LFM3 1.7B vs Claude Haiku 5.5

Overall
6
vs
Overall
70

Claude Haiku 5.5 is clearly better. It wins 110 of the 110 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. The time under each score is the average per test case, on the machine it ran on. LFM3 1.7B spends 2.9× as many thinking tokens per test case.

Thinking tokensAnswer tokens
TaskAB
Overall
62m 11s
13.5K, 66% thinking3.9K, 78% thinking
7025.5s
Agents
132m 40s
18.4K, 94% thinking3.7K, 61% thinking
6139.5s
Structured Extraction
01m 25s
10.1K, 41% thinking2.6K, 83% thinking
9013.5s
Coding
51m 21s
9.5K, 45% thinking6.8K, 76% thinking
8630.6s
Grounded Answers
01m 54s
9.8K, 65% thinking2.2K, 78% thinking
7613.9s
Instruction Following
144m 39s
23.1K, 68% thinking4.3K, 82% thinking
9431.5s
Business Logic
01m 37s
11.5K, 37% thinking5.5K, 95% thinking
6726.0s
Security & permissions
161m 48s
13K, 78% thinking2.7K, 70% thinking
6723.4s
Diagnosis & investigation
01m 36s
11.6K, 99% thinking2.3K, 50% thinking
1725.5s

What you'd run

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

SpecAB
Speed
104 tok/s
225 tok/s
Machine
Apple M5 Pro, 48 GB
Hosted
Memory at 32K
2.8 GB
—
Context
256K
1M (better)
Cost per run
Not measured
$0.42
Cost per case
Not measured
$0.0028
Time per case
2m 11s
25.5s (better)
Quantization
Q8_0
—
Harness
llama.cpp
openrouter

The race

No lead changes

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

LFM3 1.7BClaude Haiku 5.5
025507510050100150670

Every test case

153 test cases

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

0 won by LFM3 1.7B110 won by Claude Haiku 5.543 tied