GPT-5 Pro vs Hy3
Updated October 21, 2026. 0 benchmarks have a result for both. Coding is ranked on the Vibe Coding Index; every other board is shown as published.
- Coding
- No data
- Overall
- No data
- Output $/M
- $120.00
- Coding
- No data
- Overall
- No data
- Output $/M
- $0.528
Decision reading
Neither model has a coding score yet, so the two cannot be ranked on coding.
GPT-5 Pro has the edge where the context window is larger, 400K against 262K tokens.
- Shared results
- 0
- GPT-5 Pro only
- 8
- Hy3 only
- 44
- Like-for-like categories
- 0 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, six public coding benchmarks
No call
Neither has a coding score yet.
One side not measured
Web design
Design Arena: websites
No call
Only Hy3 has a Design Arena: websites result, 1230.
Directional only
Long documents
Listed context window
GPT-5 Pro
GPT-5 Pro takes 400K tokens against 262K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Hy3
GPT-5 Pro $0.075, Hy3 $0.0004 per turn.
List prices
At a glance
- Coding index
- GPT-5 Pro not benchmarked, Hy3 not benchmarked.
- Widest category
- No category has a result for both models.
- Widest single gap
- No benchmark has a result for both models.
- Output price
- GPT-5 Pro $120.00 against Hy3 $0.528 per million output tokens, 227.3x apart.
- Context window
- GPT-5 Pro 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.
CodingDirectional onlySix of these boards feed the Vibe Coding Index8 boards, none shared
| Benchmark | GPT-5 Pro | Hy3 | Leader |
|---|---|---|---|
| LMArena WebDev | Not measured | 1507 | Only Hy3 measured |
| SciCode | Not measured | 48.6% | Only Hy3 measured |
| WeirdML | 60.4% | Not measured | Only GPT-5 Pro measured |
| ALE-Bench | Not measured | 838.6 | Only Hy3 measured |
| LMArena Text: coding | Not measured | 1466 | Only Hy3 measured |
| LMArena Text: software and IT | Not measured | 1463 | Only Hy3 measured |
| LMArena WebDev: React | Not measured | 1511 | Only Hy3 measured |
| LMArena WebDev: HTML | Not measured | 1487 | Only Hy3 measured |
| Neither model has a result on the other 30 boards here | |||
IntelligenceDirectional onlyPublic boards, shown as published, kept out of the index1 board, none shared
| Benchmark | GPT-5 Pro | Hy3 | Leader |
|---|---|---|---|
| Epoch Capabilities Index | 150.6 | Not measured | Only GPT-5 Pro measured |
| Neither model has a result on the other 1 board here | |||
Agentic workNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | GPT-5 Pro | Hy3 | Leader |
|---|---|---|---|
| Neither model has a result on 39 boards here | |||
ReasoningDirectional onlyPublic boards, shown as published, kept out of the index9 boards, none shared
| Benchmark | GPT-5 Pro | Hy3 | Leader |
|---|---|---|---|
| GPQA Diamond (Artificial Analysis run) | Not measured | 89.7% | Only Hy3 measured |
| Humanity's Last Exam (Artificial Analysis run) | Not measured | 33.5% | Only Hy3 measured |
| ARC-AGI | 70.2% | Not measured | Only GPT-5 Pro measured |
| ARC-AGI-2 | 18.3% | Not measured | Only GPT-5 Pro measured |
| SimpleBench | 61.6% | Not measured | Only GPT-5 Pro measured |
| Chess puzzles | 48.0% | Not measured | Only GPT-5 Pro measured |
| LMArena Text: hard prompts | Not measured | 1447 | Only Hy3 measured |
| LMArena Text: expert | Not measured | 1461 | Only Hy3 measured |
| LMArena Text: hard prompts in English | Not measured | 1455 | Only Hy3 measured |
| Neither model has a result on the other 12 boards here | |||
MathDirectional onlyPublic boards, shown as published, kept out of the index4 boards, none shared
| Benchmark | GPT-5 Pro | Hy3 | Leader |
|---|---|---|---|
| FrontierMath, tiers 1 to 3 | 55.8% | Not measured | Only GPT-5 Pro measured |
| FrontierMath, tier 4 | 19.5% | Not measured | Only GPT-5 Pro measured |
| LMArena Text: math | Not measured | 1473 | Only Hy3 measured |
| LMArena Text: mathematical work | Not measured | 1482 | Only Hy3 measured |
| Neither model has a result on the other 9 boards here | |||
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index4 boards, none shared
| Benchmark | GPT-5 Pro | Hy3 | Leader |
|---|---|---|---|
| LMArena Text: science | Not measured | 1457 | Only Hy3 measured |
| LMArena Text: medicine and healthcare | Not measured | 1452 | Only Hy3 measured |
| LMArena Text: legal and government | Not measured | 1422 | Only Hy3 measured |
| LMArena Text: business and finance | Not measured | 1424 | Only Hy3 measured |
| Neither model has a result on the other 13 boards here | |||
Web designDirectional onlyPublic boards, shown as published, kept out of the index8 boards, none shared
| Benchmark | GPT-5 Pro | Hy3 | Leader |
|---|---|---|---|
| Design Arena: websites | Not measured | 1230 | Only Hy3 measured |
| Design Arena: UI components | Not measured | 1207 | Only Hy3 measured |
| Design Arena: game dev | Not measured | 1208 | Only Hy3 measured |
| Design Arena: data viz | Not measured | 1163 | Only Hy3 measured |
| Design Arena: 3D | Not measured | 1233 | Only Hy3 measured |
| Design Arena: all code categories | Not measured | 1227 | Only Hy3 measured |
| Design Arena: SVG | Not measured | 1200 | Only Hy3 measured |
| Design Arena: ASCII art | Not measured | 1157 | Only Hy3 measured |
| Neither model has a result on the other 1 board here | |||
GeneralDirectional onlyPublic boards, shown as published, kept out of the index18 boards, none shared
| Benchmark | GPT-5 Pro | Hy3 | Leader |
|---|---|---|---|
| Long context reasoning (AA-LCR) | Not measured | 79.0% | Only Hy3 measured |
| LMArena Text | Not measured | 1438 | Only Hy3 measured |
| LMArena Text: instruction following | Not measured | 1426 | Only Hy3 measured |
| LMArena Text: creative writing | Not measured | 1403 | Only Hy3 measured |
| LMArena Text: English | Not measured | 1448 | Only Hy3 measured |
| LMArena Text: non-English | Not measured | 1426 | Only Hy3 measured |
| LMArena Text: Chinese | Not measured | 1485 | Only Hy3 measured |
| LMArena Text: German | Not measured | 1449 | Only Hy3 measured |
| LMArena Text: Japanese | Not measured | 1397 | Only Hy3 measured |
| LMArena Text: Korean | Not measured | 1396 | Only Hy3 measured |
| LMArena Text: French | Not measured | 1456 | Only Hy3 measured |
| LMArena Text: Spanish | Not measured | 1457 | Only Hy3 measured |
| LMArena Text: Russian | Not measured | 1432 | Only Hy3 measured |
| LMArena Text: Polish | Not measured | 1447 | Only Hy3 measured |
| LMArena Text: multi-turn | Not measured | 1436 | Only Hy3 measured |
| LMArena Text: longer queries | Not measured | 1442 | Only Hy3 measured |
| LMArena Text: writing and language | Not measured | 1414 | Only Hy3 measured |
| LMArena Text: entertainment and media | Not measured | 1400 | Only Hy3 measured |
| Neither model has a result on the other 28 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | GPT-5 Pro | 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 Pro | Tencent Hy3 |
|---|---|---|
| Maker | OpenAI | Tencent |
| Weights | No public weights listed | Open weights |
| Released | October 6, 2025 | July 6, 2026 |
| Context window | 400K | 262K |
| Input $/Mtok | $15.00 | $0.132 |
| Output $/Mtok | $120.00 | $0.528 |
| Coding index | Not benchmarked | Not benchmarked |
| Independent measurements behind it | 0 | 1 |
| Cost per solved task | Not computable | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is GPT-5 Pro better than Hy3 for coding?
Neither model has a coding score yet, so the two cannot be ranked on coding. GPT-5 Pro has the edge where the context window is larger, 400K against 262K tokens.
Which is cheaper, GPT-5 Pro or Hy3?
GPT-5 Pro costs $15.00 per million input tokens and $120.00 per million output tokens; Hy3 costs $0.132 and $0.528. Cost per solved task is known for neither of them.
Which has the bigger context window, GPT-5 Pro or Hy3?
GPT-5 Pro, with 400K tokens against 262K.
How many benchmarks is the GPT-5 Pro vs Hy3 comparison based on?
0 benchmarks have a result for both models as of October 21, 2026. GPT-5 Pro's coding index rests on 0 independent benchmarks and Hy3's on 1. Where only one model has a result, the page says so instead of naming a winner.