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DeepSeek-V3.2 vs MiMo-V2.6-Pro

MiMo-V2.6-Pro leads the LLM Stats Score 50.0 to 33.2. DeepSeek-V3.2 is 1.9x cheaper per token.

DeepSeek · Xiaomi · Updated for 2026

Which is better?

MiMo-V2.6-Pro leads the overall LLM Stats Score 50.0 to 33.2, ranking #18 overall.

On price, DeepSeek-V3.2 is roughly 1.9x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.

MiMo-V2.6-Pro 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

  • cost matters — it's about 1.9x cheaper per token

Choose MiMo-V2.6-Pro

  • overall performance matters — it scores 50.0 and ranks #18 on LLM Stats
  • your work emphasizes reasoning and coding — it leads those capability indexes
  • 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
DeepSeek
MiMo-V2.6-Pro
Xiaomi
Core performance indexes
LLM Stats Score
33.2
#106
50.0
#18
Reasoning
33.2
#102
46.9
#26
Coding
22.9
#84
41.4
#11
Agents
12.0
#110
37.5
#12
Cost, coverage & limits
Benchmark wins
—
—
Input price
$0.26 / M
$0.43 / M
Output price
$0.38 / M
$0.87 / M
Context window
163,840
1,048,576

Capability indexes

Additional strengths measured across groups of related public benchmarks

1 shared
Index
DeepSeek-V3.2
MiMo-V2.6-Pro
Tool use
11.0#121
29.7#8
Conservative TrueSkill rating · higher is betterHow scores work

Individual benchmarks

17 reported for DeepSeek-V3.2 · 18 for MiMo-V2.6-Pro

No common benchmarks found

DeepSeek-V3.2 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

Pricing Analysis

Price comparison per million tokens

DeepSeek-V3.2 costs less

For input processing, DeepSeek-V3.2 ($0.26/1M tokens) is 1.7x cheaper than MiMo-V2.6-Pro ($0.43/1M tokens).

For output processing, DeepSeek-V3.2 ($0.38/1M tokens) is 2.3x cheaper than MiMo-V2.6-Pro ($0.87/1M tokens).

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

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

Lowest available price from all providers
Wed Sep 23 2026 • llm-stats.com
DeepSeek
DeepSeek-V3.2
Input tokens$0.26
Output tokens$0.38
Best providerDeepinfra
Xiaomi
MiMo-V2.6-Pro
Input tokens$0.43
Output tokens$0.87
Best providerXiaomi
Notice missing or incorrect data?Start an Issue→

Model Size

Parameter count comparison

335.0B diff

MiMo-V2.6-Pro has 335.0B more parameters than DeepSeek-V3.2, making it 48.9% larger.

DeepSeek
DeepSeek-V3.2
685.0Bparameters
Xiaomi
MiMo-V2.6-Pro
1.0Tparameters
685.0B
DeepSeek-V3.2
1020.0B
MiMo-V2.6-Pro

Context Window

Maximum input and output token capacity

MiMo-V2.6-Pro accepts 1,048,576 input tokens compared to DeepSeek-V3.2's 163,840 tokens. Only DeepSeek-V3.2 specifies output context (163,840 tokens).

DeepSeek
DeepSeek-V3.2
Input163,840 tokens
Output163,840 tokens
Xiaomi
MiMo-V2.6-Pro
Input1,048,576 tokens
Output- tokens
Wed Sep 23 2026 • llm-stats.com

Input capabilities

Documented input modalities across available providers

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

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

DeepSeek-V3.2

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-V3.2

MIT

Open weights

MiMo-V2.6-Pro

MIT

Open weights

Release Timeline

When each model was launched

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

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

DeepSeek-V3.2

Dec 1, 2025

9 months ago

MiMo-V2.6-Pro

Sep 22, 2026

0 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 is available from DeepInfra, Novita, Fireworks. MiMo-V2.6-Pro is available from Xiaomi.

DeepSeek-V3.2

deepinfra logo
Deepinfra
Input Price:Input: $0.26/1MOutput Price:Output: $0.38/1M
novita logo
Novita
Input Price:Input: $0.27/1MOutput Price:Output: $0.40/1M
fireworks logo
Fireworks
Input Price:Input: $0.56/1MOutput Price:Output: $1.68/1M

MiMo-V2.6-Pro

xiaomi logo
Xiaomi
Input Price:Input: $0.43/1MOutput Price:Output: $0.87/1M
* 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 and MiMo-V2.6-Pro side-by-side, then vote on the output you prefer.

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

FAQ

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

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

MiMo-V2.6-Pro leads the LLM Stats Score 50.0 to 33.2. DeepSeek-V3.2 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-V3.2 compare to MiMo-V2.6-Pro in benchmarks?

DeepSeek-V3.2 scores AIME 2025: 93.1%, HMMT 2025: 90.2%, MMLU-Pro: 85.0%, LiveCodeBench: 83.3%, GPQA: 82.4%. MiMo-V2.6-Pro scores CyberGym: 94.0%, Terminal-Bench 2.1: 89.9%, OSWorld-Verified: 82.0%, MiMo Cyber Bench: 81.7%, Toolathlon-Verified: 76.9%.

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

DeepSeek-V3.2 is 1.7x cheaper for input tokens. DeepSeek-V3.2 costs $0.26/M input and $0.38/M output via deepinfra. MiMo-V2.6-Pro costs $0.43/M input and $0.87/M output via xiaomi.

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

DeepSeek-V3.2 supports 164K tokens and MiMo-V2.6-Pro 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 and MiMo-V2.6-Pro?

Key differences include LLM Stats Score (33.2 vs 50.0), context window (164K vs 1.0M), input pricing ($0.26 vs $0.43/M), multimodal support (no vs yes). See the full comparison above for benchmark-by-benchmark results.

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

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

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