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Model comparison

DeepSeek V3.2 vs MiMo-V2-Flash

Data verified

Head-to-head evidence from 11 shared benchmark results across 5 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.

55.4/100
Margin
1.3pts
← winning
54.06/100
0 category wins1 category wins

Public leaderboard positions: DeepSeek V3.2 #82 (Supported); MiMo-V2-Flash #91 (Supported). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.

Evidence parity. DeepSeek V3.2 and MiMo-V2-Flash share 11 comparable benchmark results. 1 of 8 categories are comparable. 8 results are unique to DeepSeek V3.2; 8 to MiMo-V2-Flash.

Updated July 20, 2026
Shared results
11
DeepSeek V3.2 only
8
MiMo-V2-Flash only
8
Comparable categories
1 / 8

Pick DeepSeek V3.2 if you want the stronger benchmark profile. MiMo-V2-Flash only becomes the better choice if coding is the priority or you want the cheaper token bill.

Confidence note. This is a partial-evidence comparison with 11 shared benchmark results across 5 evidence categories; 1 of 8 categories currently have scoreable aggregates for both models. Treat the verdict as directional until coverage is more balanced.

Why this result

DeepSeek V3.2 has the cleaner BenchAlign overall profile here, landing at 55.4 versus 54.06. It is a real lead, but still close enough that category-level strengths matter more than the headline number.

DeepSeek V3.2 is also the more expensive model on tokens at $0.28 input / $0.42 output per 1M tokens, versus $0.00 input / $0.00 output per 1M tokens for MiMo-V2-Flash. That is roughly Infinityx on output cost alone. MiMo-V2-Flash is the reasoning model in the pair, while DeepSeek V3.2 is not. That usually helps on harder chain-of-thought-heavy tests, but it can also mean more latency and more token spend in real use. MiMo-V2-Flash gives you the larger context window at 256K, compared with 128K for DeepSeek V3.2.

Category breakdown

Exact category averages are shown below. Not measured means BenchLM does not have enough sourced public coverage for that model and category.

Category scores and score margins for DeepSeek V3.2 and MiMo-V2-Flash
CategoryDeepSeek V3.2ΔMiMo-V2-Flash
CodingDeepSeek V3.260.9Margin 12.5MiMo-V2-Flash73.4
KnowledgeDeepSeek V3.2Not measuredMarginNo overlapMiMo-V2-Flash84.7
MathDeepSeek V3.217.1MarginNo overlapMiMo-V2-FlashNot measured

Operational comparison

Runtime and commercial metrics are compared only when both models have a complete sourced value.

MetricDeepSeek V3.2MiMo-V2-FlashComparison
Input / output priceUSD per 1M tokensDeepSeek V3.2$0.28 input / $0.42 outputMiMo-V2-Flash$0 input / $0 outputMiMo-V2-Flash has the lower combined listed price.
Generation speedtokens per secondDeepSeek V3.235 tok/sMiMo-V2-Flash129 tok/sMiMo-V2-Flash has the higher measured throughput.
First-answer latencyseconds to first tokenDeepSeek V3.23.75 sMiMo-V2-Flash2.14 sMiMo-V2-Flash reaches the first token sooner.
Context windowmaximum listed tokensDeepSeek V3.2128KMiMo-V2-Flash256KMiMo-V2-Flash lists the larger context window.

Benchmark Deep Dive

Agentic
BenchmarkDeepSeek V3.2MiMo-V2-FlashResult
Claw-EvalSource 40.2%Not comparable
VITA-BenchSource 18.5%Not comparable
τ²-bench resultsSource 78.9%83.9%MiMo-V2-Flash leads
Gert LabsSource 29.57%Not comparable
AA Agentic IndexSource 12.0%Not comparable
GDPval-AASource 16.7%Not comparable
GDPval-AASource 833Not comparable
CodingMiMo-V2-Flash wins
BenchmarkDeepSeek V3.2MiMo-V2-FlashResult
SWE-RebenchSource 60.9%Not comparable
React Native EvalsSource 71.5%Not comparable
AA-SciCodeSource 38.7%25.9%DeepSeek V3.2 leads
SWE-bench VerifiedSource 73.4%Not comparable
AA Coding IndexSource 49.8%Not comparable
Reasoning
BenchmarkDeepSeek V3.2MiMo-V2-FlashResult
AA-LCRSource 39.0%31.3%DeepSeek V3.2 leads
CritPtSource 0.9%0.0%DeepSeek V3.2 leads
Knowledge
BenchmarkDeepSeek V3.2MiMo-V2-FlashResult
Artificial Analysis Intelligence IndexSource 24.7%24.7%MiMo-V2-Flash leads
AA-GPQA DiamondSource 75.1%65.6%DeepSeek V3.2 leads
AA-HLESource 10.5%8.0%DeepSeek V3.2 leads
AA-Omniscience IndexSource -46.7%-48.5%DeepSeek V3.2 leads
AA-Omniscience AccuracySource 24.2%15.2%DeepSeek V3.2 leads
AA-Omniscience Hallucination RateSource 93.5%75.1%MiMo-V2-Flash leads
GPQASource 83.7%Not comparable
MMLU-ProSource 84.9%Not comparable
Math
BenchmarkDeepSeek V3.2MiMo-V2-FlashResult
FrontierMath v2 (Tiers 1-3)Source 22.100%Not comparable
FrontierMath v2 (Tier 4)Source 2.100%Not comparable
AIME 2025Source 94.1%Not comparable
Multimodal
BenchmarkDeepSeek V3.2MiMo-V2-FlashResult
Design Arena WebsiteSource 1206Not comparable
Inst. Following
BenchmarkDeepSeek V3.2MiMo-V2-FlashResult
AA-IFBenchSource 49.0%39.9%DeepSeek V3.2 leads
Frequently Asked Questions (2)

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

DeepSeek V3.2 is ahead on BenchLM's BenchAlign leaderboard, 55.4 to 54.06.

Which is better for coding, DeepSeek V3.2 or MiMo-V2-Flash?

MiMo-V2-Flash has the edge for coding in this comparison, averaging 73.4 versus 60.9. Inside this category, AA-SciCode is the benchmark that creates the most daylight between them.

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Last updated: July 20, 2026

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