GPT-5.5 vs Hy3
Updated October 21, 2026. 44 benchmarks have a result for both. Coding is ranked on the Vibe Coding Index; every other board is shown as published.
Decision reading
Pick GPT-5.5 for coding: it scores 67.8 on the Vibe Coding Index against 43.9 for Hy3.
Pick Hy3 when output tokens cost 56.8x less, or when what matters is LMArena WebDev: React or Design Arena: 3D, where it leads.
- Shared results
- 44
- GPT-5.5 only
- 88
- Hy3 only
- 0
- 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-5.5
GPT-5.5 scores 67.8 against 43.9.
2 and 1 benchmarks behind the scores
Intelligence
AA Intelligence Index
No call
Only GPT-5.5 has a AA Intelligence Index result, 38.4.
Directional only
Agentic work
AA Agentic Index
No call
Only GPT-5.5 has a AA Agentic Index result, 36.4.
Directional only
Reasoning
GPQA Diamond
No call
Only GPT-5.5 has a GPQA Diamond result, 93.2%.
Directional only
Knowledge
MMLU Pro
No call
Only GPT-5.5 has a MMLU Pro result, 88.1%.
Directional only
Web design
Design Arena: websites
GPT-5.5
GPT-5.5 leads, 1256 against 1230.
Same board, both measured
Long documents
Listed context window
GPT-5.5
GPT-5.5 takes 1.05M tokens against 262K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Hy3
GPT-5.5 $0.020, Hy3 $0.0004 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
No call
Only GPT-5.5 has the number, $1.65.
Directional only
At a glance
- Coding index
- GPT-5.5 67.8 from 2 benchmarks, Hy3 43.9 from 1 benchmark.
- Widest category
- Coding, 9.3 points apart on average over 7 shared benchmarks.
- Widest single gap
- ALE-Bench: GPT-5.5 1943.0 against Hy3 838.6, 36.8 points apart on a 0 to 100 scale.
- Output price
- GPT-5.5 $30.00 against Hy3 $0.528 per million output tokens, 56.8x apart.
- Context window
- GPT-5.5 takes 1.05M tokens, Hy3 262K.
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-5.5 | Bars | Hy3 | Ties |
|---|---|---|---|---|
| Coding | 6 | 1 | ||
| Reasoning | 5 | 0 | ||
| Math | 2 | 0 | ||
| Knowledge | 4 | 0 | ||
| Web design | 7 | 1 | ||
| General | 18 | 0 | ||
| All shared boards | 42 | 2 |
CodingLike-for-likeFour of these boards feed the Vibe Coding Index61
| Benchmark | GPT-5.5 | Hy3 | Leader |
|---|---|---|---|
| LiveBench coding | 85.1% | Not measured | Only GPT-5.5 measured |
| LMArena WebDev | 1513 | 1507 | GPT-5.5 |
| AA Coding Index | 74.9 | Not measured | Only GPT-5.5 measured |
| LiveCodeBench (Vals AI) | 85.3% | Not measured | Only GPT-5.5 measured |
| SWE-bench Verified (Vals AI) | 82.6% | Not measured | Only GPT-5.5 measured |
| Vibe Code Bench (Vals AI) | 69.8% | Not measured | Only GPT-5.5 measured |
| Code migration (Vals AI) | 45.2% | Not measured | Only GPT-5.5 measured |
| ProgramBench (Vals AI) | 0.5% | Not measured | Only GPT-5.5 measured |
| Terminal-Bench 2.1 (Vals AI) | 76.4% | Not measured | Only GPT-5.5 measured |
| SkillsBench (Vals AI) | 62.5% | Not measured | Only GPT-5.5 measured |
| SciCode | 56.1% | 48.6% | GPT-5.5 |
| Terminal-Bench Hard (Artificial Analysis run) | 60.6% | Not measured | Only GPT-5.5 measured |
| Terminal-Bench | 84.7% | Not measured | Only GPT-5.5 measured |
| FrontierCode | 43.0% | Not measured | Only GPT-5.5 measured |
| GSO-Bench | 40.2% | Not measured | Only GPT-5.5 measured |
| WeirdML | 84.9% | Not measured | Only GPT-5.5 measured |
| MirrorCode | 10.0% | Not measured | Only GPT-5.5 measured |
| ALE-Bench | 1943.0 | 838.6 | GPT-5.5 |
| LMArena Text: coding | 1494 | 1466 | GPT-5.5 |
| LMArena Text: software and IT | 1493 | 1463 | GPT-5.5 |
| LMArena WebDev: React | 1506 | 1511 | Hy3 |
| LMArena WebDev: HTML | 1543 | 1487 | GPT-5.5 |
| LMArena WebDev: from an image | 1532 | Not measured | Only GPT-5.5 measured |
| Neither model has a result on the other 15 boards here | |||
IntelligenceDirectional onlyPublic boards, shown as published, kept out of the index2 boards, none shared
| Benchmark | GPT-5.5 | Hy3 | Leader |
|---|---|---|---|
| AA Intelligence Index | 38.4 | Not measured | Only GPT-5.5 measured |
| Epoch Capabilities Index | 159.7 | Not measured | Only GPT-5.5 measured |
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index25 boards, none shared
| Benchmark | GPT-5.5 | Hy3 | Leader |
|---|---|---|---|
| AA Agentic Index | 36.4 | Not measured | Only GPT-5.5 measured |
| Design Arena: agents building web apps | 1117 | Not measured | Only GPT-5.5 measured |
| Design Arena: agents building full-stack apps | 1089 | Not measured | Only GPT-5.5 measured |
| Design Arena: agents building mobile apps | 1143 | Not measured | Only GPT-5.5 measured |
| Design Arena: agents building Android apps | 1169 | Not measured | Only GPT-5.5 measured |
| Design Arena: agents building Godot games | 1173 | Not measured | Only GPT-5.5 measured |
| Design Arena: agents building games | 1179 | Not measured | Only GPT-5.5 measured |
| Design Arena: HTML slides | 1067 | Not measured | Only GPT-5.5 measured |
| Design Arena: PowerPoint slides | 1108 | Not measured | Only GPT-5.5 measured |
| LiveBench research | 61.6% | Not measured | Only GPT-5.5 measured |
| LiveBench browser | 48.0% | Not measured | Only GPT-5.5 measured |
| LiveBench long agentic | 44.6% | Not measured | Only GPT-5.5 measured |
| SREBench (Vals AI) | 3.8% | Not measured | Only GPT-5.5 measured |
| Finance Agent (Vals AI) | 51.8% | Not measured | Only GPT-5.5 measured |
| Tax Agent Bench (Vals AI) | 21.8% | Not measured | Only GPT-5.5 measured |
| Legal Research Bench (Vals AI) | 40.4% | Not measured | Only GPT-5.5 measured |
| Excel Modeling Benchmark (Vals AI) | 64.5% | Not measured | Only GPT-5.5 measured |
| Time Horizon Index (Vals AI) | 8.3% | Not measured | Only GPT-5.5 measured |
| τ²-Bench Telecom | 93.9% | Not measured | Only GPT-5.5 measured |
| APEX-Agents | 55.1% | Not measured | Only GPT-5.5 measured |
| Remote Labor Index | 6.3% | Not measured | Only GPT-5.5 measured |
| OSWorld 2.0 | 13.0% | Not measured | Only GPT-5.5 measured |
| DeepResearch Bench | 54.0% | Not measured | Only GPT-5.5 measured |
| PostTrainBench | 27.2% | Not measured | Only GPT-5.5 measured |
| Vending-Bench 2 | $7,524 | Not measured | Only GPT-5.5 measured |
| Neither model has a result on the other 14 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index50
| Benchmark | GPT-5.5 | Hy3 | Leader |
|---|---|---|---|
| GPQA Diamond | 93.2% | Not measured | Only GPT-5.5 measured |
| LiveBench reasoning | 89.7% | Not measured | Only GPT-5.5 measured |
| MMMU Pro (Vals AI) | 88.3% | Not measured | Only GPT-5.5 measured |
| GPQA Diamond (Artificial Analysis run) | 93.5% | 89.7% | GPT-5.5 |
| Humanity's Last Exam (Artificial Analysis run) | 45.8% | 33.5% | GPT-5.5 |
| GPQA Diamond (Epoch AI run) | 90.7% | Not measured | Only GPT-5.5 measured |
| ARC-AGI | 95.0% | Not measured | Only GPT-5.5 measured |
| ARC-AGI-2 | 85.0% | Not measured | Only GPT-5.5 measured |
| SimpleBench | 69.0% | Not measured | Only GPT-5.5 measured |
| Chess puzzles | 63.0% | Not measured | Only GPT-5.5 measured |
| Mystery game puzzles | 56.0% | Not measured | Only GPT-5.5 measured |
| EBR-bench | 34.3% | Not measured | Only GPT-5.5 measured |
| LMArena Text: hard prompts | 1489 | 1447 | GPT-5.5 |
| LMArena Text: expert | 1507 | 1461 | GPT-5.5 |
| LMArena Text: hard prompts in English | 1483 | 1455 | GPT-5.5 |
| LMArena Vision: diagrams | 1325 | Not measured | Only GPT-5.5 measured |
| LMArena Vision: homework | 1332 | Not measured | Only GPT-5.5 measured |
| Neither model has a result on the other 4 boards here | |||
MathLike-for-likePublic boards, shown as published, kept out of the index20
| Benchmark | GPT-5.5 | Hy3 | Leader |
|---|---|---|---|
| OTIS Mock AIME | 84.4% | Not measured | Only GPT-5.5 measured |
| FrontierMath, tiers 1 to 3 | 85.3% | Not measured | Only GPT-5.5 measured |
| FrontierMath, tier 4 | 72.5% | Not measured | Only GPT-5.5 measured |
| ProofBench | 50.0% | Not measured | Only GPT-5.5 measured |
| LMArena Text: math | 1487 | 1473 | GPT-5.5 |
| LMArena Text: mathematical work | 1496 | 1482 | GPT-5.5 |
| Neither model has a result on the other 7 boards here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index40
| Benchmark | GPT-5.5 | Hy3 | Leader |
|---|---|---|---|
| MMLU Pro | 88.1% | Not measured | Only GPT-5.5 measured |
| LegalBench (Vals AI) | 86.5% | Not measured | Only GPT-5.5 measured |
| CaseLaw (Vals AI) | 66.2% | Not measured | Only GPT-5.5 measured |
| CorpFin (Vals AI) | 68.4% | Not measured | Only GPT-5.5 measured |
| TaxEval (Vals AI) | 75.0% | Not measured | Only GPT-5.5 measured |
| MortgageTax (Vals AI) | 68.8% | Not measured | Only GPT-5.5 measured |
| MedCode (Vals AI) | 49.1% | Not measured | Only GPT-5.5 measured |
| SimpleQA Verified | 63.0% | Not measured | Only GPT-5.5 measured |
| LMArena Text: science | 1485 | 1457 | GPT-5.5 |
| LMArena Text: medicine and healthcare | 1465 | 1452 | GPT-5.5 |
| LMArena Text: legal and government | 1491 | 1422 | GPT-5.5 |
| LMArena Text: business and finance | 1478 | 1424 | GPT-5.5 |
| Neither model has a result on the other 5 boards here | |||
Web designLike-for-likePublic boards, shown as published, kept out of the index71
| Benchmark | GPT-5.5 | Hy3 | Leader |
|---|---|---|---|
| Design Arena: websites | 1256 | 1230 | GPT-5.5 |
| Design Arena: UI components | 1260 | 1205 | GPT-5.5 |
| Design Arena: game dev | 1294 | 1208 | GPT-5.5 |
| Design Arena: data viz | 1265 | 1163 | GPT-5.5 |
| Design Arena: 3D | 1198 | 1233 | Hy3 |
| Design Arena: all code categories | 1260 | 1227 | GPT-5.5 |
| Design Arena: SVG | 1234 | 1199 | GPT-5.5 |
| Design Arena: ASCII art | 1254 | 1157 | GPT-5.5 |
| LiveBench design | 70.3% | Not measured | Only GPT-5.5 measured |
GeneralLike-for-likePublic boards, shown as published, kept out of the index180
| Benchmark | GPT-5.5 | Hy3 | Leader |
|---|---|---|---|
| LiveBench data analysis | 81.6% | Not measured | Only GPT-5.5 measured |
| Public Benefits Bench (Vals AI) | 60.9% | Not measured | Only GPT-5.5 measured |
| SAGE (Vals AI) | 51.5% | Not measured | Only GPT-5.5 measured |
| MedScribe (Vals AI) | 86.9% | Not measured | Only GPT-5.5 measured |
| Vals Multimodal Index | 68.1% | Not measured | Only GPT-5.5 measured |
| IFBench | 75.9% | Not measured | Only GPT-5.5 measured |
| Long context reasoning (AA-LCR) | 84.3% | 79.0% | GPT-5.5 |
| DTBench | 96.0% | Not measured | Only GPT-5.5 measured |
| LMCA | 54.3% | Not measured | Only GPT-5.5 measured |
| Surface Evolver Bench | 88.1% | Not measured | Only GPT-5.5 measured |
| Furniture assembly | 44.2% | Not measured | Only GPT-5.5 measured |
| ExploitBench | 47.4% | Not measured | Only GPT-5.5 measured |
| CL-bench Life | 22.2% | Not measured | Only GPT-5.5 measured |
| LMArena Text | 1471 | 1438 | GPT-5.5 |
| LMArena Text: instruction following | 1478 | 1426 | GPT-5.5 |
| LMArena Text: creative writing | 1455 | 1403 | GPT-5.5 |
| LMArena Vision | 1297 | Not measured | Only GPT-5.5 measured |
| LMArena Text: English | 1470 | 1448 | GPT-5.5 |
| LMArena Text: non-English | 1467 | 1426 | GPT-5.5 |
| LMArena Text: Chinese | 1534 | 1485 | GPT-5.5 |
| LMArena Text: German | 1480 | 1449 | GPT-5.5 |
| LMArena Text: Japanese | 1499 | 1397 | GPT-5.5 |
| LMArena Text: Korean | 1460 | 1396 | GPT-5.5 |
| LMArena Text: French | 1485 | 1456 | GPT-5.5 |
| LMArena Text: Spanish | 1468 | 1457 | GPT-5.5 |
| LMArena Text: Russian | 1473 | 1432 | GPT-5.5 |
| LMArena Text: Polish | 1465 | 1447 | GPT-5.5 |
| LMArena Text: multi-turn | 1476 | 1436 | GPT-5.5 |
| LMArena Text: longer queries | 1484 | 1442 | GPT-5.5 |
| LMArena Text: writing and language | 1466 | 1414 | GPT-5.5 |
| LMArena Text: entertainment and media | 1449 | 1400 | GPT-5.5 |
| LMArena Vision: English | 1292 | Not measured | Only GPT-5.5 measured |
| LMArena Vision: Chinese | 1360 | Not measured | Only GPT-5.5 measured |
| LMArena Vision: reading text | 1306 | Not measured | Only GPT-5.5 measured |
| LMArena Vision: humor | 1293 | Not measured | Only GPT-5.5 measured |
| LMArena Vision: recognizing things | 1231 | Not measured | Only GPT-5.5 measured |
| LMArena Vision: creative writing | 1301 | Not measured | Only GPT-5.5 measured |
| LMArena Document | 1486 | Not measured | Only GPT-5.5 measured |
| Neither model has a result on the other 8 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | GPT-5.5 | Hy3 | 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
Hy3 costs less
Repository review
50K input + 3K output tokens
Hy3 costs less
Agent loop
200K input + 10K output tokens
Hy3 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-5.5 | Tencent Hy3 |
|---|---|---|
| Maker | OpenAI | Tencent |
| Weights | No public weights listed | Open weights |
| Released | April 24, 2026 | July 6, 2026 |
| Context window | 1.05M | 262K |
| Input $/Mtok | $5.00 | $0.132 |
| Output $/Mtok | $30.00 | $0.528 |
| Coding index | 67.8 | 43.9 |
| Independent measurements behind it | 2 | 1 |
| Cost per solved task | $1.65 | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is GPT-5.5 better than Hy3 for coding?
Pick GPT-5.5 for coding: it scores 67.8 on the Vibe Coding Index against 43.9 for Hy3. Pick Hy3 when output tokens cost 56.8x less, or when what matters is LMArena WebDev: React or Design Arena: 3D, where it leads.
Which is cheaper, GPT-5.5 or Hy3?
GPT-5.5 costs $5.00 per million input tokens and $30.00 per million output tokens; Hy3 costs $0.132 and $0.528. Cost per solved task is known for GPT-5.5 only.
Which has the bigger context window, GPT-5.5 or Hy3?
GPT-5.5, with 1.05M tokens against 262K.
How many benchmarks is the GPT-5.5 vs Hy3 comparison based on?
44 benchmarks have a result for both models as of October 21, 2026. GPT-5.5's coding index rests on 2 independent benchmarks and Hy3's on 1. Where only one model has a result, the page says so instead of naming a winner.