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Model comparison

o3-mini vs Qwen3.5 397B

Data verified

Head-to-head evidence from 8 shared benchmark results across 4 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.

OpenAI
46.59/100
Margin
9.7pts
winning →
56.26/100
2 category wins1 category wins

Public leaderboard positions: o3-mini #141 (Supported); Qwen3.5 397B #77 (Estimated). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.

Evidence parity. o3-mini and Qwen3.5 397B share 8 comparable benchmark results. 3 of 8 categories are comparable. 2 results are unique to o3-mini; 47 to Qwen3.5 397B.

Updated July 24, 2026
Shared results
8
o3-mini only
2
Qwen3.5 397B only
47
Comparable categories
3 / 8

Pick Qwen3.5 397B if you want the stronger benchmark profile. o3-mini only becomes the better choice if knowledge is the priority or you need the larger 200K context window.

Confidence note. This is a partial-evidence comparison with 8 shared benchmark results across 4 evidence categories; 3 of 8 categories currently have scoreable aggregates for both models. Treat the verdict as directional until coverage is more balanced.

Why this result

Qwen3.5 397B is clearly ahead on the BenchAlign aggregate, 56.26 to 46.59. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.

Qwen3.5 397B's sharpest advantage is in coding, where it averages 66.5 against 49.3. The single biggest benchmark swing on the page is SWE-bench Verified, 49.3% to 76.2%. 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 $0.60 input / $3.60 output per 1M tokens for Qwen3.5 397B. o3-mini is the reasoning model in the pair, while Qwen3.5 397B 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. o3-mini gives you the larger context window at 200K, compared with 128K for Qwen3.5 397B.

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 Qwen3.5 397B
Categoryo3-miniΔQwen3.5 397B
Knowledgeo3-mini77.2Margin 20.6Qwen3.5 397B56.6
Codingo3-mini49.3Margin 17.2Qwen3.5 397B66.5
Inst. Followingo3-mini93.9Margin 1.3Qwen3.5 397B92.6
Agentico3-miniNot measuredMarginNo overlapQwen3.5 397B56.5
Reasoningo3-miniNot measuredMarginNo overlapQwen3.5 397B63.2
Matho3-miniNot measuredMarginNo overlapQwen3.5 397B90.6
Multilingualo3-miniNot measuredMarginNo overlapQwen3.5 397B84.7
Multimodalo3-miniNot measuredMarginNo overlapQwen3.5 397B79.6

Decisive benchmark drivers

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

More
A · o3-miniB · Qwen3.5 397B
  1. SWE-bench Verified

    Coding
    Source ↗
    A 49.3%B 76.2%
    Winner: Qwen3.5 397BΔ 26.9
    SWE-bench Verified: o3-mini scored 49.3%; Qwen3.5 397B scored 76.2%. Qwen3.5 397B wins this benchmark.
  2. GPQA

    Knowledge
    Source ↗
    A 77.2%B 88.4%
    Winner: Qwen3.5 397BΔ 11.2
    GPQA: o3-mini scored 77.2%; Qwen3.5 397B scored 88.4%. Qwen3.5 397B wins this benchmark.
  3. IFEval

    Inst. Following
    Source ↗
    A 93.9%B 92.6%
    Winner: o3-miniΔ 1.3
    IFEval: o3-mini scored 93.9%; Qwen3.5 397B scored 92.6%. o3-mini wins this benchmark.

Operational comparison

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

Metrico3-miniQwen3.5 397BComparison
Input / output priceUSD per 1M tokenso3-mini$1.1 input / $4.4 outputQwen3.5 397B$0.6 input / $3.6 outputQwen3.5 397B has the lower combined listed price.
Generation speedtokens per secondo3-mini160 tok/sQwen3.5 397B96 tok/so3-mini has the higher measured throughput.
First-answer latencyseconds to first tokeno3-mini7.12 sQwen3.5 397B2.44 sQwen3.5 397B reaches the first token sooner.
Context windowmaximum listed tokenso3-mini200KQwen3.5 397B128Ko3-mini lists the larger context window.

Benchmark Deep Dive

Agentic
Benchmarko3-miniQwen3.5 397BResult
τ²-bench resultsSource 28.7%95.6%Qwen3.5 397B leads
Terminal-Bench 2.0Source 52.5%Not comparable
BrowseCompSource 62%Not comparable
Claw-EvalSource 56.8%Not comparable
QwenClawBenchSource 51.8%Not comparable
τ³-bench resultsSource 68.4%Not comparable
VITA-BenchSource 43.7%Not comparable
DeepPlanningSource 37.6%Not comparable
ToolathlonSource 36.3%Not comparable
MCP AtlasSource 46.1%Not comparable
MCP-TasksSource 74.2%Not comparable
WideResearchSource 74.0%Not comparable
Gert LabsSource 46.76%Not comparable
ResearchClawBenchSource 14.2%Not comparable
AA Agentic IndexSource 19.9%Not comparable
APEX-Agents-AASource 15.3%Not comparable
GDPval-AASource 23.1%Not comparable
GDPval-AASource 962Not comparable
CodingQwen3.5 397B wins
Benchmarko3-miniQwen3.5 397BResult
SWE-bench VerifiedSource 49.3%76.2%Qwen3.5 397B leads
AA-SciCodeSource 39.9%42.0%Qwen3.5 397B leads
LiveCodeBench v6Source 83.6%Not comparable
SWE-bench ProSource 50.9%Not comparable
AA Coding IndexSource 48.2%Not comparable
Reasoning
Benchmarko3-miniQwen3.5 397BResult
LongBench v2Source 63.2%Not comparable
AI-NeedleSource 68.7%Not comparable
AA-LCRSource 65.7%Not comparable
CritPtSource 1.7%Not comparable
Knowledgeo3-mini wins
Benchmarko3-miniQwen3.5 397BResult
MMLUSource 86.9%Not comparable
GPQASource 77.2%88.4%Qwen3.5 397B leads
Artificial Analysis Intelligence IndexSource 19.0%33.7%Qwen3.5 397B leads
AA-GPQA DiamondSource 74.8%89.3%Qwen3.5 397B leads
AA-HLESource 8.7%27.3%Qwen3.5 397B leads
SuperGPQASource 70.4%Not comparable
MMLU-ProSource 87.8%Not comparable
MMLU-ReduxSource 94.9%Not comparable
C-EvalSource 93%Not comparable
HLESource 28.7%Not comparable
AA-Omniscience IndexSource -29.8%Not comparable
AA-Omniscience AccuracySource 31.4%Not comparable
AA-Omniscience Hallucination RateSource 89.1%Not comparable
Math
Benchmarko3-miniQwen3.5 397BResult
AIME 2024Source 87.3%Not comparable
AIME26Source 93.3%Not comparable
HMMT Feb 2025Source 94.8%Not comparable
HMMT Nov 2025Source 92.7%Not comparable
HMMT Feb 2026Source 87.9%Not comparable
MMAnswerBenchSource 80.9%Not comparable
Multilingual
Benchmarko3-miniQwen3.5 397BResult
MMLU-ProXSource 84.7%Not comparable
NOVA-63Source 59.1%Not comparable
Multimodal
Benchmarko3-miniQwen3.5 397BResult
MMMU-ProSource 79%Not comparable
MathVisionSource 88.6%Not comparable
CharXivSource 80.8%Not comparable
VideoMMMUSource 84.7%Not comparable
ScreenSpot ProSource 65.6%Not comparable
V*Source 95.8%Not comparable
AA-MMMU-ProSource 77.3%Not comparable
Inst. Followingo3-mini wins
Benchmarko3-miniQwen3.5 397BResult
IFEvalSource 93.9%92.6%o3-mini leads
AA-IFBenchSource 78.8%Not comparable
Frequently Asked Questions (4)

Which is better, o3-mini or Qwen3.5 397B?

Qwen3.5 397B is ahead on BenchLM's BenchAlign leaderboard, 56.26 to 46.59. The biggest single separator in this matchup is SWE-bench Verified, where the scores are 49.3% and 76.2%.

Which is better for knowledge tasks, o3-mini or Qwen3.5 397B?

o3-mini has the edge for knowledge tasks in this comparison, averaging 77.2 versus 56.6. Inside this category, AA-HLE is the benchmark that creates the most daylight between them.

Which is better for coding, o3-mini or Qwen3.5 397B?

Qwen3.5 397B has the edge for coding in this comparison, averaging 66.5 versus 49.3. Inside this category, SWE-bench Verified is the benchmark that creates the most daylight between them.

Which is better for instruction following, o3-mini or Qwen3.5 397B?

o3-mini has the edge for instruction following in this comparison, averaging 93.9 versus 92.6. Inside this category, IFEval is the benchmark that creates the most daylight between them.

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Last updated: July 24, 2026