Model comparison
GPT-4.1 mini vs Phi-4
Head-to-head evidence from 11 shared benchmark results across 5 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.
Public leaderboard positions: GPT-4.1 mini #160 (Estimated); Phi-4 #202 (Supported). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.
Evidence parity. GPT-4.1 mini and Phi-4 share 11 comparable benchmark results. 0 of 8 categories are comparable. 11 results are unique to GPT-4.1 mini; 0 to Phi-4.
Updated July 24, 2026- Shared results
- 11
- GPT-4.1 mini only
- 11
- Phi-4 only
- 0
- Comparable categories
- 0 / 8
Benchmark data for GPT-4.1 mini and Phi-4 is coming soon on BenchLM.
Confidence note. This is a partial-evidence comparison with 11 shared benchmark results across 5 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.
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 Phi-4. GPT-4.1 mini has the larger context window at 1M, 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 | GPT-4.1 mini | Δ | Phi-4 |
|---|---|---|---|
| Coding | GPT-4.1 mini23.6 | MarginNo overlap | Phi-4Not measured |
| Knowledge | GPT-4.1 mini64.2 | MarginNo overlap | Phi-4Not measured |
| Math | GPT-4.1 mini4.5 | MarginNo overlap | Phi-4Not measured |
| Inst. Following | GPT-4.1 mini88.5 | MarginNo overlap | Phi-4Not measured |
Operational comparison
Runtime and commercial metrics are compared only when both models have a complete sourced value.
| Metric | GPT-4.1 mini | Phi-4 | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | GPT-4.1 mini$0.4 input / $1.6 output | Phi-4$0 input / $0 output | Phi-4 has the lower combined listed price. |
| Generation speedtokens per second | GPT-4.1 mini80 tok/s | Phi-435 tok/s | GPT-4.1 mini has the higher measured throughput. |
| First-answer latencyseconds to first token | GPT-4.1 mini0.76 s | Phi-42.02 s | GPT-4.1 mini reaches the first token sooner. |
| Context windowmaximum listed tokens | GPT-4.1 mini1M | Phi-416K | GPT-4.1 mini lists the larger context window. |
Benchmark Deep Dive
Agentic4 benchmarks
Coding3 benchmarks
Reasoning2 benchmarks
Knowledge8 benchmarks
| Benchmark | GPT-4.1 mini | Phi-4 | Result |
|---|---|---|---|
| MMLUSource | 87.5% | — | Not comparable |
| GPQASource | 64.2% | — | Not comparable |
| Artificial Analysis Intelligence IndexSource | 14.8% | 4.9% | GPT-4.1 mini leads |
| AA-GPQA DiamondSource | 66.4% | 57.5% | GPT-4.1 mini leads |
| AA-HLESource | 4.6% | 4.1% | GPT-4.1 mini leads |
| AA-Omniscience IndexSource | -50.1% | -56.7% | GPT-4.1 mini leads |
| AA-Omniscience AccuracySource | 17.5% | 13.2% | GPT-4.1 mini leads |
| AA-Omniscience Hallucination RateSource | 82.0% | 80.5% | Phi-4 leads |
Math1 benchmarks
| Benchmark | GPT-4.1 mini | Phi-4 | Result |
|---|---|---|---|
| FrontierMath v2 (Tiers 1-3)Source | 4.483% | — | Not comparable |
Multimodal2 benchmarks
Frequently Asked Questions (3)
Can I compare GPT-4.1 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 GPT-4.1 mini and Phi-4 today?
GPT-4.1 mini: $0.40 input / $1.60 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.