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

DeepSeek-V4.1-Flash and MiMo-V2.6-Pro are closely matched at 51.8 and 40.6 on the LLM Stats Score.

DeepSeek · Xiaomi · Updated for 2026

Which is better?

DeepSeek-V4.1-Flash and MiMo-V2.6-Pro are closely matched on the overall LLM Stats Score at 51.8 and 40.6.

The models split the 2 individual benchmarks reported for both models evenly.

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

Choose DeepSeek-V4.1-Flash

  • your work emphasizes agents — it leads those capability indexes

Choose MiMo-V2.6-Pro

  • 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-Pro
Xiaomi
Core performance indexes
LLM Stats Score
51.8
#13
40.6
#57
Coding
44.2
#5
34.1
#35
Agents
41.1
#4
29.9
#38
Cost, coverage & limits
Benchmark wins
1 of 2
1 of 2
Input price
$0.22 / M
— / M
Output price
$0.66 / M
— / M
Context window
1,040,000
—

Individual benchmarks

20 reported for DeepSeek-V4.1-Flash · 3 for MiMo-V2.6-Pro

2 shared

DeepSeek-V4.1-Flash outperforms in 1 benchmarks (DeepSWE 1.1), while MiMo-V2.6-Pro is better at 1 benchmark (Program Bench).

Both models are evenly matched across the benchmarks.

Tue Sep 22 2026 • llm-stats.com

Human preference

Blind head-to-head votes and playground preference scores

Model Size

Parameter count comparison

256.8B diff

MiMo-V2.6-Pro has 256.8B more parameters than DeepSeek-V4.1-Flash, making it 33.6% larger.

DeepSeek
DeepSeek-V4.1-Flash
763.2Bparameters
Xiaomi
MiMo-V2.6-Pro
1.0Tparameters
763.2B
DeepSeek-V4.1-Flash
1020.0B
MiMo-V2.6-Pro

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-Pro
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-Pro 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-Pro

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-Pro

MIT

Open weights

Release Timeline

When each model was launched

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

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

DeepSeek-V4.1-Flash

Sep 10, 2026

1 weeks ago

MiMo-V2.6-Pro

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-Pro side-by-side, then vote on the output you prefer.

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

FAQ

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

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

DeepSeek-V4.1-Flash and MiMo-V2.6-Pro are closely matched on the LLM Stats Score at 51.8 and 40.6. DeepSeek-V4.1-Flash is made by DeepSeek and MiMo-V2.6-Pro 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-Pro 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-Pro scores DeepSWE 1.1: 71.9%, MiMo Coding Bench: 63.2%, Program Bench: 26.5%.

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

DeepSeek-V4.1-Flash supports 1.0M tokens and MiMo-V2.6-Pro 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-Pro?

Key differences include LLM Stats Score (51.8 vs 40.6). See the full comparison above for benchmark-by-benchmark results.

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

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

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