GPT-5.3-Codex vs Qwen3.5 Plus 2026-04-20
GPT-5.3-Codex leads Qwen3.5 Plus 2026-04-20 on coding, 60.0 to 39.5 on the Vibe Coding Index, and Qwen3.5 Plus 2026-04-20 costs 7.8x less per output token ($1.80 vs $14.00 per million). Updated October 22, 2026; 6 benchmarks have a result for both.
GPT-5.3-Codex or Qwen3.5 Plus 2026-04-20: which to pick
Pick GPT-5.3-Codex for coding: it scores 60.0 on the Vibe Coding Index against 39.5 for Qwen3.5 Plus 2026-04-20.
Pick Qwen3.5 Plus 2026-04-20 for output tokens 7.8x cheaper ($1.80 vs $14.00 per million) and a larger context window (1M against 400K tokens).
- Shared results
- 6
- GPT-5.3-Codex only
- 28
- Qwen3.5 Plus 2026-04-20 only
- 19
- Like-for-like categories
- 3 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-5.3-Codex
GPT-5.3-Codex scores 60.0 against 39.5.
3 and 2 benchmarks behind the scores
Intelligence
AA Intelligence Index
No call
Only GPT-5.3-Codex has a AA Intelligence Index result, 32.5.
Directional only
Reasoning
GPQA Diamond
No call
Only Qwen3.5 Plus 2026-04-20 has a GPQA Diamond result, 87.4%.
Directional only
Math
AIME
No call
Only Qwen3.5 Plus 2026-04-20 has a AIME result, 86.0%.
Directional only
Knowledge
MMLU Pro
No call
Only Qwen3.5 Plus 2026-04-20 has a MMLU Pro result, 87.2%.
Directional only
Web design
Design Arena: websites
No call
Only GPT-5.3-Codex has a Design Arena: websites result, 1162.
Directional only
Long documents
Listed context window
Qwen3.5 Plus 2026-04-20
Qwen3.5 Plus 2026-04-20 takes 1M tokens against 400K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Qwen3.5 Plus 2026-04-20
GPT-5.3-Codex $0.0088, Qwen3.5 Plus 2026-04-20 $0.0012 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
GPT-5.3-Codex
GPT-5.3-Codex $0.59, Qwen3.5 Plus 2026-04-20 $1.35.
Published attempt cost and pass rate
At a glance
- Coding index
- GPT-5.3-Codex 60.0 from 3 benchmarks, Qwen3.5 Plus 2026-04-20 39.5 from 2 benchmarks.
- Widest category
- Agentic work, 37.1 points apart on average over 1 shared benchmark.
- Widest single gap
- Vibe Code Bench (Vals AI): GPT-5.3-Codex 61.8% against Qwen3.5 Plus 2026-04-20 15.7%, 46.0 points apart on a 0 to 100 scale.
- Output price
- GPT-5.3-Codex $14.00 against Qwen3.5 Plus 2026-04-20 $1.80 per million output tokens, 7.8x apart.
- Context window
- GPT-5.3-Codex takes 400K tokens, Qwen3.5 Plus 2026-04-20 1M.
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 | Qwen3.5 Plus 2026-04-20 | Ties |
|---|---|---|---|---|
| Coding | 4 | 0 | ||
| Intelligence | 1 | 0 | ||
| Agentic work | 1 | 0 | ||
| All shared boards | 6 | 0 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index40
| Benchmark | GPT-5.3-Codex | Qwen3.5 Plus 2026-04-20 | Leader |
|---|---|---|---|
| LMArena WebDev | 1407 | Not measured | Only GPT-5.3-Codex measured |
| LiveCodeBench (Vals AI) | 87.3% | 85.3% | GPT-5.3-Codex |
| SWE-bench Verified (Vals AI) | 78.0% | 71.2% | GPT-5.3-Codex |
| Vibe Code Bench (Vals AI) | 61.8% | 15.7% | GPT-5.3-Codex |
| 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 | 608.9 | GPT-5.3-Codex |
| 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 |
| Neither model has a result on the other 27 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | GPT-5.3-Codex | Qwen3.5 Plus 2026-04-20 | Leader |
|---|---|---|---|
| AA Intelligence Index | 32.5 | Not measured | Only GPT-5.3-Codex measured |
| Epoch Capabilities Index | 157.1 | 146.2 | GPT-5.3-Codex |
Agentic workLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | GPT-5.3-Codex | Qwen3.5 Plus 2026-04-20 | Leader |
|---|---|---|---|
| Design Arena: agents building web apps | 1032 | Not measured | Only GPT-5.3-Codex measured |
| Design Arena: agents building full-stack apps | 983 | Not measured | Only GPT-5.3-Codex measured |
| Design Arena: agents building mobile apps | 1053 | 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 |
| 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 | $1 | GPT-5.3-Codex |
| Neither model has a result on the other 33 boards here | |||
ReasoningDirectional onlyPublic boards, shown as published, kept out of the index7 boards, none shared
| Benchmark | GPT-5.3-Codex | Qwen3.5 Plus 2026-04-20 | Leader |
|---|---|---|---|
| GPQA Diamond | Not measured | 87.4% | Only Qwen3.5 Plus 2026-04-20 measured |
| MMMU Pro (Vals AI) | Not measured | 22.8% | Only Qwen3.5 Plus 2026-04-20 measured |
| 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 |
| GPQA Diamond (Epoch AI run) | Not measured | 84.8% | Only Qwen3.5 Plus 2026-04-20 measured |
| Chess puzzles | Not measured | 8.0% | Only Qwen3.5 Plus 2026-04-20 measured |
| Mystery game puzzles | Not measured | 17.0% | Only Qwen3.5 Plus 2026-04-20 measured |
| Neither model has a result on the other 15 boards here | |||
MathDirectional onlyPublic boards, shown as published, kept out of the index2 boards, none shared
| Benchmark | GPT-5.3-Codex | Qwen3.5 Plus 2026-04-20 | Leader |
|---|---|---|---|
| AIME | Not measured | 86.0% | Only Qwen3.5 Plus 2026-04-20 measured |
| OTIS Mock AIME | Not measured | 86.7% | Only Qwen3.5 Plus 2026-04-20 measured |
| Neither model has a result on the other 11 boards here | |||
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index7 boards, none shared
| Benchmark | GPT-5.3-Codex | Qwen3.5 Plus 2026-04-20 | Leader |
|---|---|---|---|
| MMLU Pro | Not measured | 87.2% | Only Qwen3.5 Plus 2026-04-20 measured |
| LegalBench (Vals AI) | Not measured | 85.1% | Only Qwen3.5 Plus 2026-04-20 measured |
| CaseLaw (Vals AI) | Not measured | 59.7% | Only Qwen3.5 Plus 2026-04-20 measured |
| CorpFin (Vals AI) | Not measured | 65.3% | Only Qwen3.5 Plus 2026-04-20 measured |
| MortgageTax (Vals AI) | Not measured | 60.8% | Only Qwen3.5 Plus 2026-04-20 measured |
| MedQA (Vals AI) | Not measured | 95.2% | Only Qwen3.5 Plus 2026-04-20 measured |
| SimpleQA Verified | Not measured | 25.4% | Only Qwen3.5 Plus 2026-04-20 measured |
| Neither model has a result on the other 11 boards here | |||
Web designDirectional onlyPublic boards, shown as published, kept out of the index8 boards, none shared
| Benchmark | GPT-5.3-Codex | Qwen3.5 Plus 2026-04-20 | Leader |
|---|---|---|---|
| Design Arena: websites | 1162 | Not measured | Only GPT-5.3-Codex measured |
| Design Arena: UI components | 1134 | Not measured | Only GPT-5.3-Codex measured |
| Design Arena: game dev | 1161 | Not measured | Only GPT-5.3-Codex measured |
| Design Arena: data viz | 1164 | Not measured | Only GPT-5.3-Codex measured |
| Design Arena: 3D | 1007 | Not measured | Only GPT-5.3-Codex measured |
| Design Arena: all code categories | 1144 | Not measured | Only GPT-5.3-Codex measured |
| Design Arena: SVG | 1129 | Not measured | Only GPT-5.3-Codex measured |
| Design Arena: ASCII art | 1152 | 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 index7 boards, none shared
| Benchmark | GPT-5.3-Codex | Qwen3.5 Plus 2026-04-20 | Leader |
|---|---|---|---|
| SAGE (Vals AI) | Not measured | 30.4% | Only Qwen3.5 Plus 2026-04-20 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 |
| DTBench | Not measured | 80.5% | Only Qwen3.5 Plus 2026-04-20 measured |
| LMCA | Not measured | 36.4% | Only Qwen3.5 Plus 2026-04-20 measured |
| CL-bench | Not measured | 19.8% | Only Qwen3.5 Plus 2026-04-20 measured |
| CL-bench Life | Not measured | 12.4% | Only Qwen3.5 Plus 2026-04-20 measured |
| Neither model has a result on the other 39 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | GPT-5.3-Codex | Qwen3.5 Plus 2026-04-20 | 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
Qwen3.5 Plus 2026-04-20 costs less
Repository review
50K input + 3K output tokens
Qwen3.5 Plus 2026-04-20 costs less
Agent loop
200K input + 10K output tokens
Qwen3.5 Plus 2026-04-20 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 | Qwen3.5 Plus 2026-04-20 |
|---|---|---|
| Maker | OpenAI | Qwen |
| Weights | No public weights listed | No public weights listed |
| Released | February 24, 2026 | April 27, 2026 |
| Context window | 400K | 1M |
| Input $/Mtok | $1.75 | $0.30 |
| Output $/Mtok | $14.00 | $1.80 |
| Coding index | 60.0 | 39.5 |
| Independent measurements behind it | 3 | 2 |
| Cost per solved task | $0.59 | $1.35 |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is GPT-5.3-Codex better than Qwen3.5 Plus 2026-04-20 for coding?
Pick GPT-5.3-Codex for coding: it scores 60.0 on the Vibe Coding Index against 39.5 for Qwen3.5 Plus 2026-04-20. Pick Qwen3.5 Plus 2026-04-20 for output tokens 7.8x cheaper ($1.80 vs $14.00 per million) and a larger context window (1M against 400K tokens).
Which is cheaper, GPT-5.3-Codex or Qwen3.5 Plus 2026-04-20?
GPT-5.3-Codex costs $1.75 per million input tokens and $14.00 per million output tokens; Qwen3.5 Plus 2026-04-20 costs $0.30 and $1.80. Per solved SWE-bench Verified task, GPT-5.3-Codex costs $0.59 and Qwen3.5 Plus 2026-04-20 $1.35.
Which has the bigger context window, GPT-5.3-Codex or Qwen3.5 Plus 2026-04-20?
Qwen3.5 Plus 2026-04-20, with 1M tokens against 400K.
How many benchmarks is the GPT-5.3-Codex vs Qwen3.5 Plus 2026-04-20 comparison based on?
6 benchmarks have a result for both models as of October 22, 2026. GPT-5.3-Codex's coding index rests on 3 independent benchmarks and Qwen3.5 Plus 2026-04-20's on 2. Where only one model has a result, the page says so instead of naming a winner.