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DeepSeek-V3.2-Speciale vs MiMo-V2.6-Flash

MiMo-V2.6-Flash leads the LLM Stats Score 45.6 to 33.9. MiMo-V2.6-Flash is 1.8x cheaper per token.

DeepSeek · Xiaomi · Updated for 2026

Which is better?

MiMo-V2.6-Flash leads the overall LLM Stats Score 45.6 to 33.9, ranking #29 overall.

On price, MiMo-V2.6-Flash is roughly 1.8x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.

MiMo-V2.6-Flash also accepts a larger context window (1,048,576 input tokens), making it the stronger choice for long documents and large codebases.

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

Choose DeepSeek-V3.2-Speciale

  • you want predictable pricing at $0.28/M input and $0.42/M output

Choose MiMo-V2.6-Flash

  • overall performance matters — it scores 45.6 and ranks #29 on LLM Stats
  • your work emphasizes reasoning and coding — it leads those capability indexes
  • cost matters — it's about 1.8x cheaper per token
  • you process long inputs — it offers a 1,048,576 token context window
  • you want the most recent training data — it shipped Sep 2026

At a glance

The differences that matter most.

DeepSeek-V3.2-Speciale
DeepSeek
MiMo-V2.6-Flash
Xiaomi
Core performance indexes
LLM Stats Score
33.9
#99
45.6
#29
Reasoning
32.5
#106
42.5
#45
Coding
18.6
#114
36.7
#21
Agents
10.9
#115
33.1
#26
Cost, coverage & limits
Benchmark wins
—
—
Input price
$0.28 / M
$0.14 / M
Output price
$0.42 / M
$0.28 / M
Context window
131,072
1,048,576

Capability indexes

Additional strengths measured across groups of related public benchmarks

1 shared
Index
DeepSeek-V3.2-Speciale
MiMo-V2.6-Flash
Tool use
10.2#128
24.7#29
Conservative TrueSkill rating · higher is betterHow scores work

Individual benchmarks

8 reported for DeepSeek-V3.2-Speciale · 16 for MiMo-V2.6-Flash

No common benchmarks found

DeepSeek-V3.2-Speciale and MiMo-V2.6-Flashdon'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

Pricing Analysis

Price comparison per million tokens

MiMo-V2.6-Flash costs less

For input processing, DeepSeek-V3.2-Speciale ($0.28/1M tokens) is 2.0x more expensive than MiMo-V2.6-Flash ($0.14/1M tokens).

For output processing, DeepSeek-V3.2-Speciale ($0.42/1M tokens) is 1.5x more expensive than MiMo-V2.6-Flash ($0.28/1M tokens).

In conclusion, DeepSeek-V3.2-Speciale is more expensive than MiMo-V2.6-Flash.*

* Using a 3:1 ratio of input to output tokens

Lowest available price from all providers
Tue Sep 22 2026 • llm-stats.com
DeepSeek
DeepSeek-V3.2-Speciale
Input tokens$0.28
Output tokens$0.42
Best providerDeepSeek
Xiaomi
MiMo-V2.6-Flash
Input tokens$0.14
Output tokens$0.28
Best providerXiaomi
Notice missing or incorrect data?Start an Issue→

Model Size

Parameter count comparison

376.0B diff

DeepSeek-V3.2-Speciale has 376.0B more parameters than MiMo-V2.6-Flash, making it 121.7% larger.

DeepSeek
DeepSeek-V3.2-Speciale
685.0Bparameters
Xiaomi
MiMo-V2.6-Flash
309.0Bparameters
685.0B
DeepSeek-V3.2-Speciale
309.0B
MiMo-V2.6-Flash

Context Window

Maximum input and output token capacity

MiMo-V2.6-Flash accepts 1,048,576 input tokens compared to DeepSeek-V3.2-Speciale's 131,072 tokens. Only DeepSeek-V3.2-Speciale specifies output context (131,072 tokens).

DeepSeek
DeepSeek-V3.2-Speciale
Input131,072 tokens
Output131,072 tokens
Xiaomi
MiMo-V2.6-Flash
Input1,048,576 tokens
Output- tokens
Tue Sep 22 2026 • llm-stats.com

Input capabilities

Documented input modalities across available providers

MiMo-V2.6-Flash supports multimodal inputs, whereas DeepSeek-V3.2-Speciale does not.

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

DeepSeek-V3.2-Speciale

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-V3.2-Speciale

MIT

Open weights

MiMo-V2.6-Flash

MIT

Open weights

Release Timeline

When each model was launched

DeepSeek-V3.2-Speciale was released on 2025-12-01, while MiMo-V2.6-Flash was released on 2026-09-22.

MiMo-V2.6-Flash is 10 months newer than DeepSeek-V3.2-Speciale.

DeepSeek-V3.2-Speciale

Dec 1, 2025

9 months ago

MiMo-V2.6-Flash

Sep 22, 2026

-1 days ago

9mo 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

Provider Availability

DeepSeek-V3.2-Speciale is available from DeepSeek. MiMo-V2.6-Flash is available from Xiaomi.

DeepSeek-V3.2-Speciale

deepseek logo
DeepSeek
Input Price:Input: $0.28/1MOutput Price:Output: $0.42/1M

MiMo-V2.6-Flash

xiaomi logo
Xiaomi
Input Price:Input: $0.14/1MOutput Price:Output: $0.28/1M
* Prices shown are per million tokens

Outputs Comparison

Notice missing or incorrect data?Start an Issue discussion→

Judge for yourself.

Run your own prompts against DeepSeek-V3.2-Speciale and MiMo-V2.6-Flash side-by-side, then vote on the output you prefer.

DeepSeek-V3.2-Speciale
✓ Preferred
MiMo-V2.6-Flash
Open in Playground

FAQ

Common questions about DeepSeek-V3.2-Speciale vs MiMo-V2.6-Flash.

Which is better, DeepSeek-V3.2-Speciale or MiMo-V2.6-Flash?

MiMo-V2.6-Flash leads the LLM Stats Score 45.6 to 33.9. DeepSeek-V3.2-Speciale 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-V3.2-Speciale compare to MiMo-V2.6-Flash in benchmarks?

DeepSeek-V3.2-Speciale scores HMMT 2025: 99.2%, AIME 2025: 96.0%, CodeForces: 90.0%, t2-bench: 80.3%, SWE-Bench Verified: 73.1%. 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%.

Is DeepSeek-V3.2-Speciale cheaper than MiMo-V2.6-Flash?

MiMo-V2.6-Flash is 2.0x cheaper for input tokens. DeepSeek-V3.2-Speciale costs $0.28/M input and $0.42/M output via deepseek. MiMo-V2.6-Flash costs $0.14/M input and $0.28/M output via xiaomi.

What are the context window sizes for DeepSeek-V3.2-Speciale and MiMo-V2.6-Flash?

DeepSeek-V3.2-Speciale supports 131K tokens and MiMo-V2.6-Flash supports 1.0M tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.

What are the main differences between DeepSeek-V3.2-Speciale and MiMo-V2.6-Flash?

Key differences include LLM Stats Score (33.9 vs 45.6), context window (131K vs 1.0M), input pricing ($0.28 vs $0.14/M), multimodal support (no vs yes). See the full comparison above for benchmark-by-benchmark results.

Who makes DeepSeek-V3.2-Speciale and MiMo-V2.6-Flash?

DeepSeek-V3.2-Speciale is developed by DeepSeek and MiMo-V2.6-Flash is developed by Xiaomi.

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