 won by Mellum2.1 Thinking82 won by Qwen3.8 27B68 tied