Gemini 4 Argon vs GPT-4
Gemini 4 Argon leads GPT-4 on the Artificial Analysis Intelligence Index, 52.6 to 6.7, and Gemini 4 Argon costs 6.0x less per output token ($10.00 vs $60.00 per million). Updated October 21, 2026; 27 benchmarks have a result for both.
Gemini 4 Argon or GPT-4: which to pick
Only Gemini 4 Argon has a coding score, 81.0 on the Vibe Coding Index; GPT-4 has none, so the two cannot be ranked on coding.
Compare them on price, context and the boards below.
- Shared results
- 27
- Gemini 4 Argon only
- 66
- GPT-4 only
- 18
- Like-for-like categories
- 6 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 6.7.
Same board, both measured
Web design
Design Arena: websites
No call
Only Gemini 4 Argon has a Design Arena: websites result, 1315.
Directional only
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 8K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Gemini 4 Argon
Gemini 4 Argon $0.0070, GPT-4 $0.060 per turn.
List prices
At a glance
- Coding index
- Gemini 4 Argon 81.0 from 5 benchmarks, GPT-4 not benchmarked.
- Widest category
- Knowledge, 63.2 points apart on average over 4 shared benchmarks.
- Widest single gap
- LMArena Text: Chinese: Gemini 4 Argon 1611 against GPT-4 1184, 69.3 points apart on a 0 to 100 scale.
- Output price
- Gemini 4 Argon $10.00 against GPT-4 $60.00 per million output tokens, 6.0x apart.
- Context window
- Gemini 4 Argon takes 1.05M tokens, GPT-4 8K.
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-4 | Ties |
|---|---|---|---|---|
| Coding | 2 | 0 | ||
| Intelligence | 2 | 0 | ||
| Reasoning | 3 | 0 | ||
| Math | 2 | 0 | ||
| Knowledge | 4 | 0 | ||
| General | 14 | 0 | ||
| All shared boards | 27 | 0 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index20
| Benchmark | Gemini 4 Argon | GPT-4 | Leader |
|---|---|---|---|
| SWE-bench Verified | Not measured | 22.4% | Only GPT-4 measured |
| SWE-bench Lite | Not measured | 39.7% | Only GPT-4 measured |
| SWE-bench (full test set) | Not measured | 12.5% | Only GPT-4 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 | 13.1 | Only GPT-4 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 |
| SciCode | 61.8% | Not measured | Only Gemini 4 Argon measured |
| FrontierCode | 47.5% | Not measured | Only Gemini 4 Argon measured |
| FrontierSWE | 55.0% | Not measured | Only Gemini 4 Argon measured |
| ALE-Bench | 2100.1 | Not measured | Only Gemini 4 Argon measured |
| LMArena Text: coding | 1546 | 1209 | Gemini 4 Argon |
| LMArena Text: software and IT | 1556 | 1195 | 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% | Not measured | Only Gemini 4 Argon measured |
| Neither model has a result on the other 15 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index20
| Benchmark | Gemini 4 Argon | GPT-4 | Leader |
|---|---|---|---|
| AA Intelligence Index | 52.6 | 6.7 | Gemini 4 Argon |
| Epoch Capabilities Index | 166.4 | 125.7 | Gemini 4 Argon |
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index18 boards, none shared
| Benchmark | Gemini 4 Argon | GPT-4 | Leader |
|---|---|---|---|
| Design Arena: spreadsheets | 1142 | 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 |
| APEX-Agents | 82.4% | Not measured | Only Gemini 4 Argon measured |
| Vending-Bench 2 | $13,718 | Not measured | Only Gemini 4 Argon measured |
| Neither model has a result on the other 23 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index30
| Benchmark | Gemini 4 Argon | GPT-4 | Leader |
|---|---|---|---|
| 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 | 34.9% | Only GPT-4 measured |
| Humanity's Last Exam (Artificial Analysis run) | 57.1% | Not measured | Only Gemini 4 Argon measured |
| GPQA Diamond (Epoch AI run) | 96.4% | Not measured | Only Gemini 4 Argon measured |
| ARC-AGI | 98.5% | Not measured | Only Gemini 4 Argon measured |
| ARC-AGI-2 | 91.3% | Not measured | Only Gemini 4 Argon measured |
| Chess puzzles | 59.0% | Not measured | Only Gemini 4 Argon measured |
| Mystery game puzzles | 64.0% | Not measured | Only Gemini 4 Argon measured |
| EBR-bench | 64.8% | Not measured | Only Gemini 4 Argon measured |
| BIG-Bench Hard | Not measured | 75.1% | Only GPT-4 measured |
| LMArena Text: hard prompts | 1546 | 1200 | Gemini 4 Argon |
| LMArena Text: expert | 1550 | 1149 | Gemini 4 Argon |
| LMArena Text: hard prompts in English | 1548 | 1209 | Gemini 4 Argon |
| Neither model has a result on the other 8 boards here | |||
MathLike-for-likePublic boards, shown as published, kept out of the index20
| Benchmark | Gemini 4 Argon | GPT-4 | Leader |
|---|---|---|---|
| OTIS Mock AIME | 100.0% | Not measured | Only Gemini 4 Argon measured |
| 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 |
| GSM8K | Not measured | 92.0% | Only GPT-4 measured |
| LMArena Text: math | 1536 | 1230 | Gemini 4 Argon |
| LMArena Text: mathematical work | 1557 | 1228 | Gemini 4 Argon |
| Neither model has a result on the other 6 boards here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index40
| Benchmark | Gemini 4 Argon | GPT-4 | Leader |
|---|---|---|---|
| LegalBench (Vals AI) | 88.3% | Not measured | Only Gemini 4 Argon measured |
| MedCode (Vals AI) | 58.8% | Not measured | Only Gemini 4 Argon measured |
| MMLU Pro (Artificial Analysis run) | Not measured | 56.2% | Only GPT-4 measured |
| SimpleQA Verified | 76.0% | Not measured | Only Gemini 4 Argon measured |
| MMLU | Not measured | 86.4% | Only GPT-4 measured |
| AI2 Reasoning Challenge | Not measured | 96.3% | Only GPT-4 measured |
| LMArena Text: science | 1548 | 1177 | Gemini 4 Argon |
| LMArena Text: medicine and healthcare | 1555 | 1145 | Gemini 4 Argon |
| LMArena Text: legal and government | 1548 | 1191 | Gemini 4 Argon |
| LMArena Text: business and finance | 1525 | 1145 | Gemini 4 Argon |
| Neither model has a result on the other 8 boards here | |||
Web designDirectional onlyPublic boards, shown as published, kept out of the index7 boards, none shared
| Benchmark | Gemini 4 Argon | GPT-4 | Leader |
|---|---|---|---|
| Design Arena: websites | 1315 | Not measured | Only Gemini 4 Argon measured |
| Design Arena: UI components | 1331 | Not measured | Only Gemini 4 Argon measured |
| Design Arena: game dev | 1375 | Not measured | Only Gemini 4 Argon measured |
| Design Arena: data viz | 1336 | Not measured | Only Gemini 4 Argon measured |
| Design Arena: 3D | 1389 | Not measured | Only Gemini 4 Argon measured |
| Design Arena: all code categories | 1329 | Not measured | Only Gemini 4 Argon measured |
| 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 index140
| Benchmark | Gemini 4 Argon | GPT-4 | 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 | 33.2% | Only GPT-4 measured |
| Long context reasoning (AA-LCR) | 79.7% | Not measured | Only Gemini 4 Argon measured |
| DTBench | 97.6% | 62.7% | Gemini 4 Argon |
| LMCA | 63.7% | 17.1% | Gemini 4 Argon |
| Furniture assembly | 72.5% | Not measured | Only Gemini 4 Argon measured |
| HellaSwag | Not measured | 95.3% | Only GPT-4 measured |
| WinoGrande | Not measured | 87.5% | Only GPT-4 measured |
| LMArena Text | 1532 | 1206 | Gemini 4 Argon |
| LMArena Text: instruction following | 1534 | 1201 | Gemini 4 Argon |
| LMArena Text: creative writing | 1527 | 1191 | Gemini 4 Argon |
| LMArena Text: English | 1538 | 1220 | Gemini 4 Argon |
| LMArena Text: non-English | 1522 | 1194 | Gemini 4 Argon |
| LMArena Text: Chinese | 1611 | 1184 | Gemini 4 Argon |
| LMArena Text: German | Not measured | 1198 | Only GPT-4 measured |
| LMArena Text: Japanese | Not measured | 1137 | Only GPT-4 measured |
| LMArena Text: Korean | Not measured | 1087 | Only GPT-4 measured |
| LMArena Text: French | Not measured | 1220 | Only GPT-4 measured |
| LMArena Text: Spanish | 1503 | 1197 | Gemini 4 Argon |
| LMArena Text: Russian | 1534 | 1195 | Gemini 4 Argon |
| LMArena Text: Polish | Not measured | 1265 | Only GPT-4 measured |
| LMArena Text: multi-turn | 1556 | 1206 | Gemini 4 Argon |
| LMArena Text: longer queries | 1547 | 1190 | Gemini 4 Argon |
| LMArena Text: writing and language | 1529 | 1219 | Gemini 4 Argon |
| LMArena Text: entertainment and media | 1527 | 1184 | Gemini 4 Argon |
| Neither model has a result on the other 17 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | Gemini 4 Argon | GPT-4 | 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
Gemini 4 Argon costs less
Repository review
50K input + 3K output tokens
Gemini 4 Argon costs less
Agent loop
200K input + 10K output tokens
Gemini 4 Argon 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-4 |
|---|---|---|
| Maker | OpenAI | |
| Weights | No public weights listed | No public weights listed |
| Released | October 13, 2026 | May 28, 2023 |
| Context window | 1.05M | 8K |
| Input $/Mtok | $2.00 | $30.00 |
| Output $/Mtok | $10.00 | $60.00 |
| Coding index | 81.0 | Not benchmarked |
| Independent measurements behind it | 5 | 0 |
| Cost per solved task | Not computable | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is Gemini 4 Argon better than GPT-4 for coding?
Only Gemini 4 Argon has a coding score, 81.0 on the Vibe Coding Index; GPT-4 has none, so the two cannot be ranked on coding. Compare them on price, context and the boards below.
Which is cheaper, Gemini 4 Argon or GPT-4?
Gemini 4 Argon costs $2.00 per million input tokens and $10.00 per million output tokens; GPT-4 costs $30.00 and $60.00. Cost per solved task is known for neither of them.
Which has the bigger context window, Gemini 4 Argon or GPT-4?
Gemini 4 Argon, with 1.05M tokens against 8K.
How many benchmarks is the Gemini 4 Argon vs GPT-4 comparison based on?
27 benchmarks have a result for both models as of October 21, 2026. Gemini 4 Argon's coding index rests on 5 independent benchmarks and GPT-4's on 0. Where only one model has a result, the page says so instead of naming a winner.