DeepSeek V4.1 Flash 1017 vs Mellum2.1 Thinking

Overall
56
vs
Overall
9

DeepSeek V4.1 Flash 1017 is clearly better. It wins 86 of the 87 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. Mellum2.1 Thinking spends 1.3× as many thinking tokens per test case.

Thinking tokensAnswer tokens
TaskAB
Overall
5626.0s
5.3K, 91% thinking10.3K, 63% thinking
91m 56s
Agents
5826.7s
3.3K, 71% thinking10.8K, 93% thinking
92m 3s
Structured Extraction
8117.2s
4.2K, 93% thinking8.3K, 51% thinking
51m 36s
Coding
4840.8s
9.4K, 95% thinking11.3K, 38% thinking
52m 11s
Grounded Answers
7119.8s
4.4K, 91% thinking7.3K, 62% thinking
131m 24s
Instruction Following
7625.6s
5.5K, 91% thinking17.3K, 63% thinking
283m 10s
Business Logic
6726.6s
6.6K, 97% thinking9K, 50% thinking
01m 39s
Security & permissions
4826.6s
4.7K, 87% thinking9.1K, 75% thinking
81m 40s
Diagnosis & investigation
020.2s
3.2K, 74% thinking6.8K, 98% thinking
01m 15s

What you'd run

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

SpecAB
Speed
243 tok/s
90 tok/s
Machine
Hosted
Apple M5 Pro, 48 GB
Memory at 32K
—
12.9 GB
Context
1M (better)
128K
Cost per run
$0.75 (better)
$2.46 est.
Cost per case
$0.0049 (better)
$0.016 est.
Time per case
26.0s (better)
1m 56s
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 1017Mellum2.1 Thinking
025507510050100150Perfect run569

Every test case

153 test cases

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

86 won by DeepSeek V4.1 Flash 10171 won by Mellum2.1 Thinking66 tied