GPT-5.3-Codex vs Hy4
Hy4 leads GPT-5.3-Codex on coding, 65.2 to 60.0 on the Vibe Coding Index, and Hy4 costs 11.2x less per output token ($1.2505 vs $14.00 per million). Updated November 5, 2026; 1 benchmarks have a result for both.
GPT-5.3-Codex or Hy4: which to pick
Pick Hy4 for coding: it scores 65.2 on the Vibe Coding Index against 60.0 for GPT-5.3-Codex, though on 2 benchmarks against 3.
GPT-5.3-Codex is neither cheaper nor larger in context, and leads no benchmark both models were measured on.
- Shared results
- 1
- GPT-5.3-Codex only
- 32
- Hy4 only
- 5
- Like-for-like categories
- 1 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
Hy4
Hy4 scores 65.2 against 60.0.
3 and 2 benchmarks behind the scores
Web design
Design Arena: websites
No call
Only GPT-5.3-Codex has a Design Arena: websites result, 1162.
Directional only
General
Vals Index
No call
Only Hy4 has a Vals Index result, 59.4%.
Directional only
Long documents
Listed context window
Hy4
Hy4 takes 1.05M tokens against 400K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Hy4
GPT-5.3-Codex $0.0088, Hy4 $0.0010 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
No call
Only GPT-5.3-Codex has the number, $0.59.
Directional only
At a glance
- Coding index
- GPT-5.3-Codex 60.0 from 3 benchmarks, Hy4 65.2 from 2 benchmarks.
- Widest category
- Coding, 19.2 points apart on average over 1 shared benchmark.
- Widest single gap
- Vibe Code Bench (Vals AI): GPT-5.3-Codex 61.8% against Hy4 81.0%, 19.2 points apart on a 0 to 100 scale.
- Output price
- GPT-5.3-Codex $14.00 against Hy4 $1.2505 per million output tokens, 11.2x apart.
- Context window
- GPT-5.3-Codex takes 400K tokens, Hy4 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-5.3-Codex | Bars | Hy4 | Ties |
|---|---|---|---|---|
| Coding | 0 | 1 | ||
| All shared boards | 0 | 1 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index01
| Benchmark | GPT-5.3-Codex | Hy4 | Leader |
|---|---|---|---|
| LMArena WebDev | 1407 | Not measured | Only GPT-5.3-Codex measured |
| LiveCodeBench (Vals AI) | 87.3% | Not measured | Only GPT-5.3-Codex measured |
| SWE-bench Verified (Vals AI) | 78.0% | Not measured | Only GPT-5.3-Codex measured |
| Terminal-Bench 4 (Vals AI) | Not measured | 39.4% | Only Hy4 measured |
| Vibe Code Bench (Vals AI) | 61.8% | 81.0% | Hy4 |
| IOI (Vals AI) | 53.8% | Not measured | Only GPT-5.3-Codex measured |
| Terminal-Bench Hard (Artificial Analysis run) | 53.0% | Not measured | Only GPT-5.3-Codex measured |
| Terminal-Bench | 78.4% | Not measured | Only GPT-5.3-Codex measured |
| WeirdML | 79.3% | Not measured | Only GPT-5.3-Codex measured |
| ALE-Bench | 1655.2 | Not measured | Only GPT-5.3-Codex measured |
| LMArena WebDev: React | 1395 | Not measured | Only GPT-5.3-Codex measured |
| LMArena WebDev: HTML | 1422 | Not measured | Only GPT-5.3-Codex measured |
| LMArena WebDev: from an image | 1443 | Not measured | Only GPT-5.3-Codex measured |
| Terminal-Bench 2.0 | 78.4% | Not measured | Only GPT-5.3-Codex measured |
| Neither model has a result on the other 36 boards here | |||
IntelligenceNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | GPT-5.3-Codex | Hy4 | Leader |
|---|---|---|---|
| Neither model has a result on 2 boards here | |||
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index11 boards, none shared
| Benchmark | GPT-5.3-Codex | Hy4 | Leader |
|---|---|---|---|
| Design Arena: agents building web apps | 1019 | Not measured | Only GPT-5.3-Codex measured |
| Design Arena: agents building full-stack apps | 979 | Not measured | Only GPT-5.3-Codex measured |
| Design Arena: agents building mobile apps | 1052 | Not measured | Only GPT-5.3-Codex measured |
| Design Arena: agents building Android apps | 1084 | Not measured | Only GPT-5.3-Codex measured |
| Design Arena: agents building Godot games | 1124 | Not measured | Only GPT-5.3-Codex measured |
| Tax Agent Bench (Vals AI) | Not measured | 34.4% | Only Hy4 measured |
| Legal Research Bench (Vals AI) | Not measured | 41.4% | Only Hy4 measured |
| Harvey's Legal Agent Benchmark (Vals AI) | Not measured | 12.5% | Only Hy4 measured |
| τ²-Bench Telecom | 86.0% | Not measured | Only GPT-5.3-Codex measured |
| METR time horizons | 74.5% | Not measured | Only GPT-5.3-Codex measured |
| Vending-Bench 2 | $5,940 | Not measured | Only GPT-5.3-Codex measured |
| Neither model has a result on the other 33 boards here | |||
ReasoningDirectional onlyPublic boards, shown as published, kept out of the index2 boards, none shared
| Benchmark | GPT-5.3-Codex | Hy4 | Leader |
|---|---|---|---|
| GPQA Diamond (Artificial Analysis run) | 91.5% | Not measured | Only GPT-5.3-Codex measured |
| Humanity's Last Exam (Artificial Analysis run) | 42.5% | Not measured | Only GPT-5.3-Codex measured |
| Neither model has a result on the other 22 boards here | |||
MathNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | GPT-5.3-Codex | Hy4 | Leader |
|---|---|---|---|
| Neither model has a result on 14 boards here | |||
KnowledgeNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | GPT-5.3-Codex | Hy4 | Leader |
|---|---|---|---|
| Neither model has a result on 20 boards here | |||
Web designDirectional onlyPublic boards, shown as published, kept out of the index8 boards, none shared
| Benchmark | GPT-5.3-Codex | Hy4 | Leader |
|---|---|---|---|
| Design Arena: websites | 1162 | Not measured | Only GPT-5.3-Codex measured |
| Design Arena: UI components | 1133 | Not measured | Only GPT-5.3-Codex measured |
| Design Arena: game dev | 1160 | Not measured | Only GPT-5.3-Codex measured |
| Design Arena: data viz | 1164 | Not measured | Only GPT-5.3-Codex measured |
| Design Arena: 3D | 1005 | Not measured | Only GPT-5.3-Codex measured |
| Design Arena: all code categories | 1143 | Not measured | Only GPT-5.3-Codex measured |
| Design Arena: SVG | 1125 | Not measured | Only GPT-5.3-Codex measured |
| Design Arena: ASCII art | 1148 | Not measured | Only GPT-5.3-Codex measured |
| Neither model has a result on the other 1 board here | |||
GeneralDirectional onlyPublic boards, shown as published, kept out of the index3 boards, none shared
| Benchmark | GPT-5.3-Codex | Hy4 | Leader |
|---|---|---|---|
| Vals Index | Not measured | 59.4% | Only Hy4 measured |
| IFBench | 75.4% | Not measured | Only GPT-5.3-Codex measured |
| Long context reasoning (AA-LCR) | 83.3% | Not measured | Only GPT-5.3-Codex measured |
| Neither model has a result on the other 45 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | GPT-5.3-Codex | Hy4 | 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
Hy4 costs less
Repository review
50K input + 3K output tokens
Hy4 costs less
Agent loop
200K input + 10K output tokens
Hy4 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-5.3-Codex | Tencent Hy4 |
|---|---|---|
| Maker | OpenAI | Tencent |
| Weights | No public weights listed | Open weights |
| Released | February 24, 2026 | November 4, 2026 |
| Context window | 400K | 1.05M |
| Input $/Mtok | $1.75 | $0.417 |
| Output $/Mtok | $14.00 | $1.2505 |
| Coding index | 60.0 | 65.2 |
| Independent measurements behind it | 3 | 2 |
| Cost per solved task | $0.59 | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is GPT-5.3-Codex better than Hy4 for coding?
Pick Hy4 for coding: it scores 65.2 on the Vibe Coding Index against 60.0 for GPT-5.3-Codex, though on 2 benchmarks against 3. GPT-5.3-Codex is neither cheaper nor larger in context, and leads no benchmark both models were measured on.
Which is cheaper, GPT-5.3-Codex or Hy4?
GPT-5.3-Codex costs $1.75 per million input tokens and $14.00 per million output tokens; Hy4 costs $0.417 and $1.2505. Cost per solved task is known for GPT-5.3-Codex only.
Which has the bigger context window, GPT-5.3-Codex or Hy4?
Hy4, with 1.05M tokens against 400K.
How many benchmarks is the GPT-5.3-Codex vs Hy4 comparison based on?
1 benchmarks have a result for both models as of November 5, 2026. GPT-5.3-Codex's coding index rests on 3 independent benchmarks and Hy4's on 2. Where only one model has a result, the page says so instead of naming a winner.