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Model comparison

o3-mini vs Phi-4

Data verified

Head-to-head evidence from 5 shared benchmark results across 3 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.

OpenAI
46.59/100
Margin
24.3pts
← winning
Microsoft
22.32/100
0 category wins0 category wins

Public leaderboard positions: o3-mini #141 (Supported); Phi-4 #202 (Supported). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.

Evidence parity. o3-mini and Phi-4 share 5 comparable benchmark results. 0 of 8 categories are comparable. 5 results are unique to o3-mini; 6 to Phi-4.

Updated July 24, 2026
Shared results
5
o3-mini only
5
Phi-4 only
6
Comparable categories
0 / 8

Benchmark data for o3-mini and Phi-4 is coming soon on BenchLM.

Confidence note. This is a partial-evidence comparison with 5 shared benchmark results across 3 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 has partial data for these models, but not enough overlapping benchmark coverage to produce a fair score-level comparison yet.

o3-mini is priced at $1.10 input / $4.40 output per 1M tokens, versus $0.00 input / $0.00 output per 1M tokens for Phi-4. o3-mini has the larger context window at 200K, compared with 16K for Phi-4.

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 Phi-4
Categoryo3-miniΔPhi-4
Codingo3-mini49.3MarginNo overlapPhi-4Not measured
Knowledgeo3-mini77.2MarginNo overlapPhi-4Not measured
Inst. Followingo3-mini93.9MarginNo overlapPhi-4Not measured

Operational comparison

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

Metrico3-miniPhi-4Comparison
Input / output priceUSD per 1M tokenso3-mini$1.1 input / $4.4 outputPhi-4$0 input / $0 outputPhi-4 has the lower combined listed price.
Generation speedtokens per secondo3-mini160 tok/sPhi-435 tok/so3-mini has the higher measured throughput.
First-answer latencyseconds to first tokeno3-mini7.12 sPhi-42.02 sPhi-4 reaches the first token sooner.
Context windowmaximum listed tokenso3-mini200KPhi-416Ko3-mini lists the larger context window.

Benchmark Deep Dive

Agentic
Benchmarko3-miniPhi-4Result
τ²-bench resultsSource 28.7%0%o3-mini leads
Coding
Benchmarko3-miniPhi-4Result
SWE-bench VerifiedSource 49.3%Not comparable
AA-SciCodeSource 39.9%26.0%o3-mini leads
Reasoning
Benchmarko3-miniPhi-4Result
AA-LCRSource 0.0%Not comparable
CritPtSource 0.0%Not comparable
Knowledge
Benchmarko3-miniPhi-4Result
MMLUSource 86.9%Not comparable
GPQASource 77.2%Not comparable
Artificial Analysis Intelligence IndexSource 19.0%4.9%o3-mini leads
AA-GPQA DiamondSource 74.8%57.5%o3-mini leads
AA-HLESource 8.7%4.1%o3-mini leads
AA-Omniscience IndexSource -56.7%Not comparable
AA-Omniscience AccuracySource 13.2%Not comparable
AA-Omniscience Hallucination RateSource 80.5%Not comparable
Math
Benchmarko3-miniPhi-4Result
AIME 2024Source 87.3%Not comparable
Inst. Following
Benchmarko3-miniPhi-4Result
IFEvalSource 93.9%Not comparable
AA-IFBenchSource 23.5%Not comparable
Frequently Asked Questions (3)

Can I compare o3-mini and Phi-4 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-mini and Phi-4 today?

o3-mini: $1.10 input / $4.40 output per 1M tokens Phi-4: $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