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Model comparison

DeepSeek V3.2 vs Qwen3 Max

Data verified

Head-to-head evidence from 13 shared benchmark results across 6 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.

55.4/100
Margin
7.2pts
← winning
Alibaba
48.16/100
0 category wins0 category wins

Public leaderboard positions: DeepSeek V3.2 #82 (Supported); Qwen3 Max #128 (Estimated). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.

Evidence parity. DeepSeek V3.2 and Qwen3 Max share 13 comparable benchmark results. 0 of 8 categories are comparable. 6 results are unique to DeepSeek V3.2; 1 to Qwen3 Max.

Updated July 23, 2026
Shared results
13
DeepSeek V3.2 only
6
Qwen3 Max only
1
Comparable categories
0 / 8

Benchmark data for DeepSeek V3.2 and Qwen3 Max is coming soon on BenchLM.

Confidence note. This is a partial-evidence comparison with 13 shared benchmark results across 6 evidence categories; 0 of 8 categories currently have scoreable aggregates for both models. Treat the verdict as directional until coverage is more balanced.

Why this result

BenchLM has partial data for these models, but not enough overlapping benchmark coverage to produce a fair score-level comparison yet.

Qwen3 Max has the larger context window at 1M, 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 Qwen3 Max
CategoryDeepSeek V3.2ΔQwen3 Max
CodingDeepSeek V3.260.9MarginNo overlapQwen3 MaxNot measured
MathDeepSeek V3.217.1MarginNo overlapQwen3 MaxNot measured

Operational comparison

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

MetricDeepSeek V3.2Qwen3 MaxComparison
Input / output priceUSD per 1M tokensDeepSeek V3.2$0.28 input / $0.42 outputQwen3 MaxNot availableA complete price comparison is not available.
Generation speedtokens per secondDeepSeek V3.235 tok/sQwen3 MaxNot availableA complete speed comparison is not available.
First-answer latencyseconds to first tokenDeepSeek V3.23.75 sQwen3 MaxNot availableA complete latency comparison is not available.
Context windowmaximum listed tokensDeepSeek V3.2128KQwen3 Max1MQwen3 Max lists the larger context window.

Benchmark Deep Dive

Agentic
BenchmarkDeepSeek V3.2Qwen3 MaxResult
Claw-EvalSource 40.2%Not comparable
VITA-BenchSource 18.5%Not comparable
τ²-bench resultsSource 78.9%74.3%DeepSeek V3.2 leads
Gert LabsSource 29.57%43.74%Qwen3 Max leads
Coding
BenchmarkDeepSeek V3.2Qwen3 MaxResult
SWE-RebenchSource 60.9%Not comparable
React Native EvalsSource 71.5%Not comparable
AA-SciCodeSource 38.7%38.3%DeepSeek V3.2 leads
Vibe Code BenchSource 3.51%Not comparable
Reasoning
BenchmarkDeepSeek V3.2Qwen3 MaxResult
AA-LCRSource 39.0%46.7%Qwen3 Max leads
CritPtSource 0.9%0.0%DeepSeek V3.2 leads
Knowledge
BenchmarkDeepSeek V3.2Qwen3 MaxResult
Artificial Analysis Intelligence IndexSource 24.7%24.0%DeepSeek V3.2 leads
AA-GPQA DiamondSource 75.1%76.4%Qwen3 Max leads
AA-HLESource 10.5%11.1%Qwen3 Max leads
AA-Omniscience IndexSource -46.7%-43.1%Qwen3 Max leads
AA-Omniscience AccuracySource 24.2%24.4%Qwen3 Max leads
AA-Omniscience Hallucination RateSource 93.5%89.4%Qwen3 Max leads
Math
BenchmarkDeepSeek V3.2Qwen3 MaxResult
FrontierMath v2 (Tiers 1-3)Source 22.100%Not comparable
FrontierMath v2 (Tier 4)Source 2.100%Not comparable
Multimodal
BenchmarkDeepSeek V3.2Qwen3 MaxResult
Design Arena WebsiteSource 12041148DeepSeek V3.2 leads
Inst. Following
BenchmarkDeepSeek V3.2Qwen3 MaxResult
AA-IFBenchSource 49.0%44.1%DeepSeek V3.2 leads
Frequently Asked Questions (3)

Can I compare DeepSeek V3.2 and Qwen3 Max on BenchLM yet?

Not fully yet. BenchLM is tracking both models, but the sourced benchmark breakdown for this comparison is still coming soon.

Why does this comparison show “coming soon”?

BenchLM only shows category winners and benchmark-level calls when we have sourced results that can be compared fairly. For these models, the public benchmark coverage is not complete enough yet.

What data is available for DeepSeek V3.2 and Qwen3 Max today?

DeepSeek V3.2: $0.28 input / $0.42 output per 1M tokens Both model pages still include creator, context window, reasoning mode, and other metadata while benchmark coverage fills in.

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Last updated: July 23, 2026

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