The AI arena is free today

Open Superagent

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

DeepSeek-V4.1-Flash leads the LLM Stats Score 51.8 to 45.7.

DeepSeek · Xiaomi · Updated for 2026

Which is better?

DeepSeek-V4.1-Flash leads the overall LLM Stats Score 51.8 to 45.7, ranking #13 overall.

In the 8 individual benchmarks reported for both models, DeepSeek-V4.1-Flash wins 6; this is a narrower head-to-head signal than the composite indexes.

Based on current LLM Stats indexes, shared benchmarks, pricing, and model metadata for 2026.

Choose DeepSeek-V4.1-Flash

  • overall performance matters — it scores 51.8 and ranks #13 on LLM Stats
  • your work emphasizes coding and agents — it leads those capability indexes
  • you value its reported benchmark strengths — it wins 6 of 8 exact shared results

Choose MiMo-V2.6-Flash

  • you want the most recent training data — it shipped Sep 2026

At a glance

The differences that matter most.

DeepSeek-V4.1-Flash
DeepSeek
MiMo-V2.6-Flash
Xiaomi
Core performance indexes
LLM Stats Score
51.8
#13
45.7
#29
Reasoning
48.8
#19
43.2
#42
Coding
44.2
#5
36.6
#22
Agents
41.1
#4
33.3
#25
Cost, coverage & limits
Benchmark wins
6 of 8
2 of 8
Input price
$0.22 / M
— / M
Output price
$0.66 / M
— / M
Context window
1,040,000
—

Capability indexes

Additional strengths measured across groups of related public benchmarks

2 shared
Index
DeepSeek-V4.1-Flash
MiMo-V2.6-Flash
Tool use
34.8#2
28.1#22
Safety
24.7#3
13.8#14
Conservative TrueSkill rating · higher is betterHow scores work

Individual benchmarks

20 reported for DeepSeek-V4.1-Flash · 16 for MiMo-V2.6-Flash

8 shared

DeepSeek-V4.1-Flash outperforms in 6 benchmarks (Agents' Last Exam, DeepSWE 1.1, ExploitGym, SEC-bench Pro, Terminal-Bench 2.1, Terminal-Bench 4.0), while MiMo-V2.6-Flash is better at 2 benchmarks (CyberGym, Program Bench).

DeepSeek-V4.1-Flash shows notably better performance in the majority of benchmarks.

Tue Sep 22 2026 • llm-stats.com

Human preference

Blind head-to-head votes and playground preference scores

Model Size

Parameter count comparison

454.2B diff

DeepSeek-V4.1-Flash has 454.2B more parameters than MiMo-V2.6-Flash, making it 147.0% larger.

DeepSeek
DeepSeek-V4.1-Flash
763.2Bparameters
Xiaomi
MiMo-V2.6-Flash
309.0Bparameters
763.2B
DeepSeek-V4.1-Flash
309.0B
MiMo-V2.6-Flash

Context Window

Maximum input and output token capacity

Only DeepSeek-V4.1-Flash specifies input context (1,040,000 tokens). Only DeepSeek-V4.1-Flash specifies output context (393,216 tokens).

DeepSeek
DeepSeek-V4.1-Flash
Input1,040,000 tokens
Output393,216 tokens
Xiaomi
MiMo-V2.6-Flash
Input- tokens
Output- tokens
Tue Sep 22 2026 • llm-stats.com

Input capabilities

Documented input modalities across available providers

Both DeepSeek-V4.1-Flash and MiMo-V2.6-Flash support multimodal inputs.

They are both capable of processing various types of data, offering versatility in application.

DeepSeek-V4.1-Flash

Text
Images
Audio
Video

MiMo-V2.6-Flash

Text
Images
Audio
Video

License

Usage and distribution terms

Both models are licensed under MIT.

Both models share the same licensing terms, providing consistent usage rights.

DeepSeek-V4.1-Flash

MIT

Open weights

MiMo-V2.6-Flash

MIT

Open weights

Release Timeline

When each model was launched

DeepSeek-V4.1-Flash was released on 2026-09-10, while MiMo-V2.6-Flash was released on 2026-09-22.

MiMo-V2.6-Flash is 0 month newer than DeepSeek-V4.1-Flash.

DeepSeek-V4.1-Flash

Sep 10, 2026

1 weeks ago

MiMo-V2.6-Flash

Sep 22, 2026

-1 days ago

1w newer

Knowledge Cutoff

When training data ends

Neither model specifies a knowledge cutoff date.

Unable to compare the recency of their training data.

No cutoff dates available

Outputs Comparison

Notice missing or incorrect data?Start an Issue discussion→

Judge for yourself.

Run your own prompts against DeepSeek-V4.1-Flash and MiMo-V2.6-Flash side-by-side, then vote on the output you prefer.

DeepSeek-V4.1-Flash
✓ Preferred
MiMo-V2.6-Flash
Open in Playground

FAQ

Common questions about DeepSeek-V4.1-Flash vs MiMo-V2.6-Flash.

Which is better, DeepSeek-V4.1-Flash or MiMo-V2.6-Flash?

DeepSeek-V4.1-Flash leads the LLM Stats Score 51.8 to 45.7. DeepSeek-V4.1-Flash is made by DeepSeek and MiMo-V2.6-Flash is made by Xiaomi. The best choice depends on your use case — compare their capability indexes, individual benchmarks, pricing, and limits above.

How does DeepSeek-V4.1-Flash compare to MiMo-V2.6-Flash in benchmarks?

DeepSeek-V4.1-Flash scores CodeForces: 100.0%, GPQA: 90.9%, Terminal-Bench 2.1: 90.6%, BabyVision: 89.6%, CyberGym: 88.1%. MiMo-V2.6-Flash scores CyberGym: 95.1%, Terminal-Bench 2.1: 87.6%, OSWorld-Verified: 80.8%, MiMo Cyber Bench: 77.2%, Toolathlon-Verified: 73.6%.

What are the context window sizes for DeepSeek-V4.1-Flash and MiMo-V2.6-Flash?

DeepSeek-V4.1-Flash supports 1.0M tokens and MiMo-V2.6-Flash supports an unknown number of tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.

What are the main differences between DeepSeek-V4.1-Flash and MiMo-V2.6-Flash?

Key differences include LLM Stats Score (51.8 vs 45.7). See the full comparison above for benchmark-by-benchmark results.

Who makes DeepSeek-V4.1-Flash and MiMo-V2.6-Flash?

DeepSeek-V4.1-Flash is developed by DeepSeek and MiMo-V2.6-Flash is developed by Xiaomi.

Related comparisons