GPT-5.2-Codex vs GPT-5.6 Sol
GPT-5.6 Sol leads GPT-5.2-Codex on coding, 73.5 to 45.4 on the Vibe Coding Index, and GPT-5.2-Codex costs 1.4x less per output token ($14.00 vs $20.00 per million). Updated October 22, 2026; 19 benchmarks have a result for both.
vs boards won of 19 shared
GPT-5.2-Codex or GPT-5.6 Sol: which to pick
Pick GPT-5.6 Sol for coding: it scores 73.5 on the Vibe Coding Index against 45.4 for GPT-5.2-Codex.
Pick GPT-5.2-Codex for output tokens 1.4x cheaper ($14.00 vs $20.00 per million) and a lower cost per solved task ($0.43 against $1.20).
Model AGPT-5.2-CodexOpenAI45.4/1003 independent benchmarks$0.43 per solved taskModel BGPT-5.6 SolOpenAI73.5/1006 independent benchmarks$1.20 per solved task
- Shared results
- 19
- GPT-5.2-Codex only
- 3
- GPT-5.6 Sol only
- 120
- Like-for-like categories
- 5 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
GPT-5.6 Sol
GPT-5.6 Sol scores 73.5 against 45.4.
3 and 6 benchmarks behind the scores
Intelligence
AA Intelligence Index
GPT-5.6 Sol
GPT-5.6 Sol leads, 47.0 against 28.5.
Same board, both measured
Agentic work
AA Agentic Index
No call
Only GPT-5.6 Sol has a AA Agentic Index result, 50.2.
Directional only
Reasoning
GPQA Diamond
No call
Only GPT-5.6 Sol has a GPQA Diamond result, 95.2%.
Directional only
Knowledge
MMLU Pro
No call
Only GPT-5.6 Sol has a MMLU Pro result, 89.1%.
Directional only
Web design
Design Arena: websites
No call
Only GPT-5.6 Sol has a Design Arena: websites result, 1321.
Directional only
Long documents
Listed context window
GPT-5.6 Sol
GPT-5.6 Sol takes 1.05M tokens against 400K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
GPT-5.2-Codex
GPT-5.2-Codex $0.0088, GPT-5.6 Sol $0.014 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
GPT-5.2-Codex
GPT-5.2-Codex $0.43, GPT-5.6 Sol $1.20.
Published attempt cost and pass rate
At a glance
- Coding index
- GPT-5.2-Codex 45.4 from 3 benchmarks, GPT-5.6 Sol 73.5 from 6 benchmarks.
- Widest category
- Coding, 32.0 points apart on average over 8 shared benchmarks.
- Widest single gap
- LMArena WebDev: React: GPT-5.2-Codex 1329 against GPT-5.6 Sol 1620, 45.1 points apart on a 0 to 100 scale.
- Output price
- GPT-5.2-Codex $14.00 against GPT-5.6 Sol $20.00 per million output tokens, 1.4x apart.
- Context window
- GPT-5.2-Codex takes 400K tokens, GPT-5.6 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-5.2-Codex | Bars | GPT-5.6 Sol | Ties |
|---|---|---|---|---|
| Coding | 1 | 7 | ||
| Intelligence | 0 | 1 | ||
| Agentic work | 1 | 5 | ||
| Reasoning | 0 | 2 | ||
| General | 1 | 1 | ||
| All shared boards | 3 | 16 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index17
| Benchmark | GPT-5.2-Codex | GPT-5.6 Sol | Leader |
|---|---|---|---|
| SWE-bench Verified | 72.8% | Not measured | Only GPT-5.2-Codex measured |
| SWE-bench Multilingual | 66.3% | Not measured | Only GPT-5.2-Codex measured |
| LiveBench coding | Not measured | 89.7% | Only GPT-5.6 Sol measured |
| LMArena WebDev | 1339 | 1616 | GPT-5.6 Sol |
| AA Coding Index | Not measured | 77.4 | Only GPT-5.6 Sol measured |
| LiveCodeBench (Vals AI) | 88.0% | 82.6% | GPT-5.2-Codex |
| SWE-bench Verified (Vals AI) | 72.4% | 96.2% | GPT-5.6 Sol |
| Terminal-Bench 4 (Vals AI) | Not measured | 37.9% | Only GPT-5.6 Sol measured |
| Vibe Code Bench (Vals AI) | 37.9% | 80.5% | GPT-5.6 Sol |
| Code migration (Vals AI) | Not measured | 52.9% | Only GPT-5.6 Sol measured |
| ProgramBench (Vals AI) | Not measured | 1.5% | Only GPT-5.6 Sol measured |
| IOI (Vals AI) | Not measured | 91.2% | Only GPT-5.6 Sol measured |
| Terminal-Bench 2.1 (Vals AI) | Not measured | 85.8% | Only GPT-5.6 Sol measured |
| Vibe Code Bench 1-100 (Vals AI) | Not measured | 20.0% | Only GPT-5.6 Sol measured |
| SkillsBench (Vals AI) | Not measured | 54.1% | Only GPT-5.6 Sol measured |
| CyberBench (Vals AI) | Not measured | 76.3% | Only GPT-5.6 Sol measured |
| SciCode | Not measured | 57.8% | Only GPT-5.6 Sol measured |
| Terminal-Bench Hard (Artificial Analysis run) | 37.1% | 65.9% | GPT-5.6 Sol |
| Terminal-Bench | 66.5% | Not measured | Only GPT-5.2-Codex measured |
| FrontierCode | Not measured | 47.5% | Only GPT-5.6 Sol measured |
| FrontierSWE | Not measured | 32.2% | Only GPT-5.6 Sol measured |
| GSO-Bench | Not measured | 76.5% | Only GPT-5.6 Sol measured |
| WeirdML | Not measured | 88.8% | Only GPT-5.6 Sol measured |
| MirrorCode | Not measured | 20.0% | Only GPT-5.6 Sol measured |
| ALE-Bench | 1299.9 | 2176.9 | GPT-5.6 Sol |
| LMArena Text: coding | Not measured | 1496 | Only GPT-5.6 Sol measured |
| LMArena Text: software and IT | Not measured | 1489 | Only GPT-5.6 Sol measured |
| LMArena WebDev: React | 1329 | 1620 | GPT-5.6 Sol |
| LMArena WebDev: HTML | 1348 | 1618 | GPT-5.6 Sol |
| LMArena WebDev: from an image | Not measured | 1609 | Only GPT-5.6 Sol measured |
| SciCode | Not measured | 10.8% | Only GPT-5.6 Sol measured |
| Neither model has a result on the other 8 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | GPT-5.2-Codex | GPT-5.6 Sol | Leader |
|---|---|---|---|
| AA Intelligence Index | 28.5 | 47.0 | GPT-5.6 Sol |
| Epoch Capabilities Index | Not measured | 162.8 | Only GPT-5.6 Sol measured |
Agentic workLike-for-likePublic boards, shown as published, kept out of the index15
| Benchmark | GPT-5.2-Codex | GPT-5.6 Sol | Leader |
|---|---|---|---|
| AA Agentic Index | Not measured | 50.2 | Only GPT-5.6 Sol measured |
| Design Arena: agents building web apps | 1051 | 1245 | GPT-5.6 Sol |
| Design Arena: agents building full-stack apps | 993 | 1261 | GPT-5.6 Sol |
| Design Arena: agents building mobile apps | 1089 | 1248 | GPT-5.6 Sol |
| Design Arena: agents building Android apps | 1176 | 1240 | GPT-5.6 Sol |
| Design Arena: agents building Godot games | 1142 | 1260 | GPT-5.6 Sol |
| Design Arena: agents building games | Not measured | 1266 | Only GPT-5.6 Sol measured |
| Design Arena: HTML slides | Not measured | 1236 | Only GPT-5.6 Sol measured |
| Design Arena: PowerPoint slides | Not measured | 1217 | Only GPT-5.6 Sol measured |
| LiveBench research | Not measured | 54.5% | Only GPT-5.6 Sol measured |
| LiveBench browser | Not measured | 88.0% | Only GPT-5.6 Sol measured |
| LiveBench long agentic | Not measured | 48.5% | Only GPT-5.6 Sol measured |
| SREBench (Vals AI) | Not measured | 30.5% | Only GPT-5.6 Sol measured |
| Finance Agent (Vals AI) | Not measured | 53.8% | Only GPT-5.6 Sol measured |
| Tax Agent Bench (Vals AI) | Not measured | 31.1% | Only GPT-5.6 Sol measured |
| Legal Research Bench (Vals AI) | Not measured | 48.1% | Only GPT-5.6 Sol measured |
| Excel Modeling Benchmark (Vals AI) | Not measured | 72.3% | Only GPT-5.6 Sol measured |
| BioMysteryBench (Vals AI) | Not measured | 71.1% | Only GPT-5.6 Sol measured |
| Terminal-Bench-Science (Vals AI) | Not measured | 20.0% | Only GPT-5.6 Sol measured |
| Vals Science Index | Not measured | 41.5% | Only GPT-5.6 Sol measured |
| Time Horizon Index (Vals AI) | Not measured | 23.8% | Only GPT-5.6 Sol measured |
| CUA-bench (Vals AI) | Not measured | 8.3% | Only GPT-5.6 Sol measured |
| τ²-Bench Telecom | 92.1% | 85.1% | GPT-5.2-Codex |
| OSWorld 2.0 | Not measured | 27.3% | Only GPT-5.6 Sol measured |
| BALROG | Not measured | 60.0% | Only GPT-5.6 Sol measured |
| PostTrainBench | Not measured | 36.2% | Only GPT-5.6 Sol measured |
| Vending-Bench 2 | Not measured | $9,619 | Only GPT-5.6 Sol measured |
| LMArena Search | Not measured | 1261 | Only GPT-5.6 Sol measured |
| Neither model has a result on the other 13 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index02
| Benchmark | GPT-5.2-Codex | GPT-5.6 Sol | Leader |
|---|---|---|---|
| GPQA Diamond | Not measured | 95.2% | Only GPT-5.6 Sol measured |
| LiveBench reasoning | Not measured | 91.7% | Only GPT-5.6 Sol measured |
| MysteryMechanism (Vals AI) | Not measured | 33.3% | Only GPT-5.6 Sol measured |
| MMMU Pro (Vals AI) | Not measured | 88.8% | Only GPT-5.6 Sol measured |
| GPQA Diamond (Artificial Analysis run) | 89.9% | 94.1% | GPT-5.6 Sol |
| Humanity's Last Exam (Artificial Analysis run) | 35.7% | 49.5% | GPT-5.6 Sol |
| GPQA Diamond (Epoch AI run) | Not measured | 93.5% | Only GPT-5.6 Sol measured |
| ARC-AGI | Not measured | 97.5% | Only GPT-5.6 Sol measured |
| ARC-AGI-2 | Not measured | 92.5% | Only GPT-5.6 Sol measured |
| SimpleBench | Not measured | 64.8% | Only GPT-5.6 Sol measured |
| Chess puzzles | Not measured | 59.0% | Only GPT-5.6 Sol measured |
| Mystery game puzzles | Not measured | 58.0% | Only GPT-5.6 Sol measured |
| EBR-bench | Not measured | 44.8% | Only GPT-5.6 Sol measured |
| LMArena Text: hard prompts | Not measured | 1483 | Only GPT-5.6 Sol measured |
| LMArena Text: expert | Not measured | 1517 | Only GPT-5.6 Sol measured |
| LMArena Text: hard prompts in English | Not measured | 1477 | Only GPT-5.6 Sol measured |
| LMArena Vision: diagrams | Not measured | 1305 | Only GPT-5.6 Sol measured |
| LMArena Vision: homework | Not measured | 1305 | Only GPT-5.6 Sol measured |
| Kagi LLM Benchmark | Not measured | 67.0% | Only GPT-5.6 Sol measured |
| Neither model has a result on the other 3 boards here | |||
MathDirectional onlyPublic boards, shown as published, kept out of the index6 boards, none shared
| Benchmark | GPT-5.2-Codex | GPT-5.6 Sol | Leader |
|---|---|---|---|
| OTIS Mock AIME | Not measured | 100.0% | Only GPT-5.6 Sol measured |
| FrontierMath, tiers 1 to 3 | Not measured | 89.1% | Only GPT-5.6 Sol measured |
| FrontierMath, tier 4 | Not measured | 82.9% | Only GPT-5.6 Sol measured |
| ProofBench | Not measured | 83.0% | Only GPT-5.6 Sol measured |
| LMArena Text: math | Not measured | 1473 | Only GPT-5.6 Sol measured |
| LMArena Text: mathematical work | Not measured | 1496 | Only GPT-5.6 Sol measured |
| Neither model has a result on the other 7 boards here | |||
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index12 boards, none shared
| Benchmark | GPT-5.2-Codex | GPT-5.6 Sol | Leader |
|---|---|---|---|
| MMLU Pro | Not measured | 89.1% | Only GPT-5.6 Sol measured |
| LegalBench (Vals AI) | Not measured | 87.0% | Only GPT-5.6 Sol measured |
| CorpFin (Vals AI) | Not measured | 64.4% | Only GPT-5.6 Sol measured |
| TaxEval (Vals AI) | Not measured | 74.8% | Only GPT-5.6 Sol measured |
| MortgageTax (Vals AI) | Not measured | 67.3% | Only GPT-5.6 Sol measured |
| MedCode (Vals AI) | Not measured | 44.0% | Only GPT-5.6 Sol measured |
| SimpleQA Verified | Not measured | 69.7% | Only GPT-5.6 Sol measured |
| LMArena Text: science | Not measured | 1455 | Only GPT-5.6 Sol measured |
| LMArena Text: medicine and healthcare | Not measured | 1431 | Only GPT-5.6 Sol measured |
| LMArena Text: legal and government | Not measured | 1476 | Only GPT-5.6 Sol measured |
| LMArena Text: business and finance | Not measured | 1457 | Only GPT-5.6 Sol measured |
| FACTS Benchmark Suite | Not measured | 52.4% | Only GPT-5.6 Sol measured |
| Neither model has a result on the other 6 boards here | |||
Web designDirectional onlyPublic boards, shown as published, kept out of the index9 boards, none shared
| Benchmark | GPT-5.2-Codex | GPT-5.6 Sol | Leader |
|---|---|---|---|
| Design Arena: websites | Not measured | 1321 | Only GPT-5.6 Sol measured |
| Design Arena: UI components | Not measured | 1335 | Only GPT-5.6 Sol measured |
| Design Arena: game dev | Not measured | 1367 | Only GPT-5.6 Sol measured |
| Design Arena: data viz | Not measured | 1323 | Only GPT-5.6 Sol measured |
| Design Arena: 3D | Not measured | 1384 | Only GPT-5.6 Sol measured |
| Design Arena: all code categories | Not measured | 1341 | Only GPT-5.6 Sol measured |
| Design Arena: SVG | Not measured | 1315 | Only GPT-5.6 Sol measured |
| Design Arena: ASCII art | Not measured | 1304 | Only GPT-5.6 Sol measured |
| LiveBench design | Not measured | 81.6% | Only GPT-5.6 Sol measured |
GeneralLike-for-likePublic boards, shown as published, kept out of the index11
| Benchmark | GPT-5.2-Codex | GPT-5.6 Sol | Leader |
|---|---|---|---|
| LiveBench data analysis | Not measured | 79.8% | Only GPT-5.6 Sol measured |
| Public Benefits Bench (Vals AI) | Not measured | 66.5% | Only GPT-5.6 Sol measured |
| SAGE (Vals AI) | Not measured | 52.6% | Only GPT-5.6 Sol measured |
| MedScribe (Vals AI) | Not measured | 85.2% | Only GPT-5.6 Sol measured |
| Vals Multimodal Index | Not measured | 72.6% | Only GPT-5.6 Sol measured |
| IFBench | 77.6% | 72.7% | GPT-5.2-Codex |
| Long context reasoning (AA-LCR) | 82.3% | 84.0% | GPT-5.6 Sol |
| DTBench | Not measured | 95.7% | Only GPT-5.6 Sol measured |
| LMCA | Not measured | 58.5% | Only GPT-5.6 Sol measured |
| Surface Evolver Bench | Not measured | 93.1% | Only GPT-5.6 Sol measured |
| Furniture assembly | Not measured | 56.7% | Only GPT-5.6 Sol measured |
| LMArena Text | Not measured | 1457 | Only GPT-5.6 Sol measured |
| LMArena Text: instruction following | Not measured | 1483 | Only GPT-5.6 Sol measured |
| LMArena Text: creative writing | Not measured | 1449 | Only GPT-5.6 Sol measured |
| LMArena Vision | Not measured | 1281 | Only GPT-5.6 Sol measured |
| LMArena Text: English | Not measured | 1457 | Only GPT-5.6 Sol measured |
| LMArena Text: non-English | Not measured | 1451 | Only GPT-5.6 Sol measured |
| LMArena Text: Chinese | Not measured | 1525 | Only GPT-5.6 Sol measured |
| LMArena Text: German | Not measured | 1476 | Only GPT-5.6 Sol measured |
| LMArena Text: Japanese | Not measured | 1472 | Only GPT-5.6 Sol measured |
| LMArena Text: Korean | Not measured | 1442 | Only GPT-5.6 Sol measured |
| LMArena Text: French | Not measured | 1472 | Only GPT-5.6 Sol measured |
| LMArena Text: Spanish | Not measured | 1443 | Only GPT-5.6 Sol measured |
| LMArena Text: Russian | Not measured | 1471 | Only GPT-5.6 Sol measured |
| LMArena Text: Polish | Not measured | 1459 | Only GPT-5.6 Sol measured |
| LMArena Text: multi-turn | Not measured | 1461 | Only GPT-5.6 Sol measured |
| LMArena Text: longer queries | Not measured | 1481 | Only GPT-5.6 Sol measured |
| LMArena Text: writing and language | Not measured | 1462 | Only GPT-5.6 Sol measured |
| LMArena Text: entertainment and media | Not measured | 1450 | Only GPT-5.6 Sol measured |
| LMArena Vision: English | Not measured | 1280 | Only GPT-5.6 Sol measured |
| LMArena Vision: Chinese | Not measured | 1313 | Only GPT-5.6 Sol measured |
| LMArena Vision: reading text | Not measured | 1290 | Only GPT-5.6 Sol measured |
| LMArena Vision: humor | Not measured | 1246 | Only GPT-5.6 Sol measured |
| LMArena Vision: creative writing | Not measured | 1283 | Only GPT-5.6 Sol measured |
| LMArena Document | Not measured | 1483 | Only GPT-5.6 Sol measured |
| Neither model has a result on the other 11 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | GPT-5.2-Codex | GPT-5.6 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-5.2-Codex$0.0088Fits in one request
GPT-5.6 Sol$0.014Fits in one request
GPT-5.2-Codex costs less
Repository review
50K input + 3K output tokens
GPT-5.2-Codex$0.130Fits in one request
GPT-5.6 Sol$0.260Fits in one request
GPT-5.2-Codex costs less
Agent loop
200K input + 10K output tokens
GPT-5.2-Codex$0.490Fits in one request
GPT-5.6 Sol$1.00Fits in one request
GPT-5.2-Codex 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-5.2-Codex | OpenAI GPT-5.6 Sol |
|---|---|---|
| Maker | OpenAI | OpenAI |
| Weights | No public weights listed | No public weights listed |
| Released | January 14, 2026 | July 9, 2026 |
| Context window | 400K | 1.05M |
| Input $/Mtok | $1.75 | $4.00 |
| Output $/Mtok | $14.00 | $20.00 |
| Coding index | 45.4 | 73.5 |
| Independent measurements behind it | 3 | 6 |
| Cost per solved task | $0.43 | $1.20 |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is GPT-5.2-Codex better than GPT-5.6 Sol for coding?
Pick GPT-5.6 Sol for coding: it scores 73.5 on the Vibe Coding Index against 45.4 for GPT-5.2-Codex. Pick GPT-5.2-Codex for output tokens 1.4x cheaper ($14.00 vs $20.00 per million) and a lower cost per solved task ($0.43 against $1.20).
Which is cheaper, GPT-5.2-Codex or GPT-5.6 Sol?
GPT-5.2-Codex costs $1.75 per million input tokens and $14.00 per million output tokens; GPT-5.6 Sol costs $4.00 and $20.00. Per solved SWE-bench Verified task, GPT-5.2-Codex costs $0.43 and GPT-5.6 Sol $1.20.
Which has the bigger context window, GPT-5.2-Codex or GPT-5.6 Sol?
GPT-5.6 Sol, with 1.05M tokens against 400K.
How many benchmarks is the GPT-5.2-Codex vs GPT-5.6 Sol comparison based on?
19 benchmarks have a result for both models as of October 22, 2026. GPT-5.2-Codex's coding index rests on 3 independent benchmarks and GPT-5.6 Sol's on 6. Where only one model has a result, the page says so instead of naming a winner.