LFM2.5 24B A2B vs Mellum2.1 Thinking

Overall
7
vs
Overall
9

Too close to call. Mellum2.1 Thinking wins 14 of the 25 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. LFM2.5 24B A2B spends 1.3× as many thinking tokens per test case.

Thinking tokensAnswer tokens
TaskAB
Overall
71m 53s
9.2K, 93% thinking10.3K, 63% thinking
91m 56s
Agents
123m 49s
18.5K, 98% thinking10.8K, 93% thinking
92m 3s
Structured Extraction
1054.9s
4.4K, 94% thinking8.3K, 51% thinking
51m 36s
Coding
11m 15s
6.1K, 68% thinking11.3K, 38% thinking
52m 11s
Grounded Answers
557.8s
4.7K, 96% thinking7.3K, 62% thinking
131m 24s
Instruction Following
162m 44s
13.4K, 97% thinking17.3K, 63% thinking
283m 10s
Business Logic
51m 2s
5K, 83% thinking9K, 50% thinking
01m 39s
Security & permissions
101m 52s
9K, 97% thinking9.1K, 75% thinking
81m 40s
Diagnosis & investigation
04m 12s
19.9K, 98% thinking6.8K, 98% thinking
01m 15s

What you'd run

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

SpecAB
Speed
82 tok/s
90 tok/s (better)
Machine
Apple M5 Pro, 48 GB
Apple M5 Pro, 48 GB
Memory at 32K
25.0 GB
12.9 GB (better)
Context
128K
128K
Cost per run
Not measured
$2.46 est.
Cost per case
Not measured
$0.016 est.
Time per case
1m 53s (better)
1m 56s
Quantization
Q8_0
Q8_0
Harness
llama.cpp
llama.cpp

The race

1 lead change

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

LFM2.5 24B A2BMellum2.1 Thinking
025507510050100150Perfect run79

Every test case

153 test cases

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

11 won by LFM2.5 24B A2B14 won by Mellum2.1 Thinking128 tied