LFM2.5 24B A2B vs Muse Spark 1.3 Contributor
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.
TaskALFM2.5 24B A2BBMuse Spark 1.3 Contributor
Overall
71m 53s
661m 42s
Agents
123m 49s
573m 16s
Structured Extraction
1054.9s
9037.9s
Coding
11m 15s
482m 1s
Grounded Answers
557.8s
811m 1s
Instruction Following
162m 44s
841m 18s
Business Logic
51m 2s
761m 7s
Security & permissions
101m 52s
761m 59s
Diagnosis & investigation
04m 12s
173m 34s
What you'd run
The build behind each score. Orange marks the faster, smaller, cheaper or longer-context side.
SpecALFM2.5 24B A2BBMuse Spark 1.3 Contributor
Speed
82 tok/s
107 tok/s
Machine
Apple M5 Pro, 48 GB
Hosted
Memory at 32K
25.0 GB
—
Context
128K
1M (better)
Cost per run
Not measured
$0.41
Cost per case
Not measured
$0.0027
Time per case
1m 53s
1m 42s (better)
Quantization
Q8_0
—
Harness
llama.cpp
openrouter
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