LFM2.5 24B A2B vs Mellum2.1 Thinking
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.
TaskALFM2.5 24B A2BBMellum2.1 Thinking
Overall
71m 53s
91m 56s
Agents
123m 49s
92m 3s
Structured Extraction
1054.9s
51m 36s
Coding
11m 15s
52m 11s
Grounded Answers
557.8s
131m 24s
Instruction Following
162m 44s
283m 10s
Business Logic
51m 2s
01m 39s
Security & permissions
101m 52s
81m 40s
Diagnosis & investigation
04m 12s
01m 15s
What you'd run
The build behind each score. Orange marks the faster, smaller, cheaper or longer-context side.
SpecALFM2.5 24B A2BBMellum2.1 Thinking
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
Each model's running score as the test cases go by. The dashed line is a perfect run.
Every test case
Each square is one test case, colored by the model that scored higher.
Agents
Structured Extraction
Coding
Grounded Answers
Instruction Following
Business Logic
Security & permissions
Diagnosis & investigation