Gemini 4 Argon vs gpt-oss-120b
Gemini 4 Argon leads gpt-oss-120b on the Artificial Analysis Intelligence Index, 52.6 to 11.6, and gpt-oss-120b costs 20.0x less per output token ($0.50 vs $10.00 per million). Updated October 22, 2026; 44 benchmarks have a result for both.
Gemini 4 Argon or gpt-oss-120b: which to pick
Only Gemini 4 Argon has a coding score, 81.0 on the Vibe Coding Index; gpt-oss-120b has none, so the two cannot be ranked on coding.
Pick gpt-oss-120b for output tokens 20.0x cheaper ($0.50 vs $10.00 per million).
- Shared results
- 44
- Gemini 4 Argon only
- 50
- gpt-oss-120b only
- 37
- 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
Only Gemini 4 Argon has a coding score, so no call is made.
One side not measured
Intelligence
AA Intelligence Index
Gemini 4 Argon
Gemini 4 Argon leads, 52.6 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
No call
Only gpt-oss-120b has a GPQA Diamond result, 78.5%.
Directional only
Math
AIME
No call
Only gpt-oss-120b has a AIME result, 92.6%.
Directional only
Knowledge
MMLU Pro
No call
Only gpt-oss-120b has a MMLU Pro result, 79.2%.
Directional only
Web design
Design Arena: websites
Gemini 4 Argon
Gemini 4 Argon leads, 1315 against 967.
Same board, both measured
General
Vals Index
No call
Only Gemini 4 Argon has a Vals Index result, 69.2%.
Directional only
Long documents
Listed context window
Gemini 4 Argon
Gemini 4 Argon takes 1.05M tokens against 131K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
gpt-oss-120b
Gemini 4 Argon $0.0070, gpt-oss-120b $0.0003 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
- Gemini 4 Argon 81.0 from 5 benchmarks, gpt-oss-120b not benchmarked.
- Widest category
- Agentic work, 81.9 points apart on average over 2 shared benchmarks.
- Widest single gap
- Vending-Bench 2: Gemini 4 Argon $13,718 against gpt-oss-120b -$22, 85.7 points apart on a 0 to 100 scale.
- Output price
- Gemini 4 Argon $10.00 against gpt-oss-120b $0.50 per million output tokens, 20.0x apart.
- Context window
- Gemini 4 Argon 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 | Gemini 4 Argon | Bars | gpt-oss-120b | Ties |
|---|---|---|---|---|
| Coding | 5 | 0 | ||
| Intelligence | 2 | 0 | ||
| Agentic work | 2 | 0 | ||
| Reasoning | 6 | 0 | ||
| Math | 3 | 0 | ||
| Knowledge | 5 | 0 | ||
| Web design | 6 | 0 | ||
| General | 15 | 0 | ||
| All shared boards | 44 | 0 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index50
| Benchmark | Gemini 4 Argon | gpt-oss-120b | Leader |
|---|---|---|---|
| Aider polyglot | Not measured | 41.8% | Only gpt-oss-120b measured |
| SWE-bench Verified | Not measured | 26.0% | Only gpt-oss-120b measured |
| LiveBench coding | 89.7% | Not measured | Only Gemini 4 Argon measured |
| LMArena WebDev | 1678 | Not measured | Only Gemini 4 Argon measured |
| AA Coding Index | Not measured | 30.4 | Only gpt-oss-120b measured |
| LiveCodeBench (Vals AI) | Not measured | 83.2% | Only gpt-oss-120b measured |
| SWE-bench Verified (Vals AI) | Not measured | 33.6% | Only gpt-oss-120b measured |
| Terminal-Bench 4 (Vals AI) | 57.6% | Not measured | Only Gemini 4 Argon measured |
| Vibe Code Bench (Vals AI) | 91.9% | Not measured | Only Gemini 4 Argon measured |
| Code migration (Vals AI) | 68.2% | Not measured | Only Gemini 4 Argon measured |
| ProgramBench (Vals AI) | 2.5% | Not measured | Only Gemini 4 Argon measured |
| IOI (Vals AI) | 100.0% | Not measured | Only Gemini 4 Argon measured |
| Terminal-Bench 2.1 (Vals AI) | 57.7% | Not measured | Only Gemini 4 Argon measured |
| SWE-bench Multimodal (Vals AI) | 56.0% | Not measured | Only Gemini 4 Argon measured |
| Vibe Code Bench 1-100 (Vals AI) | 21.2% | Not measured | Only Gemini 4 Argon measured |
| CyberBench (Vals AI) | 77.9% | Not measured | Only Gemini 4 Argon measured |
| LiveCodeBench (Artificial Analysis run) | Not measured | 87.8% | Only gpt-oss-120b measured |
| SciCode | 61.8% | 34.0% | Gemini 4 Argon |
| Terminal-Bench Hard (Artificial Analysis run) | Not measured | 23.5% | Only gpt-oss-120b measured |
| Terminal-Bench | Not measured | 18.7% | Only gpt-oss-120b measured |
| FrontierCode | 47.5% | Not measured | Only Gemini 4 Argon measured |
| FrontierSWE | 55.0% | Not measured | Only Gemini 4 Argon measured |
| WeirdML | Not measured | 48.2% | Only gpt-oss-120b measured |
| MirrorCode | 58.9% | Not measured | Only Gemini 4 Argon measured |
| ALE-Bench | 2100.1 | 575.6 | Gemini 4 Argon |
| LMArena Text: coding | 1546 | 1379 | Gemini 4 Argon |
| LMArena Text: software and IT | 1556 | 1387 | Gemini 4 Argon |
| LMArena WebDev: React | 1692 | Not measured | Only Gemini 4 Argon measured |
| LMArena WebDev: HTML | 1643 | Not measured | Only Gemini 4 Argon measured |
| SciCode | 12.3% | 7.7% | Gemini 4 Argon |
| Neither model has a result on the other 9 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index20
| Benchmark | Gemini 4 Argon | gpt-oss-120b | Leader |
|---|---|---|---|
| AA Intelligence Index | 52.6 | 11.6 | Gemini 4 Argon |
| Epoch Capabilities Index | 166.4 | 139.8 | Gemini 4 Argon |
Agentic workLike-for-likePublic boards, shown as published, kept out of the index20
| Benchmark | Gemini 4 Argon | gpt-oss-120b | Leader |
|---|---|---|---|
| AA Agentic Index | Not measured | 3.7 | Only gpt-oss-120b measured |
| Design Arena: spreadsheets | 1157 | Not measured | Only Gemini 4 Argon measured |
| LiveBench research | 83.1% | Not measured | Only Gemini 4 Argon measured |
| LiveBench browser | 92.0% | Not measured | Only Gemini 4 Argon measured |
| LiveBench long agentic | 69.9% | Not measured | Only Gemini 4 Argon measured |
| SREBench (Vals AI) | 44.3% | Not measured | Only Gemini 4 Argon measured |
| Finance Agent (Vals AI) | 65.4% | Not measured | Only Gemini 4 Argon measured |
| Tax Agent Bench (Vals AI) | 44.6% | Not measured | Only Gemini 4 Argon measured |
| Legal Research Bench (Vals AI) | 54.8% | Not measured | Only Gemini 4 Argon measured |
| Harvey's Legal Agent Benchmark (Vals AI) | 27.1% | Not measured | Only Gemini 4 Argon measured |
| Excel Modeling Benchmark (Vals AI) | 75.2% | Not measured | Only Gemini 4 Argon measured |
| BioMysteryBench (Vals AI) | 76.3% | Not measured | Only Gemini 4 Argon measured |
| Terminal-Bench-Science (Vals AI) | 44.3% | Not measured | Only Gemini 4 Argon measured |
| Vals Science Index | 55.4% | Not measured | Only Gemini 4 Argon measured |
| Time Horizon Index (Vals AI) | 52.5% | Not measured | Only Gemini 4 Argon measured |
| CUA-bench (Vals AI) | 4.8% | Not measured | Only Gemini 4 Argon measured |
| Robo-bench (Vals AI) | 0.8% | Not measured | Only Gemini 4 Argon measured |
| τ²-Bench Telecom | Not measured | 65.8% | Only gpt-oss-120b measured |
| APEX-Agents | 82.4% | 4.4% | Gemini 4 Argon |
| METR time horizons | Not measured | 56.6% | Only gpt-oss-120b measured |
| Vending-Bench 2 | $13,718 | -$22 | Gemini 4 Argon |
| BrowseComp-Plus | Not measured | 67.0% | Only gpt-oss-120b measured |
| Neither model has a result on the other 19 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index60
| Benchmark | Gemini 4 Argon | gpt-oss-120b | Leader |
|---|---|---|---|
| GPQA Diamond | Not measured | 78.5% | Only gpt-oss-120b measured |
| LiveBench reasoning | 95.1% | Not measured | Only Gemini 4 Argon measured |
| MysteryMechanism (Vals AI) | 45.5% | Not measured | Only Gemini 4 Argon measured |
| GPQA Diamond (Artificial Analysis run) | Not measured | 78.2% | Only gpt-oss-120b measured |
| Humanity's Last Exam (Artificial Analysis run) | 57.1% | 19.6% | Gemini 4 Argon |
| GPQA Diamond (Epoch AI run) | 96.4% | 75.8% | Gemini 4 Argon |
| ARC-AGI | 98.5% | Not measured | Only Gemini 4 Argon measured |
| ARC-AGI-2 | 91.3% | Not measured | Only Gemini 4 Argon measured |
| SimpleBench | Not measured | 22.1% | Only gpt-oss-120b measured |
| Chess puzzles | 59.0% | Not measured | Only Gemini 4 Argon measured |
| Mystery game puzzles | 64.0% | 2.0% | Gemini 4 Argon |
| EBR-bench | 64.8% | Not measured | Only Gemini 4 Argon measured |
| LMArena Text: hard prompts | 1546 | 1364 | Gemini 4 Argon |
| LMArena Text: expert | 1550 | 1356 | Gemini 4 Argon |
| LMArena Text: hard prompts in English | 1548 | 1368 | Gemini 4 Argon |
| Kagi LLM Benchmark | Not measured | 58.6% | Only gpt-oss-120b measured |
| Neither model has a result on the other 6 boards here | |||
MathLike-for-likePublic boards, shown as published, kept out of the index30
| Benchmark | Gemini 4 Argon | gpt-oss-120b | Leader |
|---|---|---|---|
| AIME | Not measured | 92.6% | Only gpt-oss-120b measured |
| MATH 500 (Vals AI) | Not measured | 94.8% | Only gpt-oss-120b measured |
| MGSM (Vals AI) | Not measured | 92.0% | Only gpt-oss-120b measured |
| AA Math Index | Not measured | 93.4 | Only gpt-oss-120b measured |
| AIME 2025 (Artificial Analysis run) | Not measured | 93.4% | Only gpt-oss-120b measured |
| OTIS Mock AIME | 100.0% | 88.9% | Gemini 4 Argon |
| FrontierMath, tiers 1 to 3 | 86.0% | Not measured | Only Gemini 4 Argon measured |
| FrontierMath, tier 4 | 78.0% | Not measured | Only Gemini 4 Argon measured |
| ProofBench | 99.0% | Not measured | Only Gemini 4 Argon measured |
| LMArena Text: math | 1536 | 1389 | Gemini 4 Argon |
| LMArena Text: mathematical work | 1557 | 1386 | Gemini 4 Argon |
| Neither model has a result on the other 2 boards here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index50
| Benchmark | Gemini 4 Argon | gpt-oss-120b | Leader |
|---|---|---|---|
| MMLU Pro | Not measured | 79.2% | Only gpt-oss-120b measured |
| LegalBench (Vals AI) | 88.3% | 75.9% | Gemini 4 Argon |
| CaseLaw (Vals AI) | Not measured | 48.8% | Only gpt-oss-120b measured |
| CorpFin (Vals AI) | Not measured | 58.2% | Only gpt-oss-120b measured |
| TaxEval (Vals AI) | Not measured | 71.6% | Only gpt-oss-120b measured |
| MedQA (Vals AI) | Not measured | 91.4% | Only gpt-oss-120b measured |
| MedCode (Vals AI) | 58.8% | Not measured | Only Gemini 4 Argon measured |
| MMLU Pro (Artificial Analysis run) | Not measured | 80.8% | Only gpt-oss-120b measured |
| SimpleQA Verified | 76.0% | Not measured | Only Gemini 4 Argon measured |
| LMArena Text: science | 1548 | 1382 | Gemini 4 Argon |
| LMArena Text: medicine and healthcare | 1555 | 1388 | Gemini 4 Argon |
| LMArena Text: legal and government | 1548 | 1355 | Gemini 4 Argon |
| LMArena Text: business and finance | 1525 | 1359 | Gemini 4 Argon |
| Neither model has a result on the other 5 boards here | |||
Web designLike-for-likePublic boards, shown as published, kept out of the index60
| Benchmark | Gemini 4 Argon | gpt-oss-120b | Leader |
|---|---|---|---|
| Design Arena: websites | 1315 | 967 | Gemini 4 Argon |
| Design Arena: UI components | 1333 | 924 | Gemini 4 Argon |
| Design Arena: game dev | 1377 | 992 | Gemini 4 Argon |
| Design Arena: data viz | 1332 | 987 | Gemini 4 Argon |
| Design Arena: 3D | 1388 | 901 | Gemini 4 Argon |
| Design Arena: all code categories | 1329 | 962 | Gemini 4 Argon |
| LiveBench design | 73.7% | Not measured | Only Gemini 4 Argon measured |
| Neither model has a result on the other 2 boards here | |||
GeneralLike-for-likePublic boards, shown as published, kept out of the index150
| Benchmark | Gemini 4 Argon | gpt-oss-120b | Leader |
|---|---|---|---|
| Vals Index | 69.2% | Not measured | Only Gemini 4 Argon measured |
| LiveBench data analysis | 85.2% | Not measured | Only Gemini 4 Argon measured |
| Public Benefits Bench (Vals AI) | 69.8% | Not measured | Only Gemini 4 Argon measured |
| SAGE (Vals AI) | 53.6% | Not measured | Only Gemini 4 Argon measured |
| MedScribe (Vals AI) | 87.4% | Not measured | Only Gemini 4 Argon measured |
| IFBench | Not measured | 69.0% | Only gpt-oss-120b measured |
| Long context reasoning (AA-LCR) | 79.7% | 52.0% | Gemini 4 Argon |
| DTBench | 97.6% | 76.3% | Gemini 4 Argon |
| LMCA | 63.7% | 22.1% | Gemini 4 Argon |
| Fiction.LiveBench | Not measured | 44.4% | Only gpt-oss-120b measured |
| 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 |
| Furniture assembly | 72.5% | Not measured | Only Gemini 4 Argon measured |
| LMArena Text | 1532 | 1366 | Gemini 4 Argon |
| LMArena Text: instruction following | 1534 | 1318 | Gemini 4 Argon |
| LMArena Text: creative writing | 1527 | 1274 | Gemini 4 Argon |
| LMArena Text: English | 1538 | 1375 | Gemini 4 Argon |
| LMArena Text: non-English | 1522 | 1351 | Gemini 4 Argon |
| LMArena Text: Chinese | 1611 | 1385 | Gemini 4 Argon |
| LMArena Text: German | Not measured | 1353 | Only gpt-oss-120b measured |
| LMArena Text: Japanese | Not measured | 1331 | Only gpt-oss-120b measured |
| LMArena Text: Korean | Not measured | 1282 | Only gpt-oss-120b measured |
| LMArena Text: French | Not measured | 1370 | Only gpt-oss-120b measured |
| LMArena Text: Spanish | 1503 | 1389 | Gemini 4 Argon |
| LMArena Text: Russian | 1534 | 1343 | Gemini 4 Argon |
| LMArena Text: Polish | Not measured | 1353 | Only gpt-oss-120b measured |
| LMArena Text: multi-turn | 1556 | 1340 | Gemini 4 Argon |
| LMArena Text: longer queries | 1547 | 1319 | Gemini 4 Argon |
| LMArena Text: writing and language | 1529 | 1306 | Gemini 4 Argon |
| LMArena Text: entertainment and media | 1527 | 1292 | Gemini 4 Argon |
| Neither model has a result on the other 16 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | Gemini 4 Argon | 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 | Google Gemini 4 Argon | OpenAI gpt-oss-120b |
|---|---|---|
| Maker | OpenAI | |
| Weights | No public weights listed | Open weights |
| Released | October 13, 2026 | August 5, 2025 |
| Context window | 1.05M | 131K |
| Input $/Mtok | $2.00 | $0.10 |
| Output $/Mtok | $10.00 | $0.50 |
| Coding index | 81.0 | Not benchmarked |
| Independent measurements behind it | 5 | 1 |
| Cost per solved task | Not computable | $0.51 |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is Gemini 4 Argon better than gpt-oss-120b for coding?
Only Gemini 4 Argon has a coding score, 81.0 on the Vibe Coding Index; gpt-oss-120b has none, so the two cannot be ranked on coding. Pick gpt-oss-120b for output tokens 20.0x cheaper ($0.50 vs $10.00 per million).
Which is cheaper, Gemini 4 Argon or gpt-oss-120b?
Gemini 4 Argon costs $2.00 per million input tokens and $10.00 per million output tokens; gpt-oss-120b costs $0.10 and $0.50. Cost per solved task is known for gpt-oss-120b only.
Which has the bigger context window, Gemini 4 Argon or gpt-oss-120b?
Gemini 4 Argon, with 1.05M tokens against 131K.
How many benchmarks is the Gemini 4 Argon vs gpt-oss-120b comparison based on?
44 benchmarks have a result for both models as of October 22, 2026. Gemini 4 Argon's coding index rests on 5 independent benchmarks and gpt-oss-120b's on 1. Where only one model has a result, the page says so instead of naming a winner.