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Model comparison

o3-mini vs Qwen3.6-27B

Data verified

Head-to-head evidence from 7 shared benchmark results across 3 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.

OpenAI
47.41/100
Margin
6.4pts
winning →
53.82/100
1 category wins1 category wins

Public leaderboard positions: o3-mini #136 (Supported); Qwen3.6-27B #93 (Estimated). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.

Evidence parity. o3-mini and Qwen3.6-27B share 7 comparable benchmark results. 2 of 8 categories are comparable. 3 results are unique to o3-mini; 47 to Qwen3.6-27B.

Updated July 21, 2026
Shared results
7
o3-mini only
3
Qwen3.6-27B only
47
Comparable categories
2 / 8

Pick Qwen3.6-27B if you want the stronger benchmark profile. o3-mini only becomes the better choice if knowledge is the priority.

Confidence note. This is a partial-evidence comparison with 7 shared benchmark results across 3 evidence categories; 2 of 8 categories currently have scoreable aggregates for both models. Treat the verdict as directional until coverage is more balanced.

Why this result

Qwen3.6-27B is clearly ahead on the BenchAlign aggregate, 53.82 to 47.41. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.

Qwen3.6-27B's sharpest advantage is in coding, where it averages 77.5 against 49.3. The single biggest benchmark swing on the page is SWE-bench Verified, 49.3% to 77.2%. o3-mini does hit back in knowledge, so the answer changes if that is the part of the workload you care about most.

o3-mini is also the more expensive model on tokens at $1.10 input / $4.40 output per 1M tokens, versus $0.00 input / $0.00 output per 1M tokens for Qwen3.6-27B. That is roughly Infinityx on output cost alone. Qwen3.6-27B gives you the larger context window at 262K, compared with 200K for o3-mini.

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 o3-mini and Qwen3.6-27B
Categoryo3-miniΔQwen3.6-27B
Codingo3-mini49.3Margin 28.2Qwen3.6-27B77.5
Knowledgeo3-mini77.2Margin 23.9Qwen3.6-27B53.3
Agentico3-miniNot measuredMarginNo overlapQwen3.6-27B59.3
Matho3-miniNot measuredMarginNo overlapQwen3.6-27B89.2
Multimodalo3-miniNot measuredMarginNo overlapQwen3.6-27B76.7
Inst. Followingo3-mini93.9MarginNo overlapQwen3.6-27BNot measured

Decisive benchmark drivers

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

More
A · o3-miniB · Qwen3.6-27B
  1. SWE-bench Verified

    Coding
    Source ↗
    A 49.3%B 77.2%
    Winner: Qwen3.6-27BΔ 27.9
    SWE-bench Verified: o3-mini scored 49.3%; Qwen3.6-27B scored 77.2%. Qwen3.6-27B wins this benchmark.
  2. GPQA

    Knowledge
    Source ↗
    A 77.2%B 87.8%
    Winner: Qwen3.6-27BΔ 10.6
    GPQA: o3-mini scored 77.2%; Qwen3.6-27B scored 87.8%. Qwen3.6-27B wins this benchmark.

Operational comparison

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

Metrico3-miniQwen3.6-27BComparison
Input / output priceUSD per 1M tokenso3-mini$1.1 input / $4.4 outputQwen3.6-27B$0 input / $0 outputQwen3.6-27B has the lower combined listed price.
Generation speedtokens per secondo3-mini160 tok/sQwen3.6-27BNot availableA complete speed comparison is not available.
First-answer latencyseconds to first tokeno3-mini7.12 sQwen3.6-27BNot availableA complete latency comparison is not available.
Context windowmaximum listed tokenso3-mini200KQwen3.6-27B262KQwen3.6-27B lists the larger context window.

Benchmark Deep Dive

Agentic
Benchmarko3-miniQwen3.6-27BResult
τ²-bench resultsSource 28.7%94.2%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
Gert LabsSource 54.84%Not comparable
CodingQwen3.6-27B wins
Benchmarko3-miniQwen3.6-27BResult
SWE-bench VerifiedSource 49.3%77.2%Qwen3.6-27B leads
AA-SciCodeSource 39.9%39.8%o3-mini leads
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
Benchmarko3-miniQwen3.6-27BResult
AA-LCRSource 68.7%Not comparable
CritPtSource 1.1%Not comparable
Knowledgeo3-mini wins
Benchmarko3-miniQwen3.6-27BResult
MMLUSource 86.9%Not comparable
GPQASource 77.2%87.8%Qwen3.6-27B leads
Artificial Analysis Intelligence IndexSource 19.0%37.0%Qwen3.6-27B leads
AA-GPQA DiamondSource 74.8%84.2%Qwen3.6-27B leads
AA-HLESource 8.7%21.6%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
HLESource 24%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
Benchmarko3-miniQwen3.6-27BResult
AIME 2024Source 87.3%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
Benchmarko3-miniQwen3.6-27BResult
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
Benchmarko3-miniQwen3.6-27BResult
IFEvalSource 93.9%Not comparable
AA-IFBenchSource 67.6%Not comparable
Frequently Asked Questions (3)

Which is better, o3-mini or Qwen3.6-27B?

Qwen3.6-27B is ahead on BenchLM's BenchAlign leaderboard, 53.82 to 47.41. The biggest single separator in this matchup is SWE-bench Verified, where the scores are 49.3% and 77.2%.

Which is better for knowledge tasks, o3-mini or Qwen3.6-27B?

o3-mini has the edge for knowledge tasks in this comparison, averaging 77.2 versus 53.3. Inside this category, Artificial Analysis Intelligence Index is the benchmark that creates the most daylight between them.

Which is better for coding, o3-mini or Qwen3.6-27B?

Qwen3.6-27B has the edge for coding in this comparison, averaging 77.5 versus 49.3. Inside this category, SWE-bench Verified 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.

o3-mini
API / mo$4,125
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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