GPT-4.1 Mini vs gpt-oss-120b
Updated October 21, 2026. 66 benchmarks have a result for both. Coding is ranked on the Vibe Coding Index; every other board is shown as published.
Decision reading
Pick gpt-oss-120b for coding: it scores 34.5 on the Vibe Coding Index against 28.5 for GPT-4.1 Mini.
Pick GPT-4.1 Mini when the context window is larger, 1.05M against 131K tokens, or when what matters is Mystery game puzzles or LegalBench (Vals AI), where it leads.
- Shared results
- 66
- GPT-4.1 Mini only
- 18
- gpt-oss-120b only
- 12
- Like-for-like categories
- 8 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
gpt-oss-120b
gpt-oss-120b scores 34.5 against 28.5.
2 benchmarks behind each score
Intelligence
AA Intelligence Index
gpt-oss-120b
gpt-oss-120b leads, 11.6 against 10.2.
Same board, both measured
Agentic work
AA Agentic Index
No call
Only gpt-oss-120b has a AA Agentic Index result, 3.7.
Directional only
Reasoning
GPQA Diamond
gpt-oss-120b
gpt-oss-120b leads, 78.5% against 67.9%.
Same board, both measured
Math
AIME
gpt-oss-120b
gpt-oss-120b leads, 92.6% against 49.4%.
Same board, both measured
Knowledge
MMLU Pro
gpt-oss-120b
gpt-oss-120b leads, 79.2% against 77.2%.
Same board, both measured
Web design
Design Arena: websites
GPT-4.1 Mini
GPT-4.1 Mini leads, 997 against 968.
Same board, both measured
Long documents
Listed context window
GPT-4.1 Mini
GPT-4.1 Mini takes 1.05M tokens against 131K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
gpt-oss-120b
GPT-4.1 Mini $0.0012, gpt-oss-120b $0.0004 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
gpt-oss-120b
GPT-4.1 Mini $1.818, gpt-oss-120b $0.51.
Published attempt cost and pass rate
At a glance
- Coding index
- GPT-4.1 Mini 28.5 from 2 benchmarks, gpt-oss-120b 34.5 from 2 benchmarks.
- Widest category
- Math, 25.9 points apart on average over 8 shared benchmarks.
- Widest single gap
- AIME 2025 (Artificial Analysis run): GPT-4.1 Mini 46.3% against gpt-oss-120b 93.4%, 47.1 points apart on a 0 to 100 scale.
- Output price
- GPT-4.1 Mini $1.60 against gpt-oss-120b $0.60 per million output tokens, 2.7x apart.
- Context window
- GPT-4.1 Mini takes 1.05M tokens, gpt-oss-120b 131K.
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 | gpt-oss-120b | Ties |
|---|---|---|---|---|
| Coding | 0 | 9 | ||
| Intelligence | 0 | 2 | ||
| Agentic work | 0 | 1 | ||
| Reasoning | 1 | 7 | ||
| Math | 0 | 8 | ||
| Knowledge | 2 | 8 | ||
| Web design | 5 | 1 | ||
| General | 7 | 14 | 1 tie | |
| All shared boards | 15 | 50 | 1 tie |
CodingLike-for-likeFour of these boards feed the Vibe Coding Index09
| Benchmark | GPT-4.1 Mini | gpt-oss-120b | Leader |
|---|---|---|---|
| Aider polyglot | 32.4% | 41.8% | gpt-oss-120b |
| SWE-bench Verified | 23.9% | 26.0% | gpt-oss-120b |
| AA Coding Index | 20.2 | 30.4 | gpt-oss-120b |
| LiveCodeBench (Vals AI) | 58.2% | 83.2% | gpt-oss-120b |
| SWE-bench Verified (Vals AI) | Not measured | 33.6% | Only gpt-oss-120b measured |
| LiveCodeBench (Artificial Analysis run) | 48.3% | 87.8% | gpt-oss-120b |
| SciCode | Not measured | 34.0% | Only gpt-oss-120b measured |
| Terminal-Bench Hard (Artificial Analysis run) | 7.6% | 23.5% | gpt-oss-120b |
| Terminal-Bench | Not measured | 18.7% | Only gpt-oss-120b measured |
| WeirdML | 37.6% | 48.2% | gpt-oss-120b |
| ALE-Bench | Not measured | 575.6 | Only gpt-oss-120b measured |
| LMArena Text: coding | 1367 | 1379 | gpt-oss-120b |
| LMArena Text: software and IT | 1360 | 1387 | gpt-oss-120b |
| Neither model has a result on the other 25 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index02
| Benchmark | GPT-4.1 Mini | gpt-oss-120b | Leader |
|---|---|---|---|
| AA Intelligence Index | 10.2 | 11.6 | gpt-oss-120b |
| Epoch Capabilities Index | 134.9 | 139.8 | gpt-oss-120b |
Agentic workLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | GPT-4.1 Mini | gpt-oss-120b | Leader |
|---|---|---|---|
| AA Agentic Index | Not measured | 3.7 | Only gpt-oss-120b measured |
| τ²-Bench Telecom | 52.9% | 65.8% | gpt-oss-120b |
| APEX-Agents | Not measured | 4.4% | Only gpt-oss-120b measured |
| METR time horizons | Not measured | 56.6% | Only gpt-oss-120b measured |
| Vending-Bench 2 | Not measured | -$22 | Only gpt-oss-120b measured |
| Neither model has a result on the other 34 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index17
| Benchmark | GPT-4.1 Mini | gpt-oss-120b | Leader |
|---|---|---|---|
| GPQA Diamond | 67.9% | 78.5% | gpt-oss-120b |
| MMMU Pro (Vals AI) | 70.5% | Not measured | Only GPT-4.1 Mini measured |
| GPQA Diamond (Artificial Analysis run) | 66.4% | 78.2% | gpt-oss-120b |
| Humanity's Last Exam (Artificial Analysis run) | 5.0% | 19.6% | gpt-oss-120b |
| GPQA Diamond (Epoch AI run) | 65.8% | 75.8% | gpt-oss-120b |
| ARC-AGI | 3.5% | Not measured | Only GPT-4.1 Mini measured |
| ARC-AGI-2 | 0.0% | Not measured | Only GPT-4.1 Mini measured |
| SimpleBench | Not measured | 22.1% | Only gpt-oss-120b measured |
| Chess puzzles | 1.0% | Not measured | Only GPT-4.1 Mini measured |
| Mystery game puzzles | 7.0% | 2.0% | GPT-4.1 Mini |
| LMArena Text: hard prompts | 1349 | 1364 | gpt-oss-120b |
| LMArena Text: expert | 1338 | 1356 | gpt-oss-120b |
| LMArena Text: hard prompts in English | 1362 | 1368 | gpt-oss-120b |
| 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 6 boards here | |||
MathLike-for-likePublic boards, shown as published, kept out of the index08
| Benchmark | GPT-4.1 Mini | gpt-oss-120b | Leader |
|---|---|---|---|
| AIME | 49.4% | 92.6% | gpt-oss-120b |
| MATH 500 (Vals AI) | 88.0% | 94.8% | gpt-oss-120b |
| MGSM (Vals AI) | 87.8% | 92.0% | gpt-oss-120b |
| AA Math Index | 46.3 | 93.4 | gpt-oss-120b |
| AIME 2025 (Artificial Analysis run) | 46.3% | 93.4% | gpt-oss-120b |
| OTIS Mock AIME | 44.7% | 88.9% | gpt-oss-120b |
| FrontierMath, tiers 1 to 3 | 6.7% | Not measured | Only GPT-4.1 Mini measured |
| MATH level 5 | 87.3% | Not measured | Only GPT-4.1 Mini measured |
| LMArena Text: math | 1343 | 1389 | gpt-oss-120b |
| LMArena Text: mathematical work | 1347 | 1386 | gpt-oss-120b |
| Neither model has a result on the other 3 boards here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index28
| Benchmark | GPT-4.1 Mini | gpt-oss-120b | Leader |
|---|---|---|---|
| MMLU Pro | 77.2% | 79.2% | gpt-oss-120b |
| LegalBench (Vals AI) | 78.0% | 75.9% | GPT-4.1 Mini |
| CaseLaw (Vals AI) | Not measured | 48.8% | Only gpt-oss-120b measured |
| CorpFin (Vals AI) | 57.9% | 58.2% | gpt-oss-120b |
| TaxEval (Vals AI) | 71.9% | 71.6% | GPT-4.1 Mini |
| MortgageTax (Vals AI) | 65.5% | Not measured | Only GPT-4.1 Mini measured |
| MedQA (Vals AI) | 84.6% | 91.4% | gpt-oss-120b |
| MMLU Pro (Artificial Analysis run) | 78.1% | 80.8% | gpt-oss-120b |
| SimpleQA Verified | 12.7% | Not measured | Only GPT-4.1 Mini measured |
| LMArena Text: science | 1328 | 1382 | gpt-oss-120b |
| LMArena Text: medicine and healthcare | 1324 | 1388 | gpt-oss-120b |
| LMArena Text: legal and government | 1343 | 1355 | gpt-oss-120b |
| LMArena Text: business and finance | 1322 | 1359 | gpt-oss-120b |
| Neither model has a result on the other 4 boards here | |||
Web designLike-for-likePublic boards, shown as published, kept out of the index51
| Benchmark | GPT-4.1 Mini | gpt-oss-120b | Leader |
|---|---|---|---|
| Design Arena: websites | 997 | 968 | GPT-4.1 Mini |
| Design Arena: UI components | 961 | 927 | GPT-4.1 Mini |
| Design Arena: game dev | 1071 | 992 | GPT-4.1 Mini |
| Design Arena: data viz | 1034 | 987 | GPT-4.1 Mini |
| Design Arena: 3D | 837 | 901 | gpt-oss-120b |
| Design Arena: all code categories | 994 | 963 | GPT-4.1 Mini |
| Neither model has a result on the other 3 boards here | |||
GeneralLike-for-likePublic boards, shown as published, kept out of the index714
| Benchmark | GPT-4.1 Mini | gpt-oss-120b | Leader |
|---|---|---|---|
| IFBench | 38.3% | 69.0% | gpt-oss-120b |
| Long context reasoning (AA-LCR) | 44.0% | 52.0% | gpt-oss-120b |
| DTBench | 68.8% | 76.3% | gpt-oss-120b |
| LMCA | 21.1% | 22.1% | gpt-oss-120b |
| Fiction.LiveBench | 44.4% | 44.4% | Tie |
| Creative writing (Lech Mazur) | Not measured | 77.1% | Only gpt-oss-120b measured |
| Surface Evolver Bench | Not measured | 25.0% | Only gpt-oss-120b measured |
| LMArena Text | 1341 | 1366 | gpt-oss-120b |
| LMArena Text: instruction following | 1333 | 1318 | GPT-4.1 Mini |
| LMArena Text: creative writing | 1299 | 1274 | GPT-4.1 Mini |
| LMArena Vision | 1181 | Not measured | Only GPT-4.1 Mini measured |
| LMArena Text: English | 1356 | 1375 | gpt-oss-120b |
| LMArena Text: non-English | 1318 | 1351 | gpt-oss-120b |
| LMArena Text: Chinese | 1329 | 1385 | gpt-oss-120b |
| LMArena Text: German | 1350 | 1353 | gpt-oss-120b |
| LMArena Text: Japanese | 1290 | 1331 | gpt-oss-120b |
| LMArena Text: Korean | 1298 | 1282 | GPT-4.1 Mini |
| LMArena Text: French | 1358 | 1370 | gpt-oss-120b |
| LMArena Text: Spanish | 1319 | 1389 | gpt-oss-120b |
| LMArena Text: Russian | 1324 | 1343 | gpt-oss-120b |
| LMArena Text: Polish | 1326 | 1353 | gpt-oss-120b |
| LMArena Text: multi-turn | 1354 | 1340 | GPT-4.1 Mini |
| LMArena Text: longer queries | 1344 | 1319 | GPT-4.1 Mini |
| LMArena Text: writing and language | 1319 | 1306 | GPT-4.1 Mini |
| LMArena Text: entertainment and media | 1300 | 1292 | GPT-4.1 Mini |
| LMArena Vision: English | 1191 | Not measured | Only GPT-4.1 Mini measured |
| LMArena Vision: Chinese | 1186 | Not measured | Only GPT-4.1 Mini measured |
| LMArena Vision: reading text | 1188 | Not measured | Only GPT-4.1 Mini measured |
| LMArena Vision: humor | 1182 | Not measured | Only GPT-4.1 Mini measured |
| LMArena Vision: captioning | 1174 | Not measured | Only GPT-4.1 Mini measured |
| LMArena Vision: recognizing things | 1187 | Not measured | Only GPT-4.1 Mini measured |
| LMArena Vision: creative writing | 1182 | Not measured | Only GPT-4.1 Mini measured |
| Neither model has a result on the other 14 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | GPT-4.1 Mini | gpt-oss-120b | 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-oss-120b costs less
Repository review
50K input + 3K output tokens
gpt-oss-120b costs less
Agent loop
200K input + 10K output tokens
gpt-oss-120b 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 gpt-oss-120b |
|---|---|---|
| Maker | OpenAI | OpenAI |
| Weights | No public weights listed | Open weights |
| Released | April 14, 2025 | August 5, 2025 |
| Context window | 1.05M | 131K |
| Input $/Mtok | $0.40 | $0.15 |
| Output $/Mtok | $1.60 | $0.60 |
| Coding index | 28.5 | 34.5 |
| Independent measurements behind it | 2 | 2 |
| Cost per solved task | $1.818 | $0.51 |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is GPT-4.1 Mini better than gpt-oss-120b for coding?
Pick gpt-oss-120b for coding: it scores 34.5 on the Vibe Coding Index against 28.5 for GPT-4.1 Mini. Pick GPT-4.1 Mini when the context window is larger, 1.05M against 131K tokens, or when what matters is Mystery game puzzles or LegalBench (Vals AI), where it leads.
Which is cheaper, GPT-4.1 Mini or gpt-oss-120b?
GPT-4.1 Mini costs $0.40 per million input tokens and $1.60 per million output tokens; gpt-oss-120b costs $0.15 and $0.60. Per solved SWE-bench Verified task, GPT-4.1 Mini costs $1.818 and gpt-oss-120b $0.51.
Which has the bigger context window, GPT-4.1 Mini or gpt-oss-120b?
GPT-4.1 Mini, with 1.05M tokens against 131K.
How many benchmarks is the GPT-4.1 Mini vs gpt-oss-120b comparison based on?
66 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 gpt-oss-120b's on 2. Where only one model has a result, the page says so instead of naming a winner.