Model comparison
GPT-4.1 mini vs Trinity-Large-Preview
Head-to-head evidence from 15 shared benchmark results across 6 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.
Public leaderboard positions: GPT-4.1 mini #152 (Estimated); Trinity-Large-Preview #79 (Estimated). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.
Evidence parity. GPT-4.1 mini and Trinity-Large-Preview share 15 comparable benchmark results. 0 of 8 categories are comparable. 7 results are unique to GPT-4.1 mini; 3 to Trinity-Large-Preview.
Updated July 21, 2026- Shared results
- 15
- GPT-4.1 mini only
- 7
- Trinity-Large-Preview only
- 3
- Comparable categories
- 0 / 8
Benchmark data for GPT-4.1 mini and Trinity-Large-Preview is coming soon on BenchLM.
Confidence note. This is a partial-evidence comparison with 15 shared benchmark results across 6 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 $0.25 input / $1.00 output per 1M tokens for Trinity-Large-Preview. GPT-4.1 mini has the larger context window at 1M, compared with 512K for Trinity-Large-Preview.
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 | Trinity-Large-Preview |
|---|---|---|---|
| Coding | GPT-4.1 mini23.6 | MarginNo overlap | Trinity-Large-PreviewNot measured |
| Knowledge | GPT-4.1 mini64.2 | MarginNo overlap | Trinity-Large-PreviewNot measured |
| Math | GPT-4.1 mini4.5 | MarginNo overlap | Trinity-Large-PreviewNot measured |
| Inst. Following | GPT-4.1 mini88.5 | MarginNo overlap | Trinity-Large-PreviewNot measured |
Operational comparison
Runtime and commercial metrics are compared only when both models have a complete sourced value.
| Metric | GPT-4.1 mini | Trinity-Large-Preview | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | GPT-4.1 mini$0.4 input / $1.6 output | Trinity-Large-Preview$0.25 input / $1 output | Trinity-Large-Preview has the lower combined listed price. |
| Generation speedtokens per second | GPT-4.1 mini80 tok/s | Trinity-Large-PreviewNot available | A complete speed comparison is not available. |
| First-answer latencyseconds to first token | GPT-4.1 mini0.76 s | Trinity-Large-PreviewNot available | A complete latency comparison is not available. |
| Context windowmaximum listed tokens | GPT-4.1 mini1M | Trinity-Large-Preview512K | GPT-4.1 mini lists the larger context window. |
Benchmark Deep Dive
Agentic4 benchmarks
Coding3 benchmarks
Reasoning2 benchmarks
Knowledge10 benchmarks
| Benchmark | GPT-4.1 mini | Trinity-Large-Preview | Result |
|---|---|---|---|
| MMLUSource | 87.5% | 87.2% | GPT-4.1 mini leads |
| GPQASource | 64.2% | — | Not comparable |
| Artificial Analysis Intelligence IndexSource | 14.8% | 24.5% | Trinity-Large-Preview leads |
| AA-GPQA DiamondSource | 66.4% | 75.2% | Trinity-Large-Preview leads |
| AA-HLESource | 4.6% | 14.7% | Trinity-Large-Preview leads |
| AA-Omniscience IndexSource | -50.1% | -44.2% | Trinity-Large-Preview leads |
| AA-Omniscience AccuracySource | 17.5% | 22.8% | Trinity-Large-Preview leads |
| AA-Omniscience Hallucination RateSource | 82.0% | 86.6% | GPT-4.1 mini leads |
| MMLU-Pro (Arcee)Source | — | 75.2% | Not comparable |
| GPQA-DSource | — | 63.3% | Not comparable |
Math2 benchmarks
Multimodal2 benchmarks
Frequently Asked Questions (3)
Can I compare GPT-4.1 mini and Trinity-Large-Preview 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 Trinity-Large-Preview today?
GPT-4.1 mini: $0.40 input / $1.60 output per 1M tokens Trinity-Large-Preview: $0.25 input / $1.00 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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