Flint vs GPT-6 Luna
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. Flint spends 7.2× as many thinking tokens per test case.
TaskAFlintBGPT-6 Luna
Overall
211m 17s
6149.1s
Agents
1447.7s
561m 18s
Structured Extraction
291m 17s
9514.5s
Coding
141m 19s
732m 18s
Grounded Answers
2957.7s
6715.6s
Instruction Following
352m 28s
8432.3s
Business Logic
101m 20s
3743.1s
Security & permissions
3552.6s
6224.5s
Diagnosis & investigation
057.0s
1737.7s
What you'd run
The build behind each score. Orange marks the faster, smaller, cheaper or longer-context side.
SpecAFlintBGPT-6 Luna
Speed
149 tok/s (better)
90 tok/s
Machine
Hosted
Hosted
Memory at 32K
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Context
256K
1.1M (better)
Cost per run
Not measured
$0.10
Cost per case
Not measured
$0.00067
Time per case
1m 17s
49.1s (better)
Quantization
BF16
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Harness
openrouter
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