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Model comparison

Grok 4 vs Qwen3.6-27B

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.

60.42/100
Margin
6.6pts
← winning
53.82/100
0 category wins1 category wins

Public leaderboard positions: Grok 4 #50 (Supported); Qwen3.6-27B #93 (Estimated). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.

Evidence parity. Grok 4 and Qwen3.6-27B share 13 comparable benchmark results. 1 of 8 categories are comparable. 3 results are unique to Grok 4; 41 to Qwen3.6-27B.

Updated July 21, 2026
Shared results
13
Grok 4 only
3
Qwen3.6-27B only
41
Comparable categories
1 / 8

Pick Grok 4 if you want the stronger benchmark profile. Qwen3.6-27B only becomes the better choice if mathematics is the priority or you need the larger 262K context window.

Confidence note. This is a partial-evidence comparison with 13 shared benchmark results across 6 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

Grok 4 is clearly ahead on the BenchAlign aggregate, 60.42 to 53.82. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.

Qwen3.6-27B is the reasoning model in the pair, while Grok 4 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. Qwen3.6-27B gives you the larger context window at 262K, compared with 128K for Grok 4.

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 Grok 4 and Qwen3.6-27B
CategoryGrok 4ΔQwen3.6-27B
MathGrok 415.3Margin 73.9Qwen3.6-27B89.2
AgenticGrok 4Not measuredMarginNo overlapQwen3.6-27B59.3
CodingGrok 4Not measuredMarginNo overlapQwen3.6-27B77.5
KnowledgeGrok 4Not measuredMarginNo overlapQwen3.6-27B53.3
MultimodalGrok 4Not measuredMarginNo overlapQwen3.6-27B76.7

Operational comparison

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

MetricGrok 4Qwen3.6-27BComparison
Input / output priceUSD per 1M tokensGrok 4Not availableQwen3.6-27B$0 input / $0 outputA complete price comparison is not available.
Generation speedtokens per secondGrok 454 tok/sQwen3.6-27BNot availableA complete speed comparison is not available.
First-answer latencyseconds to first tokenGrok 415.60 sQwen3.6-27BNot availableA complete latency comparison is not available.
Context windowmaximum listed tokensGrok 4128KQwen3.6-27B262KQwen3.6-27B lists the larger context window.

Benchmark Deep Dive

Agentic
BenchmarkGrok 4Qwen3.6-27BResult
τ²-bench resultsSource 74.9%94.2%Qwen3.6-27B leads
Gert LabsSource 42.34%54.84%Qwen3.6-27B leads
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
GDPval-AASource 32.0%Not comparable
GDPval-AASource 1140Not comparable
Coding
BenchmarkGrok 4Qwen3.6-27BResult
React Native EvalsSource 72.6%Not comparable
AA-SciCodeSource 45.7%39.8%Grok 4 leads
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
Reasoning
BenchmarkGrok 4Qwen3.6-27BResult
AA-LCRSource 68.0%68.7%Qwen3.6-27B leads
CritPtSource 2.0%1.1%Grok 4 leads
Knowledge
BenchmarkGrok 4Qwen3.6-27BResult
Artificial Analysis Intelligence IndexSource 33.3%37.0%Qwen3.6-27B leads
AA-GPQA DiamondSource 87.7%84.2%Grok 4 leads
AA-HLESource 23.9%21.6%Grok 4 leads
AA-Omniscience IndexSource 3.8%-19.8%Grok 4 leads
AA-Omniscience AccuracySource 41.4%19.2%Grok 4 leads
AA-Omniscience Hallucination RateSource 64.2%48.3%Qwen3.6-27B leads
MMLU-ProSource 86.2%Not comparable
MMLU-ReduxSource 93.5%Not comparable
SuperGPQASource 66%Not comparable
C-EvalSource 91.4%Not comparable
GPQASource 87.8%Not comparable
HLESource 24%Not comparable
MathQwen3.6-27B wins
BenchmarkGrok 4Qwen3.6-27BResult
FrontierMath v2 (Tiers 1-3)Source 19.655%Not comparable
FrontierMath v2 (Tier 4)Source 2.083%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
Multimodal
BenchmarkGrok 4Qwen3.6-27BResult
AA-MMMU-ProSource 68.8%74.6%Qwen3.6-27B leads
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
Inst. Following
BenchmarkGrok 4Qwen3.6-27BResult
AA-IFBenchSource 53.7%67.6%Qwen3.6-27B leads
Frequently Asked Questions (2)

Which is better, Grok 4 or Qwen3.6-27B?

Grok 4 is ahead on BenchLM's BenchAlign leaderboard, 60.42 to 53.82.

Which is better for math, Grok 4 or Qwen3.6-27B?

Qwen3.6-27B has the edge for math in this comparison, averaging 89.2 versus 15.3. Grok 4 stays close enough that the answer can still flip depending on your workload.

Self-host vs API cost

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

Grok 4
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 21, 2026

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