DeepSeek V4.1 Flash vs MiMo-V2.6-Pro

Overall
64
vs
Overall
48

DeepSeek V4.1 Flash is clearly better. It wins 38 of the 47 test cases where they differ.

Learn to build evals like this in the AI Engineering Academy

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. Both models spend about the same on thinking per test case.

Thinking tokensAnswer tokens
TaskAB
Overall
643m 35s
6K, 91% thinking5.9K, 89% thinking
482m 13s
Agents
464m 42s
6.1K, 82% thinking8.7K, 84% thinking
474m 48s
Structured Extraction
862m 8s
4.4K, 94% thinking3.4K, 87% thinking
601m 26s
Coding
514m 55s
9.7K, 95% thinking10.7K, 95% thinking
242m 58s
Grounded Answers
762m 17s
3.9K, 90% thinking3.2K, 89% thinking
621m 9s
Instruction Following
894m 24s
7.5K, 94% thinking4.5K, 86% thinking
591m 23s
Business Logic
814m 1s
7K, 97% thinking7.1K, 92% thinking
571m 52s
Security & permissions
693m 3s
4.4K, 81% thinking3.6K, 86% thinking
711m 41s
Diagnosis & investigation
172m 8s
3.2K, 67% thinking6.2K, 86% thinking
02m 54s

What you'd run

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

SpecAB
Speed
30 tok/s
55 tok/s (better)
Machine
Hosted
Hosted
Memory at 32K
—
—
Context
1M
1.1M (better)
Cost per run
$0.39 (better)
$1.80
Cost per case
$0.0026 (better)
$0.012
Time per case
3m 35s
2m 13s (better)
Quantization
FP8
BF16
Harness
openrouter
openrouter

The race

3 lead changes

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

DeepSeek V4.1 FlashMiMo-V2.6-Pro
025507510050100150Perfect run6448

Every test case

153 test cases

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

38 won by DeepSeek V4.1 Flash9 won by MiMo-V2.6-Pro106 tied