LFM2.5 24B A2B vs Mistral Large 4
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 1.9× as many thinking tokens per test case.
TaskALFM2.5 24B A2BBMistral Large 4
Overall
71m 53s
281m 56s
Agents
123m 49s
1126.1s
Structured Extraction
1054.9s
153.78s
Coding
11m 15s
332m 48s
Grounded Answers
557.8s
382m 45s
Instruction Following
162m 44s
693m 47s
Business Logic
51m 2s
242m 40s
Security & permissions
101m 52s
331m 9s
Diagnosis & investigation
04m 12s
01m 19s
What you'd run
The build behind each score. Orange marks the faster, smaller, cheaper or longer-context side.
SpecALFM2.5 24B A2BBMistral Large 4
Speed
82 tok/s
56 tok/s
Machine
Apple M5 Pro, 48 GB
Hosted
Memory at 32K
25.0 GB
—
Context
128K
512K (better)
Cost per run
Not measured
$2.67
Cost per case
Not measured
$0.017
Time per case
1m 53s (better)
1m 56s
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