DeepSeek V4.1 Flash 1017 vs LFM2.5 24B A2B

Overall
56
vs
Overall
7

DeepSeek V4.1 Flash 1017 is clearly better. It wins 88 of the 89 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 1.8× as many thinking tokens per test case.

Thinking tokensAnswer tokens
TaskAB
Overall
5626.0s
5.3K, 91% thinking9.2K, 93% thinking
71m 53s
Agents
5826.7s
3.3K, 71% thinking18.5K, 98% thinking
123m 49s
Structured Extraction
8117.2s
4.2K, 93% thinking4.4K, 94% thinking
1054.9s
Coding
4840.8s
9.4K, 95% thinking6.1K, 68% thinking
11m 15s
Grounded Answers
7119.8s
4.4K, 91% thinking4.7K, 96% thinking
557.8s
Instruction Following
7625.6s
5.5K, 91% thinking13.4K, 97% thinking
162m 44s
Business Logic
6726.6s
6.6K, 97% thinking5K, 83% thinking
51m 2s
Security & permissions
4826.6s
4.7K, 87% thinking9K, 97% thinking
101m 52s
Diagnosis & investigation
020.2s
3.2K, 74% thinking19.9K, 98% thinking
04m 12s

What you'd run

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

SpecAB
Speed
243 tok/s
82 tok/s
Machine
Hosted
Apple M5 Pro, 48 GB
Memory at 32K
—
25.0 GB
Context
1M (better)
128K
Cost per run
$0.75
Not measured
Cost per case
$0.0049
Not measured
Time per case
26.0s (better)
1m 53s
Quantization
—
Q8_0
Harness
openrouter
llama.cpp

The race

No lead changes

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

DeepSeek V4.1 Flash 1017LFM2.5 24B A2B
025507510050100150Perfect run567

Every test case

153 test cases

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

88 won by DeepSeek V4.1 Flash 10171 won by LFM2.5 24B A2B64 tied