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Model comparison

GPT-4.1 mini vs Qwen2.5-VL-32B

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.
43.1/100
No comparison
N/A
0 category wins0 category wins

Public leaderboard positions: GPT-4.1 mini #160 (Estimated); Qwen2.5-VL-32B #184 (Estimated). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.

Evidence parity. GPT-4.1 mini and Qwen2.5-VL-32B share 0 comparable benchmark results. 0 of 8 categories are comparable. 22 results are unique to GPT-4.1 mini; 0 to Qwen2.5-VL-32B.

Updated July 24, 2026
Shared results
0
GPT-4.1 mini only
22
Qwen2.5-VL-32B only
0
Comparable categories
0 / 8

Benchmark data for GPT-4.1 mini and Qwen2.5-VL-32B is coming soon on BenchLM.

Confidence note. This is a partial-evidence comparison with 0 shared benchmark results across 0 evidence categories; 0 of 8 categories currently have scoreable aggregates for both models. Treat the verdict as directional until coverage is more balanced.

Why this result

BenchLM does not have sourced benchmark coverage for Qwen2.5-VL-32B yet. This comparison is currently limited to metadata such as context window, reasoning mode, and pricing where available.

GPT-4.1 mini is priced at $0.40 input / $1.60 output per 1M tokens, versus $0.00 input / $0.00 output per 1M tokens for Qwen2.5-VL-32B. GPT-4.1 mini has the larger context window at 1M, compared with 32K for Qwen2.5-VL-32B.

Operational comparison

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

MetricGPT-4.1 miniQwen2.5-VL-32BComparison
Input / output priceUSD per 1M tokensGPT-4.1 mini$0.4 input / $1.6 outputQwen2.5-VL-32B$0 input / $0 outputQwen2.5-VL-32B has the lower combined listed price.
Generation speedtokens per secondGPT-4.1 mini80 tok/sQwen2.5-VL-32BNot availableA complete speed comparison is not available.
First-answer latencyseconds to first tokenGPT-4.1 mini0.76 sQwen2.5-VL-32BNot availableA complete latency comparison is not available.
Context windowmaximum listed tokensGPT-4.1 mini1MQwen2.5-VL-32B32KGPT-4.1 mini lists the larger context window.

Benchmark Deep Dive

Agentic
BenchmarkGPT-4.1 miniQwen2.5-VL-32BResult
AA Agentic IndexSource 1.7%Not comparable
τ²-bench resultsSource 52.9%Not comparable
GDPval-AASource 0.4%Not comparable
GDPval-AASource 508Not comparable
Coding
BenchmarkGPT-4.1 miniQwen2.5-VL-32BResult
SWE-bench VerifiedSource 23.6%Not comparable
AA Coding IndexSource 20.2%Not comparable
AA-SciCodeSource 40.4%Not comparable
Reasoning
BenchmarkGPT-4.1 miniQwen2.5-VL-32BResult
AA-LCRSource 42.3%Not comparable
CritPtSource 0.0%Not comparable
Knowledge
BenchmarkGPT-4.1 miniQwen2.5-VL-32BResult
MMLUSource 87.5%Not comparable
GPQASource 64.2%Not comparable
Artificial Analysis Intelligence IndexSource 14.8%Not comparable
AA-GPQA DiamondSource 66.4%Not comparable
AA-HLESource 4.6%Not comparable
AA-Omniscience IndexSource -50.1%Not comparable
AA-Omniscience AccuracySource 17.5%Not comparable
AA-Omniscience Hallucination RateSource 82.0%Not comparable
Math
BenchmarkGPT-4.1 miniQwen2.5-VL-32BResult
FrontierMath v2 (Tiers 1-3)Source 4.483%Not comparable
Multimodal
BenchmarkGPT-4.1 miniQwen2.5-VL-32BResult
AA-MMMU-ProSource 58.7%Not comparable
Design Arena WebsiteSource 1027Not comparable
Inst. Following
BenchmarkGPT-4.1 miniQwen2.5-VL-32BResult
IFEvalSource 88.5%Not comparable
AA-IFBenchSource 38.3%Not comparable
Frequently Asked Questions (3)

Can I compare GPT-4.1 mini and Qwen2.5-VL-32B on BenchLM yet?

Not fully yet. BenchLM is tracking both models, but the sourced benchmark breakdown for this comparison is still coming soon.

Why does this comparison show “coming soon”?

BenchLM only shows category winners and benchmark-level calls when we have sourced results that can be compared fairly. For these models, the public benchmark coverage is not complete enough yet.

What data is available for GPT-4.1 mini and Qwen2.5-VL-32B today?

GPT-4.1 mini: $0.40 input / $1.60 output per 1M tokens Qwen2.5-VL-32B: $0.00 input / $0.00 output per 1M tokens Both model pages still include creator, context window, reasoning mode, and other metadata while benchmark coverage fills in.

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Last updated: July 24, 2026