Mellum2.1 Thinking vs Spark X2.6 4B

Overall
9
vs
Overall
15

Spark X2.6 4B is clearly better. It wins 23 of the 33 test cases where they differ.

Learn to build evals like this in the AI Engineering Academy

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

Thinking tokensAnswer tokens
TaskAB
Overall
91m 56s
10.3K, 63% thinking8.2K, 84% thinking
151m 3s
Agents
92m 3s
10.8K, 93% thinking11.5K, 97% thinking
141m 32s
Structured Extraction
51m 36s
8.3K, 51% thinking5.3K, 78% thinking
1039.5s
Coding
52m 11s
11.3K, 38% thinking9.1K, 48% thinking
41m 8s
Grounded Answers
131m 24s
7.3K, 62% thinking6.6K, 86% thinking
1050.2s
Instruction Following
283m 10s
17.3K, 63% thinking11.9K, 90% thinking
371m 29s
Business Logic
01m 39s
9K, 50% thinking4.9K, 86% thinking
1036.3s
Security & permissions
81m 40s
9.1K, 75% thinking7K, 94% thinking
3154.3s
Diagnosis & investigation
01m 15s
6.8K, 98% thinking11.6K, 98% thinking
01m 30s

What you'd run

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

SpecAB
Speed
90 tok/s
136 tok/s
Machine
Apple M5 Pro, 48 GB
RTX 5090, 32 GB
Memory at 32K
12.9 GB
9.4 GB (better)
Context
128K
605K (better)
Cost per run
$2.46 est.
$1.61 est. (better)
Cost per case
$0.016 est.
$0.011 est. (better)
Time per case
1m 56s
1m 3s (better)
Quantization
Q8_0
BF16
Harness
llama.cpp
llama.cpp

The race

4 lead changes

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

Mellum2.1 ThinkingSpark X2.6 4B
025507510050100150915

Every test case

153 test cases

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

10 won by Mellum2.1 Thinking23 won by Spark X2.6 4B120 tied