Model comparison
Mercury 2.5 vs o4-mini
o4-mini is the stronger model overall, scoring 41.6 to 33.5 on the Noometry Index. Mercury 2.5 costs 29× less per token, which makes it the better buy when o4-mini's lead doesn't matter for your workload.
Last verified . 2 shared benchmarks.
Summary
- They share 2 benchmarks with published results for both. Mercury 2.5 scores higher in 0 categories and o4-mini in 3 categories; 3 gaps are clear of the uncertainty.
- The widest gap is in math, where o4-mini leads 40.8 to 23.3.
- Mercury 2.5 is cheaper at $0.04 / $0.15 per million input/output tokens, against $1.10 / $4.40 for o4-mini.
- Mercury 2.5 accepts more context: 260K tokens versus 200K.
Side by side
| Mercury 2.5 | o4-mini | |
|---|---|---|
| Provider | Inception | OpenAI |
| Noometry Index | 33.5 | 41.6 |
| Released | 2026-09-08 | 2025-04-16 |
| Weights | Proprietary | Proprietary |
| Context window | 260K | 200K |
| Max output | 66K | 100K |
| Input $ / M tokens | $0.04 | $1.10 |
| Output $ / M tokens | $0.15 | $4.40 |
| Results tracked | 4 | 60 |
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Category by category
Coding o4-mini leads
Mercury 2.5: 39.5 (#156), o4-mini: 40.9 (#127)
| Benchmark | Mercury 2.5 | o4-mini |
|---|---|---|
| ALE-Bench | 301.65 | 826.17 |
| SWE-bench Verified (bash only) | — | 45% |
| Aider Polyglot | — | 72% |
| SciCode | 38.5% | — |
| GSO | — | 3.6% |
| WeirdML | — | 52.6% |
| LMArena Coding | — | 1368 |
| CadEval | — | 62% |
| AlgoTune | — | 1.72 |
Agentic & Tool Use Not comparable
Mercury 2.5: —, o4-mini: 32.6 (#61)
| Benchmark | Mercury 2.5 | o4-mini |
|---|---|---|
| Berkeley Function Calling Leaderboard | — | 53.2% |
| GDPval | — | 25.3% |
| METR Time Horizons | — | 63.9% |
Reasoning o4-mini leads
Mercury 2.5: 22.4 (#193), o4-mini: 24.6 (#162)
| Benchmark | Mercury 2.5 | o4-mini |
|---|---|---|
| CritPt | 0% | 0.6% |
| ARC-AGI-2 | — | 6.1% |
| SimpleBench | — | 38.7% |
| Kagi LLM Benchmark | — | 67.6% |
| ARC-AGI-1 | — | 58.7% |
| Chess Puzzles | — | 26% |
| EnigmaEval | — | 9.2% |
| LMArena Hard Prompts | — | 1351 |
| Mystery Game Puzzles | — | 5% |
| DTBench | — | 77.6% |
| LMCA | — | 26.5% |
| Epoch Capabilities Index | — | 145.64 |
| ForecastBench | — | 61.8 |
Math o4-mini leads
Mercury 2.5: 23.3 (#272), o4-mini: 40.8 (#89)
| Benchmark | Mercury 2.5 | o4-mini |
|---|---|---|
| FrontierMath (Tiers 1-3) | — | 36.1% |
| FrontierMath Tier 4 | — | 4.9% |
| OTIS Mock AIME 2024-2025 | — | 81.7% |
| ProofBench | 3% | — |
| Omni-MATH | — | 72% |
| LMArena Math | — | 1389 |
| MATH Level 5 | — | 97.8% |
| FrontierMath (Feb 2025 set) | — | 24.8% |
| FrontierMath Tier 4 (v1) | — | 6.3% |
Knowledge Not comparable
Mercury 2.5: —, o4-mini: 43.6 (#91)
| Benchmark | Mercury 2.5 | o4-mini |
|---|---|---|
| GPQA Diamond | — | 79.6% |
| Humanity's Last Exam | — | 18.1% |
| SimpleQA Verified | — | 19.6% |
| MMLU-Pro | — | 82% |
| Confabulations | — | 15.8% |
| Vectara Hallucination Rate | — | 18.6% |
| GPQA (HELM) | — | 73.5% |
| LMArena Expert | — | 1343 |
Multimodal Not comparable
Mercury 2.5: —, o4-mini: 40.2 (#49)
| Benchmark | Mercury 2.5 | o4-mini |
|---|---|---|
| LMArena Vision | — | 1194 |
| GeoBench | — | 64% |
| VPCT | — | 57.5% |
Multilingual Not comparable
Mercury 2.5: —, o4-mini: 47.0 (#154)
| Benchmark | Mercury 2.5 | o4-mini |
|---|---|---|
| LMArena Non-English | — | 1337 |
| LMArena Chinese | — | 1354 |
| LMArena French | — | 1364 |
| LMArena German | — | 1336 |
| LMArena Japanese | — | 1308 |
| LMArena Korean | — | 1312 |
| LMArena Russian | — | 1334 |
| LMArena Spanish | — | 1347 |
Instruction Following Not comparable
Mercury 2.5: —, o4-mini: 75.2 (#68)
| Benchmark | Mercury 2.5 | o4-mini |
|---|---|---|
| IFEval | — | 92.8% |
| LMArena Instruction Following | — | 1321 |
Long Context Not comparable
Mercury 2.5: —, o4-mini: 45.5 (#33)
| Benchmark | Mercury 2.5 | o4-mini |
|---|---|---|
| Fiction.LiveBench | — | 77.8% |
| LMArena Longer Query | — | 1315 |
Writing & Preference Not comparable
Mercury 2.5: —, o4-mini: 54.0 (#152)
| Benchmark | Mercury 2.5 | o4-mini |
|---|---|---|
| LMArena Text | — | 1353 |
| LMArena Creative Writing | — | 1294 |
| Short-Story Creative Writing | — | 75% |
| WildBench | — | 85.4% |
| LMArena Multi-Turn | — | 1350 |
Frequently asked questions
Is Mercury 2.5 better than o4-mini?
o4-mini is the stronger model overall, scoring 41.6 to 33.5 on the Noometry Index. Mercury 2.5 costs 29× less per token, which makes it the better buy when o4-mini's lead doesn't matter for your workload.
Which is cheaper, Mercury 2.5 or o4-mini?
Mercury 2.5 is cheaper. It lists at $0.04 per million input tokens and $0.15 per million output tokens; o4-mini lists at $1.10 and $4.40.
Is Mercury 2.5 or o4-mini better for coding?
o4-mini scores higher on coding benchmarks: 40.9 versus 39.5 in the Noometry coding category.
Which has the bigger context window?
Mercury 2.5 does, with 260K tokens against 200K.
How many benchmarks do Mercury 2.5 and o4-mini share?
2 benchmarks have published results for both models. Mercury 2.5 has 4 scored results on Noometry and o4-mini has 60.