Model comparison
GPT-4.1 mini vs Mercury 2
Mercury 2 is the stronger model overall, scoring 38.8 to 33.5 on the Noometry Index.
Last verified . 14 shared benchmarks.
Summary
- They share 14 benchmarks with published results for both. GPT-4.1 mini scores higher in 1 category and Mercury 2 in 6 categories; 5 gaps are clear of the uncertainty.
- The widest gap is in reasoning, where Mercury 2 leads 23.0 to 10.9.
- The biggest single-benchmark swing is WeirdML: 37.6% for GPT-4.1 mini and 43.2% for Mercury 2.
- Mercury 2 is cheaper at $0.25 / $0.75 per million input/output tokens, against $0.40 / $1.60 for GPT-4.1 mini.
- GPT-4.1 mini accepts more context: 1.05M tokens versus 128K.
Side by side
| GPT-4.1 mini | Mercury 2 | |
|---|---|---|
| Provider | OpenAI | Inception |
| Noometry Index | 33.5 | 38.8 |
| Released | 2025-04-14 | 2026-02-20 |
| Weights | Proprietary | Proprietary |
| Context window | 1.05M | 128K |
| Max output | 33K | 50K |
| Input $ / M tokens | $0.40 | $0.25 |
| Output $ / M tokens | $1.60 | $0.75 |
| Results tracked | 47 | 17 |
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Category by category
Coding Mercury 2 leads
GPT-4.1 mini: 30.4 (#286), Mercury 2: 33.2 (#250)
| Benchmark | GPT-4.1 mini | Mercury 2 |
|---|---|---|
| SciCode | 40.4% | 38.7% |
| WeirdML | 37.6% | 43.2% |
| LMArena Coding | 1367 | 1391 |
| SWE-bench Verified (bash only) | 23.9% | — |
| Aider Polyglot | 32.4% | — |
| LMArena WebDev | — | 1170 |
| BigCodeBench Instruct | 48.9% | — |
| CadEval | 16% | — |
| ALE-Bench | — | 785.58 |
Agentic & Tool Use Not comparable
GPT-4.1 mini: 33.0 (#52), Mercury 2: —
| Benchmark | GPT-4.1 mini | Mercury 2 |
|---|---|---|
| Berkeley Function Calling Leaderboard | 50.5% | — |
Reasoning Mercury 2 leads
GPT-4.1 mini: 10.9 (#335), Mercury 2: 23.0 (#170)
| Benchmark | GPT-4.1 mini | Mercury 2 |
|---|---|---|
| CritPt | 0% | 0.8% |
| LMArena Hard Prompts | 1349 | 1362 |
| ARC-AGI-2 | 0% | — |
| Kagi LLM Benchmark | 48.6% | — |
| ARC-AGI-1 | 3.5% | — |
| Chess Puzzles | 7% | — |
| Mystery Game Puzzles | 7% | — |
| DTBench | 68.8% | — |
| LMCA | 21.1% | — |
| Epoch Capabilities Index | 135.01 | — |
Math Not comparable
GPT-4.1 mini: 23.1 (#264), Mercury 2: —
| Benchmark | GPT-4.1 mini | Mercury 2 |
|---|---|---|
| FrontierMath (Tiers 1-3) | 6.7% | — |
| OTIS Mock AIME 2024-2025 | 44.7% | — |
| Omni-MATH | 49.1% | — |
| LMArena Math | 1343 | — |
| MATH Level 5 | 87.3% | — |
| FrontierMath (Feb 2025 set) | 4.5% | — |
Knowledge Too close to call
GPT-4.1 mini: 34.7 (#183), Mercury 2: 35.6 (#170)
| Benchmark | GPT-4.1 mini | Mercury 2 |
|---|---|---|
| LMArena Expert | 1338 | 1358 |
| GPQA Diamond | 65.8% | — |
| SimpleQA Verified | 12.7% | — |
| MMLU-Pro | 78.3% | — |
| Vectara Hallucination Rate | — | 12.3% |
| GPQA (HELM) | 61.4% | — |
Multimodal Not comparable
GPT-4.1 mini: 35.2 (#77), Mercury 2: —
| Benchmark | GPT-4.1 mini | Mercury 2 |
|---|---|---|
| LMArena Vision | 1181 | — |
Multilingual Too close to call
GPT-4.1 mini: 45.9 (#161), Mercury 2: 46.8 (#153)
| Benchmark | GPT-4.1 mini | Mercury 2 |
|---|---|---|
| LMArena Non-English | 1318 | 1331 |
| LMArena Chinese | 1329 | 1416 |
| LMArena Russian | 1324 | 1303 |
| LMArena French | 1357 | — |
| LMArena German | 1349 | — |
| LMArena Japanese | 1291 | — |
| LMArena Korean | 1298 | — |
| LMArena Spanish | 1319 | — |
Instruction Following GPT-4.1 mini leads
GPT-4.1 mini: 73.9 (#113), Mercury 2: 70.4 (#161)
| Benchmark | GPT-4.1 mini | Mercury 2 |
|---|---|---|
| LMArena Instruction Following | 1332 | 1328 |
| IFEval | 90.4% | — |
Long Context Mercury 2 leads
GPT-4.1 mini: 31.8 (#270), Mercury 2: 40.4 (#149)
| Benchmark | GPT-4.1 mini | Mercury 2 |
|---|---|---|
| LMArena Longer Query | 1344 | 1329 |
| Fiction.LiveBench | 44.4% | — |
Writing & Preference Mercury 2 leads
GPT-4.1 mini: 48.8 (#193), Mercury 2: 54.0 (#151)
| Benchmark | GPT-4.1 mini | Mercury 2 |
|---|---|---|
| LMArena Text | 1341 | 1355 |
| LMArena Creative Writing | 1300 | 1289 |
| LMArena Multi-Turn | 1354 | 1358 |
| EQ-Bench Creative Writing | 1147 | — |
| WildBench | 83.8% | — |
Frequently asked questions
Is GPT-4.1 mini better than Mercury 2?
Mercury 2 is the stronger model overall, scoring 38.8 to 33.5 on the Noometry Index.
Which is cheaper, GPT-4.1 mini or Mercury 2?
Mercury 2 is cheaper. It lists at $0.25 per million input tokens and $0.75 per million output tokens; GPT-4.1 mini lists at $0.40 and $1.60.
Is GPT-4.1 mini or Mercury 2 better for coding?
Mercury 2 scores higher on coding benchmarks: 33.2 versus 30.4 in the Noometry coding category.
Which has the bigger context window?
GPT-4.1 mini does, with 1.05M tokens against 128K.
How many benchmarks do GPT-4.1 mini and Mercury 2 share?
14 benchmarks have published results for both models. GPT-4.1 mini has 47 scored results on Noometry and Mercury 2 has 17.