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Model comparison

DeepSeek V4 Pro Base vs Qwen3.6-27B

Data verified

Head-to-head evidence from 4 shared benchmark results across 1 category. Overall scores shown here use the public BenchAlign v5 ranking lane.

No comparison
53.82/100
1 category wins0 category wins

Public leaderboard positions: DeepSeek V4 Pro Base unranked (Not scored); Qwen3.6-27B #93 (Estimated). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.

Evidence parity. DeepSeek V4 Pro Base and Qwen3.6-27B share 4 comparable benchmark results. 1 of 8 categories are comparable. 20 results are unique to DeepSeek V4 Pro Base; 50 to Qwen3.6-27B.

Updated July 23, 2026
Shared results
4
DeepSeek V4 Pro Base only
20
Qwen3.6-27B only
50
Comparable categories
1 / 8

Treat this as a split decision. DeepSeek V4 Pro Base makes more sense if knowledge is the priority or you need the larger 1M context window; Qwen3.6-27B is the better fit if you want the stronger reasoning-first profile.

Confidence note. This is a partial-evidence comparison with 4 shared benchmark results across 1 evidence category; 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 V4 Pro Base and Qwen3.6-27B finish on the same BenchAlign overall score, so this is less about a single winner and more about where the edge shows up. The BenchAlign headline says tie; the benchmark table is where the real choice happens.

Qwen3.6-27B is the reasoning model in the pair, while DeepSeek V4 Pro Base 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. DeepSeek V4 Pro Base gives you the larger context window at 1M, compared with 262K for Qwen3.6-27B.

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 V4 Pro Base and Qwen3.6-27B
CategoryDeepSeek V4 Pro BaseΔQwen3.6-27B
KnowledgeDeepSeek V4 Pro Base66.4Margin 13.1Qwen3.6-27B53.3
AgenticDeepSeek V4 Pro BaseNot measuredMarginNo overlapQwen3.6-27B59.3
CodingDeepSeek V4 Pro BaseNot measuredMarginNo overlapQwen3.6-27B77.5
ReasoningDeepSeek V4 Pro Base51.5MarginNo overlapQwen3.6-27BNot measured
MathDeepSeek V4 Pro BaseNot measuredMarginNo overlapQwen3.6-27B89.2
MultimodalDeepSeek V4 Pro BaseNot measuredMarginNo overlapQwen3.6-27B76.7

Decisive benchmark drivers

The largest measured benchmark gaps in this matchup, with exact reported values.

More
A · DeepSeek V4 Pro BaseB · Qwen3.6-27B
  1. MMLU-Pro

    Knowledge
    Source ↗
    A 73.5%B 86.2%
    Winner: Qwen3.6-27BΔ 12.7
    MMLU-Pro: DeepSeek V4 Pro Base scored 73.5%; Qwen3.6-27B scored 86.2%. Qwen3.6-27B wins this benchmark.
  2. SuperGPQA

    Knowledge
    Source ↗
    A 53.9%B 66%
    Winner: Qwen3.6-27BΔ 12.1
    SuperGPQA: DeepSeek V4 Pro Base scored 53.9%; Qwen3.6-27B scored 66%. Qwen3.6-27B wins this benchmark.

Operational comparison

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

MetricDeepSeek V4 Pro BaseQwen3.6-27BComparison
Input / output priceUSD per 1M tokensDeepSeek V4 Pro BaseNot availableQwen3.6-27B$0 input / $0 outputA complete price comparison is not available.
Generation speedtokens per secondDeepSeek V4 Pro BaseNot availableQwen3.6-27BNot availableA complete speed comparison is not available.
First-answer latencyseconds to first tokenDeepSeek V4 Pro BaseNot availableQwen3.6-27BNot availableA complete latency comparison is not available.
Context windowmaximum listed tokensDeepSeek V4 Pro Base1MQwen3.6-27B262KDeepSeek V4 Pro Base lists the larger context window.

Benchmark Deep Dive

Agentic
BenchmarkDeepSeek V4 Pro BaseQwen3.6-27BResult
Terminal-Bench 2.0Source 59.3%Not comparable
Claw-EvalSource 72.4%Not comparable
QwenClawBenchSource 53.4%Not comparable
QwenWebBenchSource 1487Not comparable
AndroidWorldSource 70.3%Not comparable
AA Agentic IndexSource 27.0%Not comparable
τ²-bench resultsSource 94.2%Not comparable
GDPval-AASource 32.0%Not comparable
GDPval-AASource 1140Not comparable
Gert LabsSource 54.84%Not comparable
Coding
BenchmarkDeepSeek V4 Pro BaseQwen3.6-27BResult
BigCodeBenchSource 59.2%Not comparable
HumanEvalSource 76.8%Not comparable
SWE-bench VerifiedSource 77.2%Not comparable
SWE MultilingualSource 71.3%Not comparable
SWE-bench ProSource 53.5%Not comparable
Terminal-Bench 2.0Source 59.3%Not comparable
LiveCodeBenchSource 83.9%Not comparable
NL2RepoSource 36.2%Not comparable
AA Coding IndexSource 53.7%Not comparable
AA-SciCodeSource 39.8%Not comparable
Reasoning
BenchmarkDeepSeek V4 Pro BaseQwen3.6-27BResult
BBHSource 87.5%Not comparable
DROPSource 88.7%Not comparable
HellaSwagSource 88.0%Not comparable
WinoGrandeSource 81.5%Not comparable
CLUEWSCSource 85.2%Not comparable
LongBench v2Source 51.5%Not comparable
AA-LCRSource 68.7%Not comparable
CritPtSource 1.1%Not comparable
KnowledgeDeepSeek V4 Pro Base wins
BenchmarkDeepSeek V4 Pro BaseQwen3.6-27BResult
AGIEvalSource 83.1%Not comparable
MMLUSource 90.1%Not comparable
MMLU-ReduxSource 90.8%93.5%Qwen3.6-27B leads
MMLU-ProSource 73.5%86.2%Qwen3.6-27B leads
MMMLUSource 90.3%Not comparable
C-EvalSource 93.1%91.4%DeepSeek V4 Pro Base leads
CMMLUSource 90.8%Not comparable
MultiLoKoSource 51.1%Not comparable
SimpleQASource 55.2%Not comparable
SuperGPQASource 53.9%66%Qwen3.6-27B leads
FACTS ParametricSource 62.6%Not comparable
TriviaQASource 85.6%Not comparable
GPQASource 87.8%Not comparable
HLESource 24%Not comparable
Artificial Analysis Intelligence IndexSource 37.0%Not comparable
AA-GPQA DiamondSource 84.2%Not comparable
AA-HLESource 21.6%Not comparable
AA-Omniscience IndexSource -19.8%Not comparable
AA-Omniscience AccuracySource 19.2%Not comparable
AA-Omniscience Hallucination RateSource 48.3%Not comparable
Math
BenchmarkDeepSeek V4 Pro BaseQwen3.6-27BResult
GSM8KSource 92.6%Not comparable
MATHSource 64.5%Not comparable
CMathSource 90.9%Not comparable
HMMT Feb 2025Source 93.8%Not comparable
HMMT Nov 2025Source 90.7%Not comparable
HMMT Feb 2026Source 84.3%Not comparable
MMAnswerBenchSource 80.8%Not comparable
AIME26Source 94.1%Not comparable
Multilingual
BenchmarkDeepSeek V4 Pro BaseQwen3.6-27BResult
MGSMSource 84.4%Not comparable
Multimodal
BenchmarkDeepSeek V4 Pro BaseQwen3.6-27BResult
MMMUSource 82.9%Not comparable
MMMU-ProSource 75.8%Not comparable
RealWorldQASource 84.1%Not comparable
DynaMathSource 85.6%Not comparable
MStarSource 81.4%Not comparable
SimpleVQASource 56.1%Not comparable
CharXivSource 78.4%Not comparable
CC-OCRSource 81.2%Not comparable
CountBenchSource 97.8%Not comparable
RefCOCO (avg)Source 92.5%Not comparable
ERQASource 62.5%Not comparable
Video-MME (with subtitle)Source 87.7%Not comparable
VideoMMMUSource 84.4%Not comparable
MLVU (M-Avg)Source 86.6%Not comparable
V*Source 94.7%Not comparable
AA-MMMU-ProSource 74.6%Not comparable
Inst. Following
BenchmarkDeepSeek V4 Pro BaseQwen3.6-27BResult
AA-IFBenchSource 67.6%Not comparable
Frequently Asked Questions (2)

Which is better, DeepSeek V4 Pro Base or Qwen3.6-27B?

DeepSeek V4 Pro Base and Qwen3.6-27B are tied on the BenchAlign overall score, so the right pick depends on which category matters most for your use case.

Which is better for knowledge tasks, DeepSeek V4 Pro Base or Qwen3.6-27B?

DeepSeek V4 Pro Base has the edge for knowledge tasks in this comparison, averaging 66.4 versus 53.3. Inside this category, MMLU-Pro is the benchmark that creates the most daylight between them.

Self-host vs API cost

Estimates at 50,000 req/day · 1000 tokens/req average.

DeepSeek V4 Pro Base
API / mo$0
Self-host / moNot listed
Break-even
Proprietary model — self-hosting not applicable.
Qwen3.6-27B
API / mo$0
Self-host / mo$429
Break-even
Model the full break-even

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Last updated: July 23, 2026

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