GPT-5.1-Codex-Mini vs Qwen3 Coder Next
Updated October 21, 2026. 7 benchmarks have a result for both. Coding is ranked on the Vibe Coding Index; every other board is shown as published.
Decision reading
Neither model has a coding score yet, so the two cannot be ranked on coding.
GPT-5.1-Codex-Mini has the edge where the context window is larger, 400K against 262K tokens, and where the benchmark that matters is τ²-Bench Telecom, where it leads.
- Shared results
- 7
- GPT-5.1-Codex-Mini only
- 15
- Qwen3 Coder Next only
- 4
- Like-for-like categories
- 5 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
Intelligence
AA Intelligence Index
GPT-5.1-Codex-Mini
GPT-5.1-Codex-Mini leads, 20.4 against 9.2.
Same board, both measured
Agentic work
AA Agentic Index
No call
Only Qwen3 Coder Next has a AA Agentic Index result, 0.9.
Directional only
Web design
Design Arena: websites
No call
Only GPT-5.1-Codex-Mini has a Design Arena: websites result, 1111.
Directional only
Long documents
Listed context window
GPT-5.1-Codex-Mini
GPT-5.1-Codex-Mini takes 400K tokens against 262K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Qwen3 Coder Next
GPT-5.1-Codex-Mini $0.0013, Qwen3 Coder Next $0.0005 per turn.
List prices
At a glance
- Coding index
- GPT-5.1-Codex-Mini not benchmarked, Qwen3 Coder Next not benchmarked.
- Widest category
- General, 26.2 points apart on average over 2 shared benchmarks.
- Widest single gap
- IFBench: GPT-5.1-Codex-Mini 67.9% against Qwen3 Coder Next 35.2%, 32.7 points apart on a 0 to 100 scale.
- Output price
- GPT-5.1-Codex-Mini $2.00 against Qwen3 Coder Next $0.80 per million output tokens, 2.5x apart.
- Context window
- GPT-5.1-Codex-Mini takes 400K tokens, Qwen3 Coder Next 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-5.1-Codex-Mini | Bars | Qwen3 Coder Next | Ties |
|---|---|---|---|---|
| Coding | 1 | 0 | ||
| Intelligence | 1 | 0 | ||
| Agentic work | 0 | 1 | ||
| Reasoning | 2 | 0 | ||
| General | 2 | 0 | ||
| All shared boards | 6 | 1 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index10
| Benchmark | GPT-5.1-Codex-Mini | Qwen3 Coder Next | Leader |
|---|---|---|---|
| LMArena WebDev | 1244 | Not measured | Only GPT-5.1-Codex-Mini measured |
| AA Coding Index | Not measured | 36.2 | Only Qwen3 Coder Next measured |
| LiveCodeBench (Artificial Analysis run) | 83.6% | Not measured | Only GPT-5.1-Codex-Mini measured |
| SciCode | Not measured | 36.2% | Only Qwen3 Coder Next measured |
| Terminal-Bench Hard (Artificial Analysis run) | 33.3% | 18.2% | GPT-5.1-Codex-Mini |
| Terminal-Bench | 61.6% | Not measured | Only GPT-5.1-Codex-Mini measured |
| WeirdML | Not measured | 34.4% | Only Qwen3 Coder Next measured |
| LMArena WebDev: HTML | 1253 | Not measured | Only GPT-5.1-Codex-Mini measured |
| Neither model has a result on the other 30 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | GPT-5.1-Codex-Mini | Qwen3 Coder Next | Leader |
|---|---|---|---|
| AA Intelligence Index | 20.4 | 9.2 | GPT-5.1-Codex-Mini |
| Neither model has a result on the other 1 board here | |||
Agentic workLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | GPT-5.1-Codex-Mini | Qwen3 Coder Next | Leader |
|---|---|---|---|
| AA Agentic Index | Not measured | 0.9 | Only Qwen3 Coder Next measured |
| τ²-Bench Telecom | 62.9% | 79.5% | Qwen3 Coder Next |
| Neither model has a result on the other 37 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index20
| Benchmark | GPT-5.1-Codex-Mini | Qwen3 Coder Next | Leader |
|---|---|---|---|
| GPQA Diamond (Artificial Analysis run) | 81.3% | 73.7% | GPT-5.1-Codex-Mini |
| Humanity's Last Exam (Artificial Analysis run) | 18.5% | 10.1% | GPT-5.1-Codex-Mini |
| 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-5.1-Codex-Mini | Qwen3 Coder Next | Leader |
|---|---|---|---|
| AA Math Index | 91.7 | Not measured | Only GPT-5.1-Codex-Mini measured |
| AIME 2025 (Artificial Analysis run) | 91.7% | Not measured | Only GPT-5.1-Codex-Mini 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-5.1-Codex-Mini | Qwen3 Coder Next | Leader |
|---|---|---|---|
| MMLU Pro (Artificial Analysis run) | 82.0% | Not measured | Only GPT-5.1-Codex-Mini measured |
| Neither model has a result on the other 16 boards here | |||
Web designDirectional onlyPublic boards, shown as published, kept out of the index8 boards, none shared
| Benchmark | GPT-5.1-Codex-Mini | Qwen3 Coder Next | Leader |
|---|---|---|---|
| Design Arena: websites | 1111 | Not measured | Only GPT-5.1-Codex-Mini measured |
| Design Arena: UI components | 1081 | Not measured | Only GPT-5.1-Codex-Mini measured |
| Design Arena: game dev | 1092 | Not measured | Only GPT-5.1-Codex-Mini measured |
| Design Arena: data viz | 1096 | Not measured | Only GPT-5.1-Codex-Mini measured |
| Design Arena: 3D | 988 | Not measured | Only GPT-5.1-Codex-Mini measured |
| Design Arena: all code categories | 1094 | Not measured | Only GPT-5.1-Codex-Mini measured |
| Design Arena: SVG | 978 | Not measured | Only GPT-5.1-Codex-Mini measured |
| Design Arena: ASCII art | 1104 | Not measured | Only GPT-5.1-Codex-Mini 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-5.1-Codex-Mini | Qwen3 Coder Next | Leader |
|---|---|---|---|
| IFBench | 67.9% | 35.2% | GPT-5.1-Codex-Mini |
| Long context reasoning (AA-LCR) | 66.7% | 47.0% | GPT-5.1-Codex-Mini |
| 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-5.1-Codex-Mini | Qwen3 Coder Next | 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 Next costs less
Repository review
50K input + 3K output tokens
Qwen3 Coder Next costs less
Agent loop
200K input + 10K output tokens
Qwen3 Coder Next 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-5.1-Codex-Mini | Qwen3 Coder Next |
|---|---|---|
| Maker | OpenAI | Qwen |
| Weights | No public weights listed | Open weights |
| Released | November 13, 2025 | February 4, 2026 |
| Context window | 400K | 262K |
| Input $/Mtok | $0.25 | $0.12 |
| Output $/Mtok | $2.00 | $0.80 |
| Coding index | Not benchmarked | Not benchmarked |
| Independent measurements behind it | 1 | 0 |
| Cost per solved task | Not computable | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is GPT-5.1-Codex-Mini better than Qwen3 Coder Next for coding?
Neither model has a coding score yet, so the two cannot be ranked on coding. GPT-5.1-Codex-Mini has the edge where the context window is larger, 400K against 262K tokens, and where the benchmark that matters is τ²-Bench Telecom, where it leads.
Which is cheaper, GPT-5.1-Codex-Mini or Qwen3 Coder Next?
GPT-5.1-Codex-Mini costs $0.25 per million input tokens and $2.00 per million output tokens; Qwen3 Coder Next costs $0.12 and $0.80. Cost per solved task is known for neither of them.
Which has the bigger context window, GPT-5.1-Codex-Mini or Qwen3 Coder Next?
GPT-5.1-Codex-Mini, with 400K tokens against 262K.
How many benchmarks is the GPT-5.1-Codex-Mini vs Qwen3 Coder Next comparison based on?
7 benchmarks have a result for both models as of October 21, 2026. GPT-5.1-Codex-Mini's coding index rests on 1 independent benchmark and Qwen3 Coder Next's on 0. Where only one model has a result, the page says so instead of naming a winner.