DeepSeek-V3.2 (Thinking) vs MiMo-V2-Flash
DeepSeek-V3.2 (Thinking) and MiMo-V2-Flash are closely matched at 32.2 and 30.3 on the LLM Stats Score. MiMo-V2-Flash is 2.1x cheaper per token.
DeepSeek · Xiaomi · Updated for 2026
Which is better?
DeepSeek-V3.2 (Thinking) and MiMo-V2-Flash are closely matched on the overall LLM Stats Score at 32.2 and 30.3.
In the 9 individual benchmarks reported for both models, MiMo-V2-Flash wins 5; this is a narrower head-to-head signal than the composite indexes.
On price, MiMo-V2-Flash is roughly 2.1x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
MiMo-V2-Flash also accepts a larger context window (256,000 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 (Thinking)
- you want predictable pricing at $0.28/M input and $0.42/M output
Choose MiMo-V2-Flash
- you value its reported benchmark strengths — it wins 5 of 9 exact shared results
- cost matters — it's about 2.1x cheaper per token
- you process long inputs — it offers a 256,000 token context window
- you want the most recent training data — it shipped Dec 2025
At a glance
The differences that matter most.
Capability indexes
Additional strengths measured across groups of related public benchmarks
Individual benchmarks
14 reported for DeepSeek-V3.2 (Thinking) · 15 for MiMo-V2-Flash
DeepSeek-V3.2 (Thinking) outperforms in 4 benchmarks (HMMT 2025, Humanity's Last Exam, MMLU-Pro, Terminal-Bench 2.0), while MiMo-V2-Flash is better at 5 benchmarks (AIME 2025, BrowseComp, GPQA, SWE-bench Multilingual, SWE-Bench Verified).
MiMo-V2-Flash has a slight edge in benchmark performance.
Human preference
Blind head-to-head votes and playground preference scores
Pricing Analysis
Price comparison per million tokens
For input processing, DeepSeek-V3.2 (Thinking) ($0.28/1M tokens) is 2.8x more expensive than MiMo-V2-Flash ($0.10/1M tokens).
For output processing, DeepSeek-V3.2 (Thinking) ($0.42/1M tokens) is 1.4x more expensive than MiMo-V2-Flash ($0.30/1M tokens).
In conclusion, DeepSeek-V3.2 (Thinking) is more expensive than MiMo-V2-Flash.*
* Using a 3:1 ratio of input to output tokens
Model Size
Parameter count comparison
DeepSeek-V3.2 (Thinking) has 376.0B more parameters than MiMo-V2-Flash, making it 121.7% larger.
Context Window
Maximum input and output token capacity
MiMo-V2-Flash accepts 256,000 input tokens compared to DeepSeek-V3.2 (Thinking)'s 131,072 tokens. DeepSeek-V3.2 (Thinking) can generate longer responses up to 65,536 tokens, while MiMo-V2-Flash is limited to 16,384 tokens.
License
Usage and distribution terms
Both models are licensed under MIT.
Both models share the same licensing terms, providing consistent usage rights.
MIT
Open weights
MIT
Open weights
Release Timeline
When each model was launched
DeepSeek-V3.2 (Thinking) was released on 2025-12-01, while MiMo-V2-Flash was released on 2025-12-16.
MiMo-V2-Flash is 1 month newer than DeepSeek-V3.2 (Thinking).
Dec 1, 2025
10 months ago
Dec 16, 2025
10 months ago
2w newerKnowledge Cutoff
When training data ends
Neither model specifies a knowledge cutoff date.
Unable to compare the recency of their training data.
Provider Availability
DeepSeek-V3.2 (Thinking) is available from DeepSeek. MiMo-V2-Flash is available from Xiaomi.
DeepSeek-V3.2 (Thinking)
MiMo-V2-Flash
Outputs Comparison
Judge for yourself.
Run your own prompts against DeepSeek-V3.2 (Thinking) and MiMo-V2-Flash side-by-side, then vote on the output you prefer.
FAQ
Common questions about DeepSeek-V3.2 (Thinking) vs MiMo-V2-Flash.