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Model comparison

o4-mini (high) vs Qwen3.5 397B

Data verified

Head-to-head evidence from 0 shared benchmark results across 0 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.

No sourced benchmark result is currently shared by both models. This page therefore compares only the available metadata, pricing, and runtime rows; it does not name a quality winner.
49.98/100
Margin
7.0pts
winning →
57.01/100
0 category wins1 category wins

Public leaderboard positions: o4-mini (high) #118 (Estimated); Qwen3.5 397B #71 (Estimated). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.

Evidence parity. o4-mini (high) and Qwen3.5 397B share 0 comparable benchmark results. 1 of 8 categories are comparable. 2 results are unique to o4-mini (high); 55 to Qwen3.5 397B.

Updated July 22, 2026
Shared results
0
o4-mini (high) only
2
Qwen3.5 397B only
55
Comparable categories
1 / 8

Pick Qwen3.5 397B if you want the stronger benchmark profile. o4-mini (high) only becomes the better choice if you need the larger 200K context window or you want the stronger reasoning-first profile.

Confidence note. This is a partial-evidence comparison with 0 shared benchmark results across 0 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

Qwen3.5 397B is clearly ahead on the BenchAlign aggregate, 57.01 to 49.98. 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 mathematics, where it averages 90.6 against 20.2.

o4-mini (high) 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. o4-mini (high) gives you the larger context window at 200K, compared with 128K for Qwen3.5 397B.

Operational comparison

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

Metrico4-mini (high)Qwen3.5 397BComparison
Input / output priceUSD per 1M tokenso4-mini (high)Not availableQwen3.5 397B$0.6 input / $3.6 outputA complete price comparison is not available.
Generation speedtokens per secondo4-mini (high)161 tok/sQwen3.5 397B96 tok/so4-mini (high) has the higher measured throughput.
First-answer latencyseconds to first tokeno4-mini (high)21.94 sQwen3.5 397B2.44 sQwen3.5 397B reaches the first token sooner.
Context windowmaximum listed tokenso4-mini (high)200KQwen3.5 397B128Ko4-mini (high) lists the larger context window.

Benchmark Deep Dive

Agentic
Benchmarko4-mini (high)Qwen3.5 397BResult
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
τ²-bench resultsSource 95.6%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
Coding
Benchmarko4-mini (high)Qwen3.5 397BResult
SWE-bench VerifiedSource 76.2%Not comparable
LiveCodeBench v6Source 83.6%Not comparable
SWE-bench ProSource 50.9%Not comparable
AA-SciCodeSource 42.0%Not comparable
AA Coding IndexSource 48.2%Not comparable
Reasoning
Benchmarko4-mini (high)Qwen3.5 397BResult
LongBench v2Source 63.2%Not comparable
AI-NeedleSource 68.7%Not comparable
AA-LCRSource 65.7%Not comparable
CritPtSource 1.7%Not comparable
Knowledge
Benchmarko4-mini (high)Qwen3.5 397BResult
GPQASource 88.4%Not comparable
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
Artificial Analysis Intelligence IndexSource 33.7%Not comparable
AA-GPQA DiamondSource 89.3%Not comparable
AA-HLESource 27.3%Not comparable
AA-Omniscience IndexSource -29.8%Not comparable
AA-Omniscience AccuracySource 31.4%Not comparable
AA-Omniscience Hallucination RateSource 89.1%Not comparable
MathQwen3.5 397B wins
Benchmarko4-mini (high)Qwen3.5 397BResult
FrontierMath v2 (Tiers 1-3)Source 24.828%Not comparable
FrontierMath v2 (Tier 4)Source 6.250%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
Benchmarko4-mini (high)Qwen3.5 397BResult
MMLU-ProXSource 84.7%Not comparable
NOVA-63Source 59.1%Not comparable
Multimodal
Benchmarko4-mini (high)Qwen3.5 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. Following
Benchmarko4-mini (high)Qwen3.5 397BResult
IFEvalSource 92.6%Not comparable
AA-IFBenchSource 78.8%Not comparable
Frequently Asked Questions (2)

Which is better, o4-mini (high) or Qwen3.5 397B?

Qwen3.5 397B is ahead on BenchLM's BenchAlign leaderboard, 57.01 to 49.98.

Which is better for math, o4-mini (high) or Qwen3.5 397B?

Qwen3.5 397B has the edge for math in this comparison, averaging 90.6 versus 20.2. o4-mini (high) stays close enough that the answer can still flip depending on your workload.

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Last updated: July 22, 2026

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