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Model comparison

o3 vs Qwen2.5-VL-32B

Data verified

Head-to-head evidence from 0 shared benchmark results across 0 categories. Overall scores shown here use BenchLM's provisional ranking lane.

Benchmark data for one or both models is coming soon. This page currently shows metadata and pricing where BenchLM has it, and score-level comparisons will populate as public benchmark results land.
OpenAI
54/100
No comparison
N/A
0 category wins0 category wins

Evidence parity. o3 and Qwen2.5-VL-32B share 0 comparable benchmark results. 0 of 8 categories are comparable. 17 results are unique to o3; 0 to Qwen2.5-VL-32B.

Updated July 14, 2026
Shared results
0
o3 only
17
Qwen2.5-VL-32B only
0
Comparable categories
0 / 8

Benchmark data for o3 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.

o3 is priced at $2.00 input / $8.00 output per 1M tokens, versus $0.00 input / $0.00 output per 1M tokens for Qwen2.5-VL-32B. o3 has the larger context window at 200K, 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.

Metrico3Qwen2.5-VL-32BComparison
Input / output priceUSD per 1M tokenso3$2 input / $8 outputQwen2.5-VL-32B$0 input / $0 outputQwen2.5-VL-32B has the lower combined listed price.
Generation speedtokens per secondo3118 tok/sQwen2.5-VL-32BNot availableA complete speed comparison is not available.
First-answer latencyseconds to first tokeno35.38 sQwen2.5-VL-32BNot availableA complete latency comparison is not available.
Context windowmaximum listed tokenso3200KQwen2.5-VL-32B32Ko3 lists the larger context window.

Benchmark Deep Dive

Agentic
Benchmarko3Qwen2.5-VL-32BResult
Tau2-TelecomSource 80.7%Not comparable
Coding
Benchmarko3Qwen2.5-VL-32BResult
Terminal-Bench HardSource 37.1%Not comparable
AA-SciCodeSource 41.0%Not comparable
Reasoning
Benchmarko3Qwen2.5-VL-32BResult
AA-LCRSource 69.3%Not comparable
CritPtSource 1.1%Not comparable
Knowledge
Benchmarko3Qwen2.5-VL-32BResult
Artificial Analysis Intelligence IndexSource 30.4%Not comparable
AA-GPQA DiamondSource 82.7%Not comparable
AA-HLESource 20.0%Not comparable
AA-Omniscience IndexSource -15.3%Not comparable
AA-Omniscience AccuracySource 38.4%Not comparable
AA-Omniscience Hallucination RateSource 87.1%Not comparable
Math
Benchmarko3Qwen2.5-VL-32BResult
AA MATH-500Source 99.2%Not comparable
FrontierMath v2 (Tiers 1-3)Source 18.685%Not comparable
FrontierMath v2 (Tier 4)Source 2.083%Not comparable
Multimodal
Benchmarko3Qwen2.5-VL-32BResult
AA-MMMU-ProSource 70.1%Not comparable
Design Arena WebsiteSource 1071Not comparable
Inst. Following
Benchmarko3Qwen2.5-VL-32BResult
AA-IFBenchSource 71.4%Not comparable
Frequently Asked Questions (3)

Can I compare o3 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 o3 and Qwen2.5-VL-32B today?

o3: $2.00 input / $8.00 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 14, 2026

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