DeepSeek V4.1 Flash vs GPT-6 Luna

Overall
64
vs
Overall
61

Too close to call. DeepSeek V4.1 Flash wins 25 of the 43 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. DeepSeek V4.1 Flash spends 4.0× as many thinking tokens per test case.

Thinking tokensAnswer tokens
TaskAB
Overall
643m 35s
6K, 91% thinking1.9K, 73% thinking
6149.1s
Agents
464m 42s
6.1K, 82% thinking1.3K, 67% thinking
561m 18s
Structured Extraction
862m 8s
4.4K, 94% thinking999, 72% thinking
9514.5s
Coding
514m 55s
9.7K, 95% thinking3.6K, 60% thinking
732m 18s
Grounded Answers
762m 17s
3.9K, 90% thinking1.1K, 72% thinking
6715.6s
Instruction Following
894m 24s
7.5K, 94% thinking2K, 74% thinking
8432.3s
Business Logic
814m 1s
7K, 97% thinking3.2K, 93% thinking
3743.1s
Security & permissions
693m 3s
4.4K, 81% thinking1K, 68% thinking
6224.5s
Diagnosis & investigation
172m 8s
3.2K, 67% thinking1.1K, 68% thinking
1737.7s

What you'd run

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

SpecAB
Speed
30 tok/s
90 tok/s (better)
Machine
Hosted
Hosted
Memory at 32K
—
—
Context
1M
1.1M (better)
Cost per run
$0.39
$0.10 (better)
Cost per case
$0.0026
$0.00067 (better)
Time per case
3m 35s
49.1s (better)
Quantization
FP8
—
Harness
openrouter
openrouter

The race

5 lead changes

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

DeepSeek V4.1 FlashGPT-6 Luna
025507510050100150Perfect run6461

Every test case

153 test cases

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

25 won by DeepSeek V4.1 Flash18 won by GPT-6 Luna110 tied