GPT-6 Luna vs LFM2.5 24B A2B
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 6.3× as many thinking tokens per test case.
TaskAGPT-6 LunaBLFM2.5 24B A2B
Overall
6149.1s
71m 53s
Agents
561m 18s
123m 49s
Structured Extraction
9514.5s
1054.9s
Coding
732m 18s
11m 15s
Grounded Answers
6715.6s
557.8s
Instruction Following
8432.3s
162m 44s
Business Logic
3743.1s
51m 2s
Security & permissions
6224.5s
101m 52s
Diagnosis & investigation
1737.7s
04m 12s
What you'd run
The build behind each score. Orange marks the faster, smaller, cheaper or longer-context side.
SpecAGPT-6 LunaBLFM2.5 24B A2B
Speed
90 tok/s
82 tok/s
Machine
Hosted
Apple M5 Pro, 48 GB
Memory at 32K
—
25.0 GB
Context
1.1M (better)
128K
Cost per run
$0.10
Not measured
Cost per case
$0.00067
Not measured
Time per case
49.1s (better)
1m 53s
Quantization
—
Q8_0
Harness
openrouter
llama.cpp
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