GPT-4.1 Mini vs o1
Updated October 21, 2026. 63 benchmarks have a result for both. Coding is ranked on the Vibe Coding Index; every other board is shown as published.
Decision reading
Pick o1 for coding: it scores 61.7 on the Vibe Coding Index against 28.5 for GPT-4.1 Mini, though on 1 benchmark against 2.
Pick GPT-4.1 Mini when output tokens cost 37.5x less, or when the context window is larger, 1.05M against 200K tokens.
- Shared results
- 63
- GPT-4.1 Mini only
- 21
- o1 only
- 5
- Like-for-like categories
- 7 of 9
Shared results can support a head-to-head reading. Results only one model has describe coverage, not superiority.
Which one for your work
Each card is decided by one number both models carry. Where only one has it, the card says so and makes no call.
Coding
Vibe Coding Index, four public coding benchmarks
o1
o1 scores 61.7 against 28.5.
2 and 1 benchmarks behind the scores
Intelligence
AA Intelligence Index
o1
o1 leads, 15.2 against 10.2.
Same board, both measured
Reasoning
GPQA Diamond
o1
o1 leads, 73.2% against 67.9%.
Same board, both measured
Math
AIME
o1
o1 leads, 71.5% against 49.4%.
Same board, both measured
Knowledge
MMLU Pro
o1
o1 leads, 83.5% against 77.2%.
Same board, both measured
Web design
Design Arena: websites
No call
Only GPT-4.1 Mini has a Design Arena: websites result, 997.
Directional only
Long documents
Listed context window
GPT-4.1 Mini
GPT-4.1 Mini takes 1.05M tokens against 200K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
GPT-4.1 Mini
GPT-4.1 Mini $0.0012, o1 $0.045 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
No call
Only GPT-4.1 Mini has the number, $1.818.
Directional only
At a glance
- Coding index
- GPT-4.1 Mini 28.5 from 2 benchmarks, o1 61.7 from 1 benchmark.
- Widest category
- Coding, 11.4 points apart on average over 8 shared benchmarks.
- Widest single gap
- Fiction.LiveBench: GPT-4.1 Mini 44.4% against o1 83.3%, 38.9 points apart on a 0 to 100 scale.
- Output price
- GPT-4.1 Mini $1.60 against o1 $60.00 per million output tokens, 37.5x apart.
- Context window
- GPT-4.1 Mini takes 1.05M tokens, o1 200K.
Benchmark by benchmark
First the score: boards each model leads, per category, where both have a result. Then every board, a category to a fold; bars are each result on a 0 to 100 scale, so compare the two in a row, not one row with another.
| Category | GPT-4.1 Mini | Bars | o1 | Ties |
|---|---|---|---|---|
| Coding | 2 | 6 | ||
| Intelligence | 0 | 2 | ||
| Agentic work | 0 | 1 | ||
| Reasoning | 0 | 10 | ||
| Math | 0 | 8 | ||
| Knowledge | 0 | 10 | ||
| General | 4 | 20 | ||
| All shared boards | 6 | 57 |
CodingLike-for-likeFour of these boards feed the Vibe Coding Index26
| Benchmark | GPT-4.1 Mini | o1 | Leader |
|---|---|---|---|
| Aider polyglot | 32.4% | 61.7% | o1 |
| SWE-bench Verified | 23.9% | Not measured | Only GPT-4.1 Mini measured |
| AA Coding Index | 20.2 | 39.7 | o1 |
| LiveCodeBench (Vals AI) | 58.2% | 50.3% | GPT-4.1 Mini |
| LiveCodeBench (Artificial Analysis run) | 48.3% | 67.9% | o1 |
| Terminal-Bench Hard (Artificial Analysis run) | 7.6% | 12.9% | o1 |
| WeirdML | 37.6% | 46.1% | o1 |
| LMArena Text: coding | 1367 | 1367 | GPT-4.1 Mini |
| LMArena Text: software and IT | 1360 | 1366 | o1 |
| Neither model has a result on the other 29 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index02
| Benchmark | GPT-4.1 Mini | o1 | Leader |
|---|---|---|---|
| AA Intelligence Index | 10.2 | 15.2 | o1 |
| Epoch Capabilities Index | 134.9 | 141.7 | o1 |
Agentic workLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | GPT-4.1 Mini | o1 | Leader |
|---|---|---|---|
| τ²-Bench Telecom | 52.9% | 62.6% | o1 |
| METR time horizons | Not measured | 51.1% | Only o1 measured |
| Neither model has a result on the other 37 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index010
| Benchmark | GPT-4.1 Mini | o1 | Leader |
|---|---|---|---|
| GPQA Diamond | 67.9% | 73.2% | o1 |
| MMMU Pro (Vals AI) | 70.5% | 77.4% | o1 |
| GPQA Diamond (Artificial Analysis run) | 66.4% | 74.7% | o1 |
| Humanity's Last Exam (Artificial Analysis run) | 5.0% | 7.0% | o1 |
| GPQA Diamond (Epoch AI run) | 65.8% | 76.8% | o1 |
| ARC-AGI | 3.5% | 30.7% | o1 |
| ARC-AGI-2 | 0.0% | Not measured | Only GPT-4.1 Mini measured |
| SimpleBench | Not measured | 40.1% | Only o1 measured |
| Chess puzzles | 1.0% | 10.0% | o1 |
| Mystery game puzzles | 7.0% | Not measured | Only GPT-4.1 Mini measured |
| VPCT | Not measured | 37.0% | Only o1 measured |
| LMArena Text: hard prompts | 1349 | 1371 | o1 |
| LMArena Text: expert | 1338 | 1361 | o1 |
| LMArena Text: hard prompts in English | 1362 | 1372 | o1 |
| LMArena Vision: diagrams | 1182 | Not measured | Only GPT-4.1 Mini measured |
| LMArena Vision: homework | 1214 | Not measured | Only GPT-4.1 Mini measured |
| Neither model has a result on the other 5 boards here | |||
MathLike-for-likePublic boards, shown as published, kept out of the index08
| Benchmark | GPT-4.1 Mini | o1 | Leader |
|---|---|---|---|
| AIME | 49.4% | 71.5% | o1 |
| MATH 500 (Vals AI) | 88.0% | 90.4% | o1 |
| MGSM (Vals AI) | 87.8% | 89.3% | o1 |
| AA Math Index | 46.3 | Not measured | Only GPT-4.1 Mini measured |
| AIME 2025 (Artificial Analysis run) | 46.3% | Not measured | Only GPT-4.1 Mini measured |
| OTIS Mock AIME | 44.7% | 73.3% | o1 |
| FrontierMath, tiers 1 to 3 | 6.7% | 14.7% | o1 |
| MATH level 5 | 87.3% | 94.7% | o1 |
| LMArena Text: math | 1343 | 1388 | o1 |
| LMArena Text: mathematical work | 1347 | 1390 | o1 |
| Neither model has a result on the other 3 boards here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index010
| Benchmark | GPT-4.1 Mini | o1 | Leader |
|---|---|---|---|
| MMLU Pro | 77.2% | 83.5% | o1 |
| LegalBench (Vals AI) | 78.0% | 80.4% | o1 |
| CorpFin (Vals AI) | 57.9% | Not measured | Only GPT-4.1 Mini measured |
| TaxEval (Vals AI) | 71.9% | 74.3% | o1 |
| MortgageTax (Vals AI) | 65.5% | Not measured | Only GPT-4.1 Mini measured |
| MedQA (Vals AI) | 84.6% | 96.5% | o1 |
| MMLU Pro (Artificial Analysis run) | 78.1% | 84.1% | o1 |
| SimpleQA Verified | 12.7% | 41.1% | o1 |
| GeoBench | Not measured | 80.0% | Only o1 measured |
| LMArena Text: science | 1328 | 1369 | o1 |
| LMArena Text: medicine and healthcare | 1324 | 1355 | o1 |
| LMArena Text: legal and government | 1343 | 1368 | o1 |
| LMArena Text: business and finance | 1322 | 1328 | o1 |
| Neither model has a result on the other 4 boards here | |||
Web designDirectional onlyPublic boards, shown as published, kept out of the index6 boards, none shared
| Benchmark | GPT-4.1 Mini | o1 | Leader |
|---|---|---|---|
| Design Arena: websites | 997 | Not measured | Only GPT-4.1 Mini measured |
| Design Arena: UI components | 961 | Not measured | Only GPT-4.1 Mini measured |
| Design Arena: game dev | 1071 | Not measured | Only GPT-4.1 Mini measured |
| Design Arena: data viz | 1034 | Not measured | Only GPT-4.1 Mini measured |
| Design Arena: 3D | 837 | Not measured | Only GPT-4.1 Mini measured |
| Design Arena: all code categories | 994 | Not measured | Only GPT-4.1 Mini measured |
| Neither model has a result on the other 3 boards here | |||
GeneralLike-for-likePublic boards, shown as published, kept out of the index420
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | GPT-4.1 Mini | o1 | Leader |
|---|---|---|---|
| Neither model has a result on 5 boards here | |||
What each workload costs
Three fixed token mixes at each model's listed price, so per-token rates become a bill.
Chat turn
1K input + 500 output tokens
GPT-4.1 Mini costs less
Repository review
50K input + 3K output tokens
GPT-4.1 Mini costs less
Agent loop
200K input + 10K output tokens
GPT-4.1 Mini costs less
Listed OpenRouter rates, without cache or batch discounts. A workload that does not fit a model's context window would need splitting.
Specification differences
The leading value in a row is marked; a row with a missing value names no leader. Our two rows are marked in red.
| Specification | OpenAI GPT-4.1 Mini | OpenAI o1 |
|---|---|---|
| Maker | OpenAI | OpenAI |
| Weights | No public weights listed | No public weights listed |
| Released | April 14, 2025 | December 17, 2024 |
| Context window | 1.05M | 200K |
| Input $/Mtok | $0.40 | $15.00 |
| Output $/Mtok | $1.60 | $60.00 |
| Coding index | 28.5 | 61.7 |
| Independent measurements behind it | 2 | 1 |
| Cost per solved task | $1.818 | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is GPT-4.1 Mini better than o1 for coding?
Pick o1 for coding: it scores 61.7 on the Vibe Coding Index against 28.5 for GPT-4.1 Mini, though on 1 benchmark against 2. Pick GPT-4.1 Mini when output tokens cost 37.5x less, or when the context window is larger, 1.05M against 200K tokens.
Which is cheaper, GPT-4.1 Mini or o1?
GPT-4.1 Mini costs $0.40 per million input tokens and $1.60 per million output tokens; o1 costs $15.00 and $60.00. Cost per solved task is known for GPT-4.1 Mini only.
Which has the bigger context window, GPT-4.1 Mini or o1?
GPT-4.1 Mini, with 1.05M tokens against 200K.
How many benchmarks is the GPT-4.1 Mini vs o1 comparison based on?
63 benchmarks have a result for both models as of October 21, 2026. GPT-4.1 Mini's coding index rests on 2 independent benchmarks and o1's on 1. Where only one model has a result, the page says so instead of naming a winner.