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DeepSeek-V4-Flash-0731 vs MiMo-V2.6-Pro

DeepSeek-V4-Flash-0731 and MiMo-V2.6-Pro are closely matched at 44.3 and 49.8 on the LLM Stats Score.

DeepSeek · Xiaomi · Updated for 2026

Which is better?

DeepSeek-V4-Flash-0731 and MiMo-V2.6-Pro are closely matched on the overall LLM Stats Score at 44.3 and 49.8.

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

Choose DeepSeek-V4-Flash-0731

  • you want predictable pricing at $0.06/M input and $0.18/M output

Choose MiMo-V2.6-Pro

  • your work emphasizes coding and agents — it leads those capability indexes
  • you want the most recent training data — it shipped Sep 2026

At a glance

The differences that matter most.

DeepSeek-V4-Flash-0731
DeepSeek
MiMo-V2.6-Pro
Xiaomi
Core performance indexes
LLM Stats Score
44.3
#39
49.8
#19
Reasoning
41.8
#48
45.2
#30
Coding
32.4
#41
41.8
#9
Agents
30.6
#35
37.5
#13
Cost, coverage & limits
Benchmark wins
—
—
Input price
$0.06 / M
— / M
Output price
$0.18 / M
— / M
Context window
1,048,576
—

Capability indexes

Additional strengths measured across groups of related public benchmarks

1 shared
Index
DeepSeek-V4-Flash-0731
MiMo-V2.6-Pro
Tool use
22.8#41
28.0#21
Conservative TrueSkill rating · higher is betterHow scores work

Individual benchmarks

9 reported for DeepSeek-V4-Flash-0731 · 3 for MiMo-V2.6-Pro

No common benchmarks found

DeepSeek-V4-Flash-0731 and MiMo-V2.6-Prodon't have any common benchmark datasets to compare. They may have been evaluated on different testing suites.

Human preference

Blind head-to-head votes and playground preference scores

Model Size

Parameter count comparison

716.0B diff

MiMo-V2.6-Pro has 716.0B more parameters than DeepSeek-V4-Flash-0731, making it 235.5% larger.

DeepSeek
DeepSeek-V4-Flash-0731
304.0Bparameters
Xiaomi
MiMo-V2.6-Pro
1.0Tparameters
304.0B
DeepSeek-V4-Flash-0731
1020.0B
MiMo-V2.6-Pro

Context Window

Maximum input and output token capacity

Only DeepSeek-V4-Flash-0731 specifies input context (1,048,576 tokens). Only DeepSeek-V4-Flash-0731 specifies output context (1,048,576 tokens).

DeepSeek
DeepSeek-V4-Flash-0731
Input1,048,576 tokens
Output1,048,576 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

MiMo-V2.6-Pro supports multimodal inputs, whereas DeepSeek-V4-Flash-0731 does not.

MiMo-V2.6-Pro can handle both text and other forms of data like images, making it suitable for multimodal applications.

DeepSeek-V4-Flash-0731

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-Flash-0731

MIT

Open weights

MiMo-V2.6-Pro

MIT

Open weights

Release Timeline

When each model was launched

DeepSeek-V4-Flash-0731 was released on 2026-07-31, while MiMo-V2.6-Pro was released on 2026-09-22.

MiMo-V2.6-Pro is 2 months newer than DeepSeek-V4-Flash-0731.

DeepSeek-V4-Flash-0731

Jul 31, 2026

1 months ago

MiMo-V2.6-Pro

Sep 22, 2026

-1 days ago

1mo 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-Flash-0731 and MiMo-V2.6-Pro side-by-side, then vote on the output you prefer.

DeepSeek-V4-Flash-0731
✓ Preferred
MiMo-V2.6-Pro
Open in Playground

FAQ

Common questions about DeepSeek-V4-Flash-0731 vs MiMo-V2.6-Pro.

Which is better, DeepSeek-V4-Flash-0731 or MiMo-V2.6-Pro?

DeepSeek-V4-Flash-0731 and MiMo-V2.6-Pro are closely matched on the LLM Stats Score at 44.3 and 49.8. DeepSeek-V4-Flash-0731 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-Flash-0731 compare to MiMo-V2.6-Pro in benchmarks?

DeepSeek-V4-Flash-0731 scores Terminal-Bench 2.1: 82.7%, CyberGym: 76.7%, Toolathlon: 70.3%, DSBench-FullStack: 68.7%, DSBench-Hard: 59.6%. 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-Flash-0731 and MiMo-V2.6-Pro?

DeepSeek-V4-Flash-0731 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-Flash-0731 and MiMo-V2.6-Pro?

Key differences include LLM Stats Score (44.3 vs 49.8), multimodal support (no vs yes). See the full comparison above for benchmark-by-benchmark results.

Who makes DeepSeek-V4-Flash-0731 and MiMo-V2.6-Pro?

DeepSeek-V4-Flash-0731 is developed by DeepSeek and MiMo-V2.6-Pro is developed by Xiaomi.

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