GPT-4o (2024-08-06) vs GPT-6.1 Sol
Updated October 21, 2026. 34 benchmarks have a result for both. Coding is ranked on the Vibe Coding Index; every other board is shown as published.
vs boards won of 34 shared
Decision reading
Pick GPT-6.1 Sol for coding: it scores 88.7 on the Vibe Coding Index against 23.1 for GPT-4o (2024-08-06).
GPT-4o (2024-08-06) is neither cheaper nor larger in context, and leads no benchmark both models were measured on.
Model AGPT-4o (2024-08-06)OpenAI23.1/1001 independent benchmarkNo cost per solved taskModel BGPT-6.1 SolOpenAI88.7/1002 independent benchmarksNo cost per solved task
- Shared results
- 34
- GPT-4o (2024-08-06) only
- 24
- GPT-6.1 Sol only
- 61
- Like-for-like categories
- 6 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-6.1 Sol
GPT-6.1 Sol scores 88.7 against 23.1.
1 and 2 benchmarks behind the scores
Intelligence
AA Intelligence Index
GPT-6.1 Sol
GPT-6.1 Sol leads, 51.8 against 7.7.
Same board, both measured
Math
AIME
No call
Only GPT-4o (2024-08-06) has a AIME result, 14.0%.
Directional only
Knowledge
MMLU Pro
No call
Only GPT-4o (2024-08-06) has a MMLU Pro result, 74.1%.
Directional only
Web design
Design Arena: websites
No call
Only GPT-6.1 Sol has a Design Arena: websites result, 1321.
Directional only
General
Vals Index
No call
Only GPT-6.1 Sol has a Vals Index result, 63.9%.
Directional only
Long documents
Listed context window
GPT-6.1 Sol
GPT-6.1 Sol takes 1.05M tokens against 128K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
GPT-6.1 Sol
GPT-4o (2024-08-06) $0.0075, GPT-6.1 Sol $0.0070 per turn.
List prices
At a glance
- Coding index
- GPT-4o (2024-08-06) 23.1 from 1 benchmark, GPT-6.1 Sol 88.7 from 2 benchmarks.
- Widest category
- Math, 64.8 points apart on average over 4 shared benchmarks.
- Widest single gap
- OTIS Mock AIME: GPT-4o (2024-08-06) 6.4% against GPT-6.1 Sol 100.0%, 93.6 points apart on a 0 to 100 scale.
- Output price
- Both cost $10.00 per million output tokens.
- Context window
- GPT-4o (2024-08-06) takes 128K tokens, GPT-6.1 Sol 1.05M.
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-4o (2024-08-06) | Bars | GPT-6.1 Sol | Ties |
|---|---|---|---|---|
| Coding | 0 | 2 | ||
| Intelligence | 0 | 1 | ||
| Reasoning | 0 | 6 | ||
| Math | 0 | 4 | ||
| Knowledge | 0 | 5 | ||
| General | 0 | 16 | ||
| All shared boards | 0 | 34 |
CodingLike-for-likeFour of these boards feed the Vibe Coding Index02
| Benchmark | GPT-4o (2024-08-06) | GPT-6.1 Sol | Leader |
|---|---|---|---|
| Aider polyglot | 23.1% | Not measured | Only GPT-4o (2024-08-06) measured |
| SWE-bench Lite | 21.7% | Not measured | Only GPT-4o (2024-08-06) measured |
| LiveBench coding | Not measured | 96.0% | Only GPT-6.1 Sol measured |
| LMArena WebDev | Not measured | 1753 | Only GPT-6.1 Sol measured |
| Terminal-Bench 4 (Vals AI) | Not measured | 55.0% | Only GPT-6.1 Sol measured |
| Vibe Code Bench (Vals AI) | Not measured | 88.9% | Only GPT-6.1 Sol measured |
| Code migration (Vals AI) | Not measured | 65.1% | Only GPT-6.1 Sol measured |
| ProgramBench (Vals AI) | Not measured | 3.0% | Only GPT-6.1 Sol measured |
| IOI (Vals AI) | Not measured | 96.9% | Only GPT-6.1 Sol measured |
| SWE-bench Multimodal (Vals AI) | Not measured | 43.5% | Only GPT-6.1 Sol measured |
| CyberBench (Vals AI) | Not measured | 39.3% | Only GPT-6.1 Sol measured |
| LiveCodeBench (Artificial Analysis run) | 31.7% | Not measured | Only GPT-4o (2024-08-06) measured |
| SciCode | Not measured | 55.8% | Only GPT-6.1 Sol measured |
| Terminal-Bench Hard (Artificial Analysis run) | 8.3% | Not measured | Only GPT-4o (2024-08-06) measured |
| FrontierCode | Not measured | 50.2% | Only GPT-6.1 Sol measured |
| ALE-Bench | Not measured | 2743.8 | Only GPT-6.1 Sol measured |
| LMArena Text: coding | 1283 | 1478 | GPT-6.1 Sol |
| LMArena Text: software and IT | 1278 | 1476 | GPT-6.1 Sol |
| LMArena WebDev: React | Not measured | 1754 | Only GPT-6.1 Sol measured |
| LMArena WebDev: HTML | Not measured | 1800 | Only GPT-6.1 Sol measured |
| LMArena WebDev: from an image | Not measured | 1702 | Only GPT-6.1 Sol measured |
| Neither model has a result on the other 17 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | GPT-4o (2024-08-06) | GPT-6.1 Sol | Leader |
|---|---|---|---|
| AA Intelligence Index | 7.7 | 51.8 | GPT-6.1 Sol |
| Epoch Capabilities Index | Not measured | 168.4 | Only GPT-6.1 Sol measured |
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index18 boards, none shared
| Benchmark | GPT-4o (2024-08-06) | GPT-6.1 Sol | Leader |
|---|---|---|---|
| Design Arena: agents building mobile apps | Not measured | 1190 | Only GPT-6.1 Sol measured |
| Design Arena: spreadsheets | Not measured | 1250 | Only GPT-6.1 Sol measured |
| LiveBench research | Not measured | 83.5% | Only GPT-6.1 Sol measured |
| LiveBench browser | Not measured | 88.0% | Only GPT-6.1 Sol measured |
| LiveBench long agentic | Not measured | 73.0% | Only GPT-6.1 Sol measured |
| SREBench (Vals AI) | Not measured | 50.8% | Only GPT-6.1 Sol measured |
| Finance Agent (Vals AI) | Not measured | 52.0% | Only GPT-6.1 Sol measured |
| Tax Agent Bench (Vals AI) | Not measured | 21.8% | Only GPT-6.1 Sol measured |
| Legal Research Bench (Vals AI) | Not measured | 38.5% | Only GPT-6.1 Sol measured |
| Harvey's Legal Agent Benchmark (Vals AI) | Not measured | 6.3% | Only GPT-6.1 Sol measured |
| Excel Modeling Benchmark (Vals AI) | Not measured | 70.8% | Only GPT-6.1 Sol measured |
| BioMysteryBench (Vals AI) | Not measured | 79.6% | Only GPT-6.1 Sol measured |
| Terminal-Bench-Science (Vals AI) | Not measured | 52.9% | Only GPT-6.1 Sol measured |
| Vals Science Index | Not measured | 59.6% | Only GPT-6.1 Sol measured |
| Robo-bench (Vals AI) | Not measured | 28.3% | Only GPT-6.1 Sol measured |
| τ²-Bench Telecom | 28.9% | Not measured | Only GPT-4o (2024-08-06) measured |
| APEX-Agents | Not measured | 60.0% | Only GPT-6.1 Sol measured |
| SpireClimb | Not measured | 24.7% | Only GPT-6.1 Sol measured |
| Neither model has a result on the other 21 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index06
| Benchmark | GPT-4o (2024-08-06) | GPT-6.1 Sol | Leader |
|---|---|---|---|
| LiveBench reasoning | Not measured | 92.6% | Only GPT-6.1 Sol measured |
| MysteryMechanism (Vals AI) | Not measured | 46.4% | Only GPT-6.1 Sol measured |
| MMMU Pro (Vals AI) | 64.0% | Not measured | Only GPT-4o (2024-08-06) measured |
| GPQA Diamond (Artificial Analysis run) | 52.1% | Not measured | Only GPT-4o (2024-08-06) measured |
| Humanity's Last Exam (Artificial Analysis run) | 2.3% | 52.9% | GPT-6.1 Sol |
| GPQA Diamond (Epoch AI run) | 49.2% | 95.4% | GPT-6.1 Sol |
| ARC-AGI | Not measured | 98.5% | Only GPT-6.1 Sol measured |
| ARC-AGI-2 | Not measured | 94.2% | Only GPT-6.1 Sol measured |
| SimpleBench | 17.8% | Not measured | Only GPT-4o (2024-08-06) measured |
| Chess puzzles | 6.0% | 68.0% | GPT-6.1 Sol |
| Mystery game puzzles | Not measured | 80.0% | Only GPT-6.1 Sol measured |
| EBR-bench | Not measured | 54.3% | Only GPT-6.1 Sol measured |
| LMArena Text: hard prompts | 1264 | 1463 | GPT-6.1 Sol |
| LMArena Text: expert | 1241 | 1489 | GPT-6.1 Sol |
| LMArena Text: hard prompts in English | 1277 | 1465 | GPT-6.1 Sol |
| LMArena Vision: diagrams | Not measured | 1306 | Only GPT-6.1 Sol measured |
| LMArena Vision: homework | Not measured | 1356 | Only GPT-6.1 Sol measured |
| Neither model has a result on the other 4 boards here | |||
MathLike-for-likePublic boards, shown as published, kept out of the index04
| Benchmark | GPT-4o (2024-08-06) | GPT-6.1 Sol | Leader |
|---|---|---|---|
| AIME | 14.0% | Not measured | Only GPT-4o (2024-08-06) measured |
| MATH 500 (Vals AI) | 75.2% | Not measured | Only GPT-4o (2024-08-06) measured |
| MGSM (Vals AI) | 90.7% | Not measured | Only GPT-4o (2024-08-06) measured |
| OTIS Mock AIME | 6.4% | 100.0% | GPT-6.1 Sol |
| FrontierMath, tiers 1 to 3 | 0.4% | 93.7% | GPT-6.1 Sol |
| FrontierMath, tier 4 | Not measured | 100.0% | Only GPT-6.1 Sol measured |
| ProofBench | Not measured | 99.0% | Only GPT-6.1 Sol measured |
| MATH level 5 | 53.3% | Not measured | Only GPT-4o (2024-08-06) measured |
| LMArena Text: math | 1285 | 1489 | GPT-6.1 Sol |
| LMArena Text: mathematical work | 1283 | 1513 | GPT-6.1 Sol |
| Neither model has a result on the other 3 boards here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index05
| Benchmark | GPT-4o (2024-08-06) | GPT-6.1 Sol | Leader |
|---|---|---|---|
| MMLU Pro | 74.1% | Not measured | Only GPT-4o (2024-08-06) measured |
| LegalBench (Vals AI) | 80.1% | Not measured | Only GPT-4o (2024-08-06) measured |
| CorpFin (Vals AI) | 39.4% | Not measured | Only GPT-4o (2024-08-06) measured |
| TaxEval (Vals AI) | 71.1% | Not measured | Only GPT-4o (2024-08-06) measured |
| MortgageTax (Vals AI) | 61.0% | Not measured | Only GPT-4o (2024-08-06) measured |
| MedQA (Vals AI) | 88.2% | Not measured | Only GPT-4o (2024-08-06) measured |
| MedCode (Vals AI) | Not measured | 48.8% | Only GPT-6.1 Sol measured |
| SimpleQA Verified | 26.0% | 73.9% | GPT-6.1 Sol |
| MMLU | 84.3% | Not measured | Only GPT-4o (2024-08-06) measured |
| LMArena Text: science | 1274 | 1444 | GPT-6.1 Sol |
| LMArena Text: medicine and healthcare | 1252 | 1433 | GPT-6.1 Sol |
| LMArena Text: legal and government | 1275 | 1471 | GPT-6.1 Sol |
| LMArena Text: business and finance | 1232 | 1445 | GPT-6.1 Sol |
| Neither model has a result on the other 4 boards here | |||
Web designDirectional onlyPublic boards, shown as published, kept out of the index7 boards, none shared
| Benchmark | GPT-4o (2024-08-06) | GPT-6.1 Sol | Leader |
|---|---|---|---|
| Design Arena: websites | Not measured | 1321 | Only GPT-6.1 Sol measured |
| Design Arena: UI components | Not measured | 1321 | Only GPT-6.1 Sol measured |
| Design Arena: game dev | Not measured | 1389 | Only GPT-6.1 Sol measured |
| Design Arena: data viz | Not measured | 1278 | Only GPT-6.1 Sol measured |
| Design Arena: 3D | Not measured | 1461 | Only GPT-6.1 Sol measured |
| Design Arena: all code categories | Not measured | 1345 | Only GPT-6.1 Sol measured |
| LiveBench design | Not measured | 82.1% | Only GPT-6.1 Sol measured |
| Neither model has a result on the other 2 boards here | |||
GeneralLike-for-likePublic boards, shown as published, kept out of the index016
| Benchmark | GPT-4o (2024-08-06) | GPT-6.1 Sol | Leader |
|---|---|---|---|
| Vals Index | Not measured | 63.9% | Only GPT-6.1 Sol measured |
| LiveBench data analysis | Not measured | 82.7% | Only GPT-6.1 Sol measured |
| Public Benefits Bench (Vals AI) | Not measured | 59.3% | Only GPT-6.1 Sol measured |
| SAGE (Vals AI) | Not measured | 46.5% | Only GPT-6.1 Sol measured |
| MedScribe (Vals AI) | Not measured | 86.5% | Only GPT-6.1 Sol measured |
| IFBench | 36.0% | Not measured | Only GPT-4o (2024-08-06) measured |
| Long context reasoning (AA-LCR) | 41.0% | 84.0% | GPT-6.1 Sol |
| DTBench | Not measured | 96.5% | Only GPT-6.1 Sol measured |
| LMCA | Not measured | 62.8% | Only GPT-6.1 Sol measured |
| Furniture assembly | Not measured | 80.0% | Only GPT-6.1 Sol measured |
| LMArena Text | 1283 | 1443 | GPT-6.1 Sol |
| LMArena Text: instruction following | 1267 | 1466 | GPT-6.1 Sol |
| LMArena Text: creative writing | 1274 | 1425 | GPT-6.1 Sol |
| LMArena Vision | 1065 | 1288 | GPT-6.1 Sol |
| LMArena Text: English | 1297 | 1450 | GPT-6.1 Sol |
| LMArena Text: non-English | 1262 | 1433 | GPT-6.1 Sol |
| LMArena Text: Chinese | 1254 | 1487 | GPT-6.1 Sol |
| LMArena Text: German | 1257 | Not measured | Only GPT-4o (2024-08-06) measured |
| LMArena Text: Japanese | 1234 | Not measured | Only GPT-4o (2024-08-06) measured |
| LMArena Text: Korean | 1218 | Not measured | Only GPT-4o (2024-08-06) measured |
| LMArena Text: French | 1263 | 1460 | GPT-6.1 Sol |
| LMArena Text: Spanish | 1269 | 1439 | GPT-6.1 Sol |
| LMArena Text: Russian | 1272 | 1457 | GPT-6.1 Sol |
| LMArena Text: multi-turn | 1279 | 1442 | GPT-6.1 Sol |
| LMArena Text: longer queries | 1283 | 1458 | GPT-6.1 Sol |
| LMArena Text: writing and language | 1290 | 1444 | GPT-6.1 Sol |
| LMArena Text: entertainment and media | 1267 | 1426 | GPT-6.1 Sol |
| LMArena Vision: English | 1072 | 1274 | GPT-6.1 Sol |
| LMArena Vision: Chinese | 1009 | Not measured | Only GPT-4o (2024-08-06) measured |
| LMArena Vision: reading text | Not measured | 1289 | Only GPT-6.1 Sol measured |
| LMArena Vision: creative writing | Not measured | 1301 | Only GPT-6.1 Sol measured |
| Neither model has a result on the other 15 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | GPT-4o (2024-08-06) | GPT-6.1 Sol | 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-4o (2024-08-06)$0.0075Fits in one request
GPT-6.1 Sol$0.0070Fits in one request
GPT-6.1 Sol costs less
Repository review
50K input + 3K output tokens
GPT-4o (2024-08-06)$0.155Fits in one request
GPT-6.1 Sol$0.130Fits in one request
GPT-6.1 Sol costs less
Agent loop
200K input + 10K output tokens
GPT-4o (2024-08-06)$0.600Exceeds the context window
GPT-6.1 Sol$0.500Fits in one request
GPT-6.1 Sol 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-4o (2024-08-06) | OpenAI GPT-6.1 Sol |
|---|---|---|
| Maker | OpenAI | OpenAI |
| Weights | No public weights listed | No public weights listed |
| Released | August 6, 2024 | September 29, 2026 |
| Context window | 128K | 1.05M |
| Input $/Mtok | $2.50 | $2.00 |
| Output $/Mtok | $10.00 | $10.00 |
| Coding index | 23.1 | 88.7 |
| Independent measurements behind it | 1 | 2 |
| Cost per solved task | Not computable | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is GPT-4o (2024-08-06) better than GPT-6.1 Sol for coding?
Pick GPT-6.1 Sol for coding: it scores 88.7 on the Vibe Coding Index against 23.1 for GPT-4o (2024-08-06). GPT-4o (2024-08-06) is neither cheaper nor larger in context, and leads no benchmark both models were measured on.
Which is cheaper, GPT-4o (2024-08-06) or GPT-6.1 Sol?
GPT-4o (2024-08-06) costs $2.50 per million input tokens and $10.00 per million output tokens; GPT-6.1 Sol costs $2.00 and $10.00. Cost per solved task is known for neither of them.
Which has the bigger context window, GPT-4o (2024-08-06) or GPT-6.1 Sol?
GPT-6.1 Sol, with 1.05M tokens against 128K.
How many benchmarks is the GPT-4o (2024-08-06) vs GPT-6.1 Sol comparison based on?
34 benchmarks have a result for both models as of October 21, 2026. GPT-4o (2024-08-06)'s coding index rests on 1 independent benchmark and GPT-6.1 Sol's on 2. Where only one model has a result, the page says so instead of naming a winner.