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DeepSeek-V3.2 (Non-thinking) vs MiMo-V2.6-Flash

Comparing DeepSeek-V3.2 (Non-thinking) and MiMo-V2.6-Flash across benchmarks, pricing, and capabilities.

DeepSeek · Xiaomi · Updated for 2026

Which is better?

DeepSeek-V3.2 (Non-thinking) and MiMo-V2.6-Flash trade strengths across price, capabilities, and technical limits. The better choice depends on the workload.

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

Choose DeepSeek-V3.2 (Non-thinking)

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

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-V3.2 (Non-thinking)
DeepSeek
MiMo-V2.6-Flash
Xiaomi
Benchmark wins
—
—
Input price
$0.28 / M
— / M
Output price
$0.42 / M
— / M
Context window
131,072
—

Individual benchmarks

0 reported for DeepSeek-V3.2 (Non-thinking) · 16 for MiMo-V2.6-Flash

No common benchmarks found

DeepSeek-V3.2 (Non-thinking) 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

Model Size

Parameter count comparison

376.0B diff

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

DeepSeek
DeepSeek-V3.2 (Non-thinking)
685.0Bparameters
Xiaomi
MiMo-V2.6-Flash
309.0Bparameters
685.0B
DeepSeek-V3.2 (Non-thinking)
309.0B
MiMo-V2.6-Flash

Context Window

Maximum input and output token capacity

Only DeepSeek-V3.2 (Non-thinking) specifies input context (131,072 tokens). Only DeepSeek-V3.2 (Non-thinking) specifies output context (8,192 tokens).

DeepSeek
DeepSeek-V3.2 (Non-thinking)
Input131,072 tokens
Output8,192 tokens
Xiaomi
MiMo-V2.6-Flash
Input- tokens
Output- tokens
Mon Sep 21 2026 • llm-stats.com

Input capabilities

Documented input modalities across available providers

MiMo-V2.6-Flash supports multimodal inputs, whereas DeepSeek-V3.2 (Non-thinking) 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 (Non-thinking)

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 (Non-thinking)

MIT

Open weights

MiMo-V2.6-Flash

MIT

Open weights

Release Timeline

When each model was launched

DeepSeek-V3.2 (Non-thinking) 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 (Non-thinking).

DeepSeek-V3.2 (Non-thinking)

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

Outputs Comparison

Notice missing or incorrect data?Start an Issue discussion→

Judge for yourself.

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

DeepSeek-V3.2 (Non-thinking)
✓ Preferred
MiMo-V2.6-Flash
Open in Playground

FAQ

Common questions about DeepSeek-V3.2 (Non-thinking) vs MiMo-V2.6-Flash.

Which is better, DeepSeek-V3.2 (Non-thinking) or MiMo-V2.6-Flash?

DeepSeek-V3.2 (Non-thinking) (DeepSeek) and MiMo-V2.6-Flash (Xiaomi) each have strengths in different areas. Compare their benchmark scores, pricing, context windows, and capabilities above to determine which fits your needs.

How does DeepSeek-V3.2 (Non-thinking) compare to MiMo-V2.6-Flash in benchmarks?

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-V3.2 (Non-thinking) and MiMo-V2.6-Flash?

DeepSeek-V3.2 (Non-thinking) supports 131K 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-V3.2 (Non-thinking) and MiMo-V2.6-Flash?

Key differences include multimodal support (no vs yes). See the full comparison above for benchmark-by-benchmark results.

Who makes DeepSeek-V3.2 (Non-thinking) and MiMo-V2.6-Flash?

DeepSeek-V3.2 (Non-thinking) is developed by DeepSeek and MiMo-V2.6-Flash is developed by Xiaomi.

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