gpt-oss-120b vs o4 Mini
o4 Mini leads gpt-oss-120b on the Artificial Analysis Intelligence Index, 16.7 to 11.6, and gpt-oss-120b costs 8.8x less per output token ($0.50 vs $4.40 per million). Updated October 22, 2026; 70 benchmarks have a result for both.
gpt-oss-120b or o4 Mini: which to pick
Neither model has a coding score yet, so the two cannot be ranked on coding.
Pick gpt-oss-120b for output tokens 8.8x cheaper ($0.50 vs $4.40 per million) and work measured by Aider polyglot or SWE-bench Verified, where it leads.
- Shared results
- 70
- gpt-oss-120b only
- 11
- o4 Mini only
- 28
- Like-for-like categories
- 8 of 9
Only benchmarks that tested both models count toward a pick; a result only one model has is shown but not compared.
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, six public coding benchmarks
No call
Neither has a coding score yet.
One side not measured
Intelligence
AA Intelligence Index
o4 Mini
o4 Mini leads, 16.7 against 11.6.
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 74.5%.
Same board, both measured
Math
AIME
gpt-oss-120b
gpt-oss-120b leads, 92.6% against 83.7%.
Same board, both measured
Knowledge
MMLU Pro
o4 Mini
o4 Mini leads, 80.6% against 79.2%.
Same board, both measured
Web design
Design Arena: websites
o4 Mini
o4 Mini leads, 985 against 967.
Same board, both measured
Long documents
Listed context window
o4 Mini
o4 Mini takes 200K tokens against 131K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
gpt-oss-120b
gpt-oss-120b $0.0003, o4 Mini $0.0033 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
No call
Only gpt-oss-120b has the number, $0.51.
Directional only
At a glance
- Coding index
- gpt-oss-120b not benchmarked, o4 Mini not benchmarked.
- Widest category
- Coding, 10.3 points apart on average over 9 shared benchmarks.
- Widest single gap
- SWE-bench Verified: gpt-oss-120b 26.0% against o4 Mini 64.6%, 38.6 points apart on a 0 to 100 scale.
- Output price
- gpt-oss-120b $0.50 against o4 Mini $4.40 per million output tokens, 8.8x apart.
- Context window
- gpt-oss-120b takes 131K tokens, o4 Mini 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-oss-120b | Bars | o4 Mini | Ties |
|---|---|---|---|---|
| Coding | 5 | 4 | ||
| Intelligence | 0 | 2 | ||
| Agentic work | 1 | 1 | ||
| Reasoning | 5 | 5 | ||
| Math | 6 | 2 | ||
| Knowledge | 4 | 6 | ||
| Web design | 1 | 5 | ||
| General | 12 | 11 | ||
| All shared boards | 34 | 36 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index54
| Benchmark | gpt-oss-120b | o4 Mini | Leader |
|---|---|---|---|
| Aider polyglot | 41.8% | 72.0% | o4 Mini |
| SWE-bench Verified | 26.0% | 64.6% | o4 Mini |
| SWE-bench Multimodal | Not measured | 33.9% | Only o4 Mini measured |
| AA Coding Index | 30.4 | Not measured | Only gpt-oss-120b measured |
| LiveCodeBench (Vals AI) | 83.2% | 82.2% | gpt-oss-120b |
| SWE-bench Verified (Vals AI) | 33.6% | Not measured | Only gpt-oss-120b measured |
| LiveCodeBench (Artificial Analysis run) | 87.8% | 85.9% | gpt-oss-120b |
| SciCode | 34.0% | Not measured | Only gpt-oss-120b measured |
| Terminal-Bench Hard (Artificial Analysis run) | 23.5% | 15.2% | gpt-oss-120b |
| Terminal-Bench | 18.7% | Not measured | Only gpt-oss-120b measured |
| GSO-Bench | Not measured | 3.6% | Only o4 Mini measured |
| WeirdML | 48.2% | 52.6% | o4 Mini |
| ALE-Bench | 575.6 | Not measured | Only gpt-oss-120b measured |
| LMArena Text: coding | 1379 | 1368 | gpt-oss-120b |
| LMArena Text: software and IT | 1387 | 1367 | gpt-oss-120b |
| SciCode | 7.7% | 10.8% | o4 Mini |
| Neither model has a result on the other 23 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index02
| Benchmark | gpt-oss-120b | o4 Mini | Leader |
|---|---|---|---|
| AA Intelligence Index | 11.6 | 16.7 | o4 Mini |
| Epoch Capabilities Index | 139.8 | 145.5 | o4 Mini |
Agentic workLike-for-likePublic boards, shown as published, kept out of the index11
| Benchmark | gpt-oss-120b | o4 Mini | Leader |
|---|---|---|---|
| AA Agentic Index | 3.7 | Not measured | Only gpt-oss-120b measured |
| τ²-Bench Telecom | 65.8% | 55.6% | gpt-oss-120b |
| APEX-Agents | 4.4% | Not measured | Only gpt-oss-120b measured |
| METR time horizons | 56.6% | 63.9% | o4 Mini |
| Vending-Bench 2 | -$22 | Not measured | Only gpt-oss-120b measured |
| Berkeley Function Calling Leaderboard (BFCL) | Not measured | 53.2% | Only o4 Mini measured |
| BrowseComp-Plus | 67.0% | Not measured | 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 index55
| Benchmark | gpt-oss-120b | o4 Mini | Leader |
|---|---|---|---|
| GPQA Diamond | 78.5% | 74.5% | gpt-oss-120b |
| MMMU Pro (Vals AI) | Not measured | 79.7% | Only o4 Mini measured |
| GPQA Diamond (Artificial Analysis run) | 78.2% | 78.4% | o4 Mini |
| Humanity's Last Exam (Artificial Analysis run) | 19.6% | 16.5% | gpt-oss-120b |
| GPQA Diamond (Epoch AI run) | 75.8% | 79.6% | o4 Mini |
| ARC-AGI | Not measured | 58.7% | Only o4 Mini measured |
| ARC-AGI-2 | Not measured | 6.1% | Only o4 Mini measured |
| SimpleBench | 22.1% | 38.7% | o4 Mini |
| Chess puzzles | Not measured | 22.0% | Only o4 Mini measured |
| Mystery game puzzles | 2.0% | 5.0% | o4 Mini |
| VPCT | Not measured | 57.5% | Only o4 Mini measured |
| LMArena Text: hard prompts | 1364 | 1351 | gpt-oss-120b |
| LMArena Text: expert | 1356 | 1343 | gpt-oss-120b |
| LMArena Text: hard prompts in English | 1368 | 1366 | gpt-oss-120b |
| LMArena Vision: diagrams | Not measured | 1197 | Only o4 Mini measured |
| LMArena Vision: homework | Not measured | 1234 | Only o4 Mini measured |
| Kagi LLM Benchmark | 58.6% | 67.6% | o4 Mini |
| Neither model has a result on the other 5 boards here | |||
MathLike-for-likePublic boards, shown as published, kept out of the index62
| Benchmark | gpt-oss-120b | o4 Mini | Leader |
|---|---|---|---|
| AIME | 92.6% | 83.7% | gpt-oss-120b |
| MATH 500 (Vals AI) | 94.8% | 94.2% | gpt-oss-120b |
| MGSM (Vals AI) | 92.0% | 93.4% | o4 Mini |
| AA Math Index | 93.4 | 90.7 | gpt-oss-120b |
| AIME 2025 (Artificial Analysis run) | 93.4% | 90.7% | gpt-oss-120b |
| OTIS Mock AIME | 88.9% | 81.7% | gpt-oss-120b |
| FrontierMath, tiers 1 to 3 | Not measured | 36.1% | Only o4 Mini measured |
| FrontierMath, tier 4 | Not measured | 4.9% | Only o4 Mini measured |
| MATH level 5 | Not measured | 97.8% | Only o4 Mini measured |
| LMArena Text: math | 1389 | 1389 | o4 Mini |
| LMArena Text: mathematical work | 1386 | 1379 | gpt-oss-120b |
| Neither model has a result on the other 2 boards here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index46
| Benchmark | gpt-oss-120b | o4 Mini | Leader |
|---|---|---|---|
| MMLU Pro | 79.2% | 80.6% | o4 Mini |
| LegalBench (Vals AI) | 75.9% | 79.2% | o4 Mini |
| CaseLaw (Vals AI) | 48.8% | Not measured | Only gpt-oss-120b measured |
| CorpFin (Vals AI) | 58.2% | 59.0% | o4 Mini |
| TaxEval (Vals AI) | 71.6% | 74.8% | o4 Mini |
| MortgageTax (Vals AI) | Not measured | 64.8% | Only o4 Mini measured |
| MedQA (Vals AI) | 91.4% | 96.0% | o4 Mini |
| MedCode (Vals AI) | Not measured | 33.8% | Only o4 Mini measured |
| MMLU Pro (Artificial Analysis run) | 80.8% | 83.2% | o4 Mini |
| SimpleQA Verified | Not measured | 19.6% | Only o4 Mini measured |
| GeoBench | Not measured | 64.0% | Only o4 Mini measured |
| LMArena Text: science | 1382 | 1354 | gpt-oss-120b |
| LMArena Text: medicine and healthcare | 1388 | 1361 | gpt-oss-120b |
| LMArena Text: legal and government | 1355 | 1350 | gpt-oss-120b |
| LMArena Text: business and finance | 1359 | 1325 | gpt-oss-120b |
| FACTS Benchmark Suite | Not measured | 28.1% | Only o4 Mini measured |
| Neither model has a result on the other 2 boards here | |||
Web designLike-for-likePublic boards, shown as published, kept out of the index15
| Benchmark | gpt-oss-120b | o4 Mini | Leader |
|---|---|---|---|
| Design Arena: websites | 967 | 985 | o4 Mini |
| Design Arena: UI components | 924 | 983 | o4 Mini |
| Design Arena: game dev | 992 | 1003 | o4 Mini |
| Design Arena: data viz | 987 | 991 | o4 Mini |
| Design Arena: 3D | 901 | 854 | gpt-oss-120b |
| Design Arena: all code categories | 962 | 976 | o4 Mini |
| Neither model has a result on the other 3 boards here | |||
GeneralLike-for-likePublic boards, shown as published, kept out of the index1211
| Benchmark | gpt-oss-120b | o4 Mini | Leader |
|---|---|---|---|
| SAGE (Vals AI) | Not measured | 41.1% | Only o4 Mini measured |
| MedScribe (Vals AI) | Not measured | 69.1% | Only o4 Mini measured |
| IFBench | 69.0% | 68.7% | gpt-oss-120b |
| Long context reasoning (AA-LCR) | 52.0% | 61.0% | o4 Mini |
| DTBench | 76.3% | 77.6% | o4 Mini |
| LMCA | 22.1% | 26.5% | o4 Mini |
| Fiction.LiveBench | 44.4% | 77.8% | o4 Mini |
| Creative writing (Lech Mazur) | 77.1% | 75.0% | gpt-oss-120b |
| Surface Evolver Bench | 25.0% | Not measured | Only gpt-oss-120b measured |
| LMArena Text | 1366 | 1353 | gpt-oss-120b |
| LMArena Text: instruction following | 1318 | 1320 | o4 Mini |
| LMArena Text: creative writing | 1274 | 1294 | o4 Mini |
| LMArena Vision | Not measured | 1194 | Only o4 Mini measured |
| LMArena Text: English | 1375 | 1367 | gpt-oss-120b |
| LMArena Text: non-English | 1351 | 1337 | gpt-oss-120b |
| LMArena Text: Chinese | 1385 | 1354 | gpt-oss-120b |
| LMArena Text: German | 1353 | 1336 | gpt-oss-120b |
| LMArena Text: Japanese | 1331 | 1308 | gpt-oss-120b |
| LMArena Text: Korean | 1282 | 1312 | o4 Mini |
| LMArena Text: French | 1370 | 1364 | gpt-oss-120b |
| LMArena Text: Spanish | 1389 | 1346 | gpt-oss-120b |
| LMArena Text: Russian | 1343 | 1334 | gpt-oss-120b |
| LMArena Text: Polish | 1353 | 1358 | o4 Mini |
| LMArena Text: multi-turn | 1340 | 1350 | o4 Mini |
| LMArena Text: longer queries | 1319 | 1315 | gpt-oss-120b |
| LMArena Text: writing and language | 1306 | 1316 | o4 Mini |
| LMArena Text: entertainment and media | 1292 | 1308 | o4 Mini |
| LMArena Vision: English | Not measured | 1200 | Only o4 Mini measured |
| LMArena Vision: Chinese | Not measured | 1218 | Only o4 Mini measured |
| LMArena Vision: reading text | Not measured | 1197 | Only o4 Mini measured |
| LMArena Vision: humor | Not measured | 1199 | Only o4 Mini measured |
| LMArena Vision: captioning | Not measured | 1204 | Only o4 Mini measured |
| LMArena Vision: recognizing things | Not measured | 1218 | Only o4 Mini measured |
| LMArena Vision: creative writing | Not measured | 1166 | Only o4 Mini measured |
| Neither model has a result on the other 12 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | gpt-oss-120b | o4 Mini | 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-oss-120b | OpenAI o4 Mini |
|---|---|---|
| Maker | OpenAI | OpenAI |
| Weights | Open weights | No public weights listed |
| Released | August 5, 2025 | April 16, 2025 |
| Context window | 131K | 200K |
| Input $/Mtok | $0.10 | $1.10 |
| Output $/Mtok | $0.50 | $4.40 |
| Coding index | Not benchmarked | Not benchmarked |
| Independent measurements behind it | 1 | 0 |
| Cost per solved task | $0.51 | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is gpt-oss-120b better than o4 Mini for coding?
Neither model has a coding score yet, so the two cannot be ranked on coding. Pick gpt-oss-120b for output tokens 8.8x cheaper ($0.50 vs $4.40 per million) and work measured by Aider polyglot or SWE-bench Verified, where it leads.
Which is cheaper, gpt-oss-120b or o4 Mini?
gpt-oss-120b costs $0.10 per million input tokens and $0.50 per million output tokens; o4 Mini costs $1.10 and $4.40. Cost per solved task is known for gpt-oss-120b only.
Which has the bigger context window, gpt-oss-120b or o4 Mini?
o4 Mini, with 200K tokens against 131K.
How many benchmarks is the gpt-oss-120b vs o4 Mini comparison based on?
70 benchmarks have a result for both models as of October 22, 2026. gpt-oss-120b's coding index rests on 1 independent benchmark and o4 Mini's on 0. Where only one model has a result, the page says so instead of naming a winner.