GPT-5 vs Hy3
Hy3 costs 18.9x less per output token than GPT-5 ($0.528 vs $10.00 per million). Updated October 22, 2026; 42 benchmarks have a result for both.
GPT-5 or Hy3: which to pick
Only GPT-5 has a coding score, 38.8 on the Vibe Coding Index; Hy3 has none, so the two cannot be ranked on coding.
Pick Hy3 for output tokens 18.9x cheaper ($0.528 vs $10.00 per million) and work measured by LMArena WebDev or ALE-Bench, where it leads.
- Shared results
- 42
- GPT-5 only
- 71
- Hy3 only
- 2
- 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 GPT-5 has a coding score, so no call is made.
One side not measured
Intelligence
AA Intelligence Index
No call
Only GPT-5 has a AA Intelligence Index result, 23.0.
Directional only
Reasoning
GPQA Diamond
No call
Only GPT-5 has a GPQA Diamond result, 85.6%.
Directional only
Math
AIME
No call
Only GPT-5 has a AIME result, 93.4%.
Directional only
Knowledge
MMLU Pro
No call
Only GPT-5 has a MMLU Pro result, 86.5%.
Directional only
Web design
Design Arena: websites
Hy3
Hy3 leads, 1230 against 1184.
Same board, both measured
Long documents
Listed context window
GPT-5
GPT-5 takes 400K tokens against 262K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Hy3
GPT-5 $0.0063, Hy3 $0.0004 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
No call
Only GPT-5 has the number, $0.39.
Directional only
At a glance
- Coding index
- GPT-5 38.8 from 3 benchmarks, Hy3 not benchmarked.
- Widest category
- Math, 12.0 points apart on average over 2 shared benchmarks.
- Widest single gap
- Design Arena: 3D: GPT-5 1055 against Hy3 1232, 22.1 points apart on a 0 to 100 scale.
- Output price
- GPT-5 $10.00 against Hy3 $0.528 per million output tokens, 18.9x apart.
- Context window
- GPT-5 takes 400K 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 | Bars | Hy3 | Ties |
|---|---|---|---|---|
| Coding | 0 | 5 | ||
| Reasoning | 0 | 5 | ||
| Math | 0 | 2 | ||
| Knowledge | 1 | 3 | ||
| Web design | 1 | 7 | ||
| General | 1 | 17 | ||
| All shared boards | 3 | 39 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index05
| Benchmark | GPT-5 | Hy3 | Leader |
|---|---|---|---|
| Aider polyglot | 88.0% | Not measured | Only GPT-5 measured |
| SWE-bench Verified | 74.4% | Not measured | Only GPT-5 measured |
| LMArena WebDev | 1418 | 1507 | Hy3 |
| AA Coding Index | 37.8 | Not measured | Only GPT-5 measured |
| LiveCodeBench (Vals AI) | 85.9% | Not measured | Only GPT-5 measured |
| SWE-bench Verified (Vals AI) | 69.0% | Not measured | Only GPT-5 measured |
| Vibe Code Bench (Vals AI) | 20.1% | Not measured | Only GPT-5 measured |
| LiveCodeBench (Artificial Analysis run) | 84.6% | Not measured | Only GPT-5 measured |
| SciCode | Not measured | 48.6% | Only Hy3 measured |
| Terminal-Bench Hard (Artificial Analysis run) | 37.9% | Not measured | Only GPT-5 measured |
| Terminal-Bench | 49.6% | Not measured | Only GPT-5 measured |
| GSO-Bench | 6.9% | Not measured | Only GPT-5 measured |
| WeirdML | 60.7% | Not measured | Only GPT-5 measured |
| ALE-Bench | 807.6 | 838.6 | Hy3 |
| LMArena Text: coding | 1436 | 1466 | Hy3 |
| LMArena Text: software and IT | 1420 | 1463 | Hy3 |
| LMArena WebDev: React | Not measured | 1511 | Only Hy3 measured |
| LMArena WebDev: HTML | 1427 | 1487 | Hy3 |
| SciCode | 0.0% | Not measured | Only GPT-5 measured |
| Neither model has a result on the other 20 boards here | |||
IntelligenceDirectional onlyPublic boards, shown as published, kept out of the index2 boards, none shared
| Benchmark | GPT-5 | Hy3 | Leader |
|---|---|---|---|
| AA Intelligence Index | 23.0 | Not measured | Only GPT-5 measured |
| Epoch Capabilities Index | 150.0 | Not measured | Only GPT-5 measured |
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index7 boards, none shared
| Benchmark | GPT-5 | Hy3 | Leader |
|---|---|---|---|
| τ²-Bench Telecom | 86.5% | Not measured | Only GPT-5 measured |
| METR time horizons | 69.6% | Not measured | Only GPT-5 measured |
| Remote Labor Index | 1.7% | Not measured | Only GPT-5 measured |
| GDPval | 34.8% | Not measured | Only GPT-5 measured |
| BALROG | 32.8% | Not measured | Only GPT-5 measured |
| DeepResearch Bench | 49.6% | Not measured | Only GPT-5 measured |
| BrowseComp-Plus | 80.0% | Not measured | Only GPT-5 measured |
| Neither model has a result on the other 34 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index05
| Benchmark | GPT-5 | Hy3 | Leader |
|---|---|---|---|
| GPQA Diamond | 85.6% | Not measured | Only GPT-5 measured |
| MMMU Pro (Vals AI) | 81.5% | Not measured | Only GPT-5 measured |
| GPQA Diamond (Artificial Analysis run) | 85.4% | 89.7% | Hy3 |
| Humanity's Last Exam (Artificial Analysis run) | 28.5% | 33.5% | Hy3 |
| GPQA Diamond (Epoch AI run) | 86.2% | Not measured | Only GPT-5 measured |
| ARC-AGI | 65.7% | Not measured | Only GPT-5 measured |
| ARC-AGI-2 | 9.9% | Not measured | Only GPT-5 measured |
| SimpleBench | 56.7% | Not measured | Only GPT-5 measured |
| Chess puzzles | 36.0% | Not measured | Only GPT-5 measured |
| Mystery game puzzles | 23.0% | Not measured | Only GPT-5 measured |
| EBR-bench | 12.7% | Not measured | Only GPT-5 measured |
| VPCT | 66.0% | Not measured | Only GPT-5 measured |
| LMArena Text: hard prompts | 1415 | 1447 | Hy3 |
| LMArena Text: expert | 1419 | 1461 | Hy3 |
| LMArena Text: hard prompts in English | 1419 | 1455 | Hy3 |
| LMArena Vision: diagrams | 1252 | Not measured | Only GPT-5 measured |
| LMArena Vision: homework | 1278 | Not measured | Only GPT-5 measured |
| Kagi LLM Benchmark | 72.7% | Not measured | Only GPT-5 measured |
| Neither model has a result on the other 4 boards here | |||
MathLike-for-likePublic boards, shown as published, kept out of the index02
| Benchmark | GPT-5 | Hy3 | Leader |
|---|---|---|---|
| AIME | 93.4% | Not measured | Only GPT-5 measured |
| MATH 500 (Vals AI) | 96.0% | Not measured | Only GPT-5 measured |
| MGSM (Vals AI) | 92.8% | Not measured | Only GPT-5 measured |
| AA Math Index | 94.3 | Not measured | Only GPT-5 measured |
| AIME 2025 (Artificial Analysis run) | 94.3% | Not measured | Only GPT-5 measured |
| OTIS Mock AIME | 91.4% | Not measured | Only GPT-5 measured |
| FrontierMath, tiers 1 to 3 | 55.4% | Not measured | Only GPT-5 measured |
| FrontierMath, tier 4 | 22.0% | Not measured | Only GPT-5 measured |
| ProofBench | 18.0% | Not measured | Only GPT-5 measured |
| MATH level 5 | 98.1% | Not measured | Only GPT-5 measured |
| LMArena Text: math | 1407 | 1473 | Hy3 |
| LMArena Text: mathematical work | 1405 | 1482 | Hy3 |
| Neither model has a result on the other 1 board here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index13
| Benchmark | GPT-5 | Hy3 | Leader |
|---|---|---|---|
| MMLU Pro | 86.5% | Not measured | Only GPT-5 measured |
| LegalBench (Vals AI) | 86.0% | Not measured | Only GPT-5 measured |
| CaseLaw (Vals AI) | 66.5% | Not measured | Only GPT-5 measured |
| CorpFin (Vals AI) | 61.1% | Not measured | Only GPT-5 measured |
| TaxEval (Vals AI) | 73.4% | Not measured | Only GPT-5 measured |
| MortgageTax (Vals AI) | 65.5% | Not measured | Only GPT-5 measured |
| MedQA (Vals AI) | 96.3% | Not measured | Only GPT-5 measured |
| MedCode (Vals AI) | 49.6% | Not measured | Only GPT-5 measured |
| MMLU Pro (Artificial Analysis run) | 87.1% | Not measured | Only GPT-5 measured |
| SimpleQA Verified | 50.1% | Not measured | Only GPT-5 measured |
| GeoBench | 81.0% | Not measured | Only GPT-5 measured |
| LMArena Text: science | 1416 | 1457 | Hy3 |
| LMArena Text: medicine and healthcare | 1413 | 1452 | Hy3 |
| LMArena Text: legal and government | 1431 | 1422 | GPT-5 |
| LMArena Text: business and finance | 1400 | 1424 | Hy3 |
| FACTS Benchmark Suite | 56.5% | Not measured | Only GPT-5 measured |
| Neither model has a result on the other 2 boards here | |||
Web designLike-for-likePublic boards, shown as published, kept out of the index17
| Benchmark | GPT-5 | Hy3 | Leader |
|---|---|---|---|
| Design Arena: websites | 1184 | 1230 | Hy3 |
| Design Arena: UI components | 1177 | 1204 | Hy3 |
| Design Arena: game dev | 1185 | 1208 | Hy3 |
| Design Arena: data viz | 1221 | 1164 | GPT-5 |
| Design Arena: 3D | 1055 | 1232 | Hy3 |
| Design Arena: all code categories | 1167 | 1227 | Hy3 |
| Design Arena: SVG | 1188 | 1200 | Hy3 |
| Design Arena: ASCII art | 1141 | 1152 | Hy3 |
| Neither model has a result on the other 1 board here | |||
GeneralLike-for-likePublic boards, shown as published, kept out of the index117
| Benchmark | GPT-5 | Hy3 | Leader |
|---|---|---|---|
| SAGE (Vals AI) | 43.7% | Not measured | Only GPT-5 measured |
| MedScribe (Vals AI) | 83.7% | Not measured | Only GPT-5 measured |
| IFBench | 73.1% | Not measured | Only GPT-5 measured |
| Long context reasoning (AA-LCR) | 78.2% | 79.0% | Hy3 |
| DTBench | 90.7% | Not measured | Only GPT-5 measured |
| LMCA | 40.0% | Not measured | Only GPT-5 measured |
| Fiction.LiveBench | 97.2% | Not measured | Only GPT-5 measured |
| Creative writing (Lech Mazur) | 86.0% | Not measured | Only GPT-5 measured |
| LMArena Text | 1406 | 1438 | Hy3 |
| LMArena Text: instruction following | 1388 | 1426 | Hy3 |
| LMArena Text: creative writing | 1365 | 1403 | Hy3 |
| LMArena Vision | 1232 | Not measured | Only GPT-5 measured |
| LMArena Text: English | 1409 | 1448 | Hy3 |
| LMArena Text: non-English | 1397 | 1426 | Hy3 |
| LMArena Text: Chinese | 1422 | 1485 | Hy3 |
| LMArena Text: German | 1416 | 1449 | Hy3 |
| LMArena Text: Japanese | 1409 | 1397 | GPT-5 |
| LMArena Text: Korean | 1360 | 1396 | Hy3 |
| LMArena Text: French | 1409 | 1456 | Hy3 |
| LMArena Text: Spanish | 1399 | 1457 | Hy3 |
| LMArena Text: Russian | 1407 | 1432 | Hy3 |
| LMArena Text: Polish | 1431 | 1447 | Hy3 |
| LMArena Text: multi-turn | 1426 | 1436 | Hy3 |
| LMArena Text: longer queries | 1399 | 1442 | Hy3 |
| LMArena Text: writing and language | 1384 | 1414 | Hy3 |
| LMArena Text: entertainment and media | 1379 | 1400 | Hy3 |
| LMArena Vision: English | 1231 | Not measured | Only GPT-5 measured |
| LMArena Vision: Chinese | 1267 | Not measured | Only GPT-5 measured |
| LMArena Vision: reading text | 1246 | Not measured | Only GPT-5 measured |
| LMArena Vision: humor | 1219 | Not measured | Only GPT-5 measured |
| LMArena Vision: captioning | 1212 | Not measured | Only GPT-5 measured |
| LMArena Vision: recognizing things | 1263 | Not measured | Only GPT-5 measured |
| LMArena Vision: creative writing | 1210 | Not measured | Only GPT-5 measured |
| Neither model has a result on the other 13 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | GPT-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 | Tencent Hy3 |
|---|---|---|
| Maker | OpenAI | Tencent |
| Weights | No public weights listed | Open weights |
| Released | August 7, 2025 | July 6, 2026 |
| Context window | 400K | 262K |
| Input $/Mtok | $1.25 | $0.132 |
| Output $/Mtok | $10.00 | $0.528 |
| Coding index | 38.8 | Not benchmarked |
| Independent measurements behind it | 3 | 1 |
| Cost per solved task | $0.39 | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is GPT-5 better than Hy3 for coding?
Only GPT-5 has a coding score, 38.8 on the Vibe Coding Index; Hy3 has none, so the two cannot be ranked on coding. Pick Hy3 for output tokens 18.9x cheaper ($0.528 vs $10.00 per million) and work measured by LMArena WebDev or ALE-Bench, where it leads.
Which is cheaper, GPT-5 or Hy3?
GPT-5 costs $1.25 per million input tokens and $10.00 per million output tokens; Hy3 costs $0.132 and $0.528. Cost per solved task is known for GPT-5 only.
Which has the bigger context window, GPT-5 or Hy3?
GPT-5, with 400K tokens against 262K.
How many benchmarks is the GPT-5 vs Hy3 comparison based on?
42 benchmarks have a result for both models as of October 22, 2026. GPT-5's coding index rests on 3 independent benchmarks and Hy3's on 1. Where only one model has a result, the page says so instead of naming a winner.