LFM2.5 24B A2B vs Mistral Large 4

Overall
7
vs
Overall
28

Mistral Large 4 is clearly better. It wins 44 of the 48 test cases where they differ.

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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.

Thinking tokensAnswer tokens
TaskAB
Overall
71m 53s
9.2K, 93% thinking6.2K, 72% thinking
281m 56s
Agents
123m 49s
18.5K, 98% thinking795, no thinking
1126.1s
Structured Extraction
1054.9s
4.4K, 94% thinking288, no thinking
153.78s
Coding
11m 15s
6.1K, 68% thinking9.3K, 37% thinking
332m 48s
Grounded Answers
557.8s
4.7K, 96% thinking8.1K, 89% thinking
382m 45s
Instruction Following
162m 44s
13.4K, 97% thinking12.9K, 84% thinking
693m 47s
Business Logic
51m 2s
5K, 83% thinking8.8K, 77% thinking
242m 40s
Security & permissions
101m 52s
9K, 97% thinking3.7K, 83% thinking
331m 9s
Diagnosis & investigation
04m 12s
19.9K, 98% thinking4.4K, 85% thinking
01m 19s

What you'd run

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

SpecAB
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

3 lead changes

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

LFM2.5 24B A2BMistral Large 4
025507510050100150Perfect run728

Every test case

153 test cases

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

4 won by LFM2.5 24B A2B44 won by Mistral Large 4105 tied