GPT-5.3-Codex vs Qwen3 Coder 30B A3B Instruct
Updated October 21, 2026. 10 benchmarks have a result for both. Coding is ranked on the Vibe Coding Index; every other board is shown as published.
Decision reading
Pick Qwen3 Coder 30B A3B Instruct for coding: it scores 60.4 on the Vibe Coding Index against 29.5 for GPT-5.3-Codex.
Pick GPT-5.3-Codex when the context window is larger, 400K against 262K tokens, or when what matters is Terminal-Bench Hard (Artificial Analysis run) or AA Intelligence Index, where it leads.
- Shared results
- 10
- GPT-5.3-Codex only
- 24
- Qwen3 Coder 30B A3B Instruct only
- 6
- 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
Qwen3 Coder 30B A3B Instruct
Qwen3 Coder 30B A3B Instruct scores 60.4 against 29.5.
One benchmark behind each score
Intelligence
AA Intelligence Index
GPT-5.3-Codex
GPT-5.3-Codex leads, 32.5 against 9.6.
Same board, both measured
Web design
Design Arena: websites
GPT-5.3-Codex
GPT-5.3-Codex leads, 1163 against 1087.
Same board, both measured
Long documents
Listed context window
GPT-5.3-Codex
GPT-5.3-Codex takes 400K tokens against 262K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Qwen3 Coder 30B A3B Instruct
GPT-5.3-Codex $0.0088, Qwen3 Coder 30B A3B Instruct $0.0002 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 29.5 from 1 benchmark, Qwen3 Coder 30B A3B Instruct 60.4 from 1 benchmark.
- Widest category
- Agentic work, 51.5 points apart on average over 1 shared benchmark.
- Widest single gap
- τ²-Bench Telecom: GPT-5.3-Codex 86.0% against Qwen3 Coder 30B A3B Instruct 34.5%, 51.5 points apart on a 0 to 100 scale.
- Output price
- GPT-5.3-Codex $14.00 against Qwen3 Coder 30B A3B Instruct $0.28 per million output tokens, 50.0x apart.
- Context window
- GPT-5.3-Codex takes 400K tokens, Qwen3 Coder 30B A3B Instruct 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-5.3-Codex | Bars | Qwen3 Coder 30B A3B Instruct | Ties |
|---|---|---|---|---|
| Coding | 1 | 0 | ||
| Intelligence | 1 | 0 | ||
| Agentic work | 1 | 0 | ||
| Reasoning | 2 | 0 | ||
| Web design | 3 | 0 | ||
| General | 2 | 0 | ||
| All shared boards | 10 | 0 |
CodingLike-for-likeFour of these boards feed the Vibe Coding Index10
| Benchmark | GPT-5.3-Codex | Qwen3 Coder 30B A3B Instruct | Leader |
|---|---|---|---|
| SWE-bench Verified | Not measured | 60.4% | Only Qwen3 Coder 30B A3B Instruct measured |
| SWE-bench Lite | Not measured | 49.7% | Only Qwen3 Coder 30B A3B Instruct measured |
| 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 |
| Vibe Code Bench (Vals AI) | 61.8% | Not measured | Only GPT-5.3-Codex measured |
| IOI (Vals AI) | 53.8% | Not measured | Only GPT-5.3-Codex measured |
| LiveCodeBench (Artificial Analysis run) | Not measured | 40.3% | Only Qwen3 Coder 30B A3B Instruct measured |
| Terminal-Bench Hard (Artificial Analysis run) | 53.0% | 15.2% | GPT-5.3-Codex |
| 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 |
| Neither model has a result on the other 23 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | GPT-5.3-Codex | Qwen3 Coder 30B A3B Instruct | Leader |
|---|---|---|---|
| AA Intelligence Index | 32.5 | 9.6 | GPT-5.3-Codex |
| Epoch Capabilities Index | 157.1 | Not measured | Only GPT-5.3-Codex measured |
Agentic workLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | GPT-5.3-Codex | Qwen3 Coder 30B A3B Instruct | Leader |
|---|---|---|---|
| Design Arena: agents building web apps | 1033 | 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 | 1054 | 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% | 34.5% | GPT-5.3-Codex |
| 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 31 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index20
| Benchmark | GPT-5.3-Codex | Qwen3 Coder 30B A3B Instruct | Leader |
|---|---|---|---|
| GPQA Diamond (Artificial Analysis run) | 91.5% | 51.6% | GPT-5.3-Codex |
| Humanity's Last Exam (Artificial Analysis run) | 42.5% | 3.8% | GPT-5.3-Codex |
| Neither model has a result on the other 19 boards here | |||
MathDirectional onlyPublic boards, shown as published, kept out of the index2 boards, none shared
| Benchmark | GPT-5.3-Codex | Qwen3 Coder 30B A3B Instruct | Leader |
|---|---|---|---|
| AA Math Index | Not measured | 29.0 | Only Qwen3 Coder 30B A3B Instruct measured |
| AIME 2025 (Artificial Analysis run) | Not measured | 29.0% | Only Qwen3 Coder 30B A3B Instruct measured |
| Neither model has a result on the other 11 boards here | |||
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index1 board, none shared
| Benchmark | GPT-5.3-Codex | Qwen3 Coder 30B A3B Instruct | Leader |
|---|---|---|---|
| MMLU Pro (Artificial Analysis run) | Not measured | 70.6% | Only Qwen3 Coder 30B A3B Instruct measured |
| Neither model has a result on the other 16 boards here | |||
Web designLike-for-likePublic boards, shown as published, kept out of the index30
| Benchmark | GPT-5.3-Codex | Qwen3 Coder 30B A3B Instruct | Leader |
|---|---|---|---|
| Design Arena: websites | 1163 | 1087 | GPT-5.3-Codex |
| Design Arena: UI components | 1137 | 1046 | GPT-5.3-Codex |
| Design Arena: game dev | 1162 | Not measured | Only GPT-5.3-Codex measured |
| Design Arena: data viz | 1164 | 1085 | GPT-5.3-Codex |
| Design Arena: 3D | 1008 | Not measured | Only GPT-5.3-Codex measured |
| Design Arena: all code categories | 1145 | Not measured | Only GPT-5.3-Codex measured |
| Design Arena: SVG | 1129 | Not measured | Only GPT-5.3-Codex measured |
| Design Arena: ASCII art | 1151 | Not measured | Only GPT-5.3-Codex measured |
| Neither model has a result on the other 1 board here | |||
GeneralLike-for-likePublic boards, shown as published, kept out of the index20
| Benchmark | GPT-5.3-Codex | Qwen3 Coder 30B A3B Instruct | Leader |
|---|---|---|---|
| IFBench | 75.4% | 32.7% | GPT-5.3-Codex |
| Long context reasoning (AA-LCR) | 83.3% | 32.7% | GPT-5.3-Codex |
| Neither model has a result on the other 44 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | GPT-5.3-Codex | Qwen3 Coder 30B A3B Instruct | 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 Coder 30B A3B Instruct costs less
Repository review
50K input + 3K output tokens
Qwen3 Coder 30B A3B Instruct costs less
Agent loop
200K input + 10K output tokens
Qwen3 Coder 30B A3B Instruct 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 Coder 30B A3B Instruct |
|---|---|---|
| Maker | OpenAI | Qwen |
| Weights | No public weights listed | Open weights |
| Released | February 24, 2026 | July 31, 2025 |
| Context window | 400K | 262K |
| Input $/Mtok | $1.75 | $0.07 |
| Output $/Mtok | $14.00 | $0.28 |
| Coding index | 29.5 | 60.4 |
| Independent measurements behind it | 1 | 1 |
| Cost per solved task | $0.59 | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is GPT-5.3-Codex better than Qwen3 Coder 30B A3B Instruct for coding?
Pick Qwen3 Coder 30B A3B Instruct for coding: it scores 60.4 on the Vibe Coding Index against 29.5 for GPT-5.3-Codex. Pick GPT-5.3-Codex when the context window is larger, 400K against 262K tokens, or when what matters is Terminal-Bench Hard (Artificial Analysis run) or AA Intelligence Index, where it leads.
Which is cheaper, GPT-5.3-Codex or Qwen3 Coder 30B A3B Instruct?
GPT-5.3-Codex costs $1.75 per million input tokens and $14.00 per million output tokens; Qwen3 Coder 30B A3B Instruct costs $0.07 and $0.28. Cost per solved task is known for GPT-5.3-Codex only.
Which has the bigger context window, GPT-5.3-Codex or Qwen3 Coder 30B A3B Instruct?
GPT-5.3-Codex, with 400K tokens against 262K.
How many benchmarks is the GPT-5.3-Codex vs Qwen3 Coder 30B A3B Instruct comparison based on?
10 benchmarks have a result for both models as of October 21, 2026. GPT-5.3-Codex's coding index rests on 1 independent benchmark and Qwen3 Coder 30B A3B Instruct's on 1. Where only one model has a result, the page says so instead of naming a winner.