GPT-5.1-Codex-Mini vs Ministral 3 14B 2512
GPT-5.1-Codex-Mini leads Ministral 3 14B 2512 on the Artificial Analysis Intelligence Index, 20.4 to 6.0, and Ministral 3 14B 2512 costs 10.0x less per output token ($0.20 vs $2.00 per million). Updated October 23, 2026; 5 benchmarks have a result for both.
GPT-5.1-Codex-Mini or Ministral 3 14B 2512: which to pick
Neither model has a coding score yet, so the two cannot be ranked on coding.
Pick GPT-5.1-Codex-Mini for a larger context window (400K against 262K tokens) and work measured by Design Arena: 3D, where it leads.
- Shared results
- 5
- GPT-5.1-Codex-Mini only
- 17
- Ministral 3 14B 2512 only
- 2
- Like-for-like categories
- 2 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
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 6.0.
Same board, both measured
Agentic work
AA Agentic Index
No call
Only Ministral 3 14B 2512 has a AA Agentic Index result, 1.1.
Directional only
Web design
Design Arena: websites
GPT-5.1-Codex-Mini
GPT-5.1-Codex-Mini leads, 1111 against 1081.
Same board, both measured
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
Ministral 3 14B 2512
GPT-5.1-Codex-Mini $0.0013, Ministral 3 14B 2512 $0.0003 per turn.
List prices
At a glance
- Coding index
- GPT-5.1-Codex-Mini not benchmarked, Ministral 3 14B 2512 not benchmarked.
- Widest category
- Intelligence, 14.4 points apart on average over 1 shared benchmark.
- Widest single gap
- AA Intelligence Index: GPT-5.1-Codex-Mini 20.4 against Ministral 3 14B 2512 6.0, 14.4 points apart on a 0 to 100 scale.
- Output price
- GPT-5.1-Codex-Mini $2.00 against Ministral 3 14B 2512 $0.20 per million output tokens, 10.0x apart.
- Context window
- GPT-5.1-Codex-Mini takes 400K tokens, Ministral 3 14B 2512 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 | Ministral 3 14B 2512 | Ties |
|---|---|---|---|---|
| Intelligence | 1 | 0 | ||
| Web design | 3 | 1 | ||
| All shared boards | 4 | 1 |
CodingDirectional onlySix of these boards feed the Vibe Coding Index6 boards, none shared
| Benchmark | GPT-5.1-Codex-Mini | Ministral 3 14B 2512 | Leader |
|---|---|---|---|
| LMArena WebDev | 1244 | Not measured | Only GPT-5.1-Codex-Mini measured |
| AA Coding Index | Not measured | 14.4 | Only Ministral 3 14B 2512 measured |
| LiveCodeBench (Artificial Analysis run) | 83.6% | Not measured | Only GPT-5.1-Codex-Mini measured |
| Terminal-Bench Hard (Artificial Analysis run) | 33.3% | Not measured | Only GPT-5.1-Codex-Mini measured |
| Terminal-Bench | 61.6% | Not measured | Only GPT-5.1-Codex-Mini measured |
| LMArena WebDev: HTML | 1253 | Not measured | Only GPT-5.1-Codex-Mini measured |
| Neither model has a result on the other 37 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | GPT-5.1-Codex-Mini | Ministral 3 14B 2512 | Leader |
|---|---|---|---|
| AA Intelligence Index | 20.4 | 6.0 | GPT-5.1-Codex-Mini |
| Neither model has a result on the other 1 board here | |||
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index2 boards, none shared
| Benchmark | GPT-5.1-Codex-Mini | Ministral 3 14B 2512 | Leader |
|---|---|---|---|
| AA Agentic Index | Not measured | 1.1 | Only Ministral 3 14B 2512 measured |
| τ²-Bench Telecom | 62.9% | Not measured | Only GPT-5.1-Codex-Mini measured |
| Neither model has a result on the other 40 boards here | |||
ReasoningDirectional onlyPublic boards, shown as published, kept out of the index2 boards, none shared
| Benchmark | GPT-5.1-Codex-Mini | Ministral 3 14B 2512 | Leader |
|---|---|---|---|
| GPQA Diamond (Artificial Analysis run) | 81.3% | Not measured | Only GPT-5.1-Codex-Mini measured |
| Humanity's Last Exam (Artificial Analysis run) | 18.5% | Not measured | Only GPT-5.1-Codex-Mini measured |
| Neither model has a result on the other 21 boards here | |||
MathDirectional onlyPublic boards, shown as published, kept out of the index2 boards, none shared
| Benchmark | GPT-5.1-Codex-Mini | Ministral 3 14B 2512 | 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 12 boards here | |||
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index1 board, none shared
| Benchmark | GPT-5.1-Codex-Mini | Ministral 3 14B 2512 | 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 19 boards here | |||
Web designLike-for-likePublic boards, shown as published, kept out of the index31
| Benchmark | GPT-5.1-Codex-Mini | Ministral 3 14B 2512 | Leader |
|---|---|---|---|
| Design Arena: websites | 1111 | 1081 | GPT-5.1-Codex-Mini |
| Design Arena: UI components | 1078 | Not measured | Only GPT-5.1-Codex-Mini measured |
| Design Arena: game dev | 1092 | 1037 | GPT-5.1-Codex-Mini |
| Design Arena: data viz | 1097 | Not measured | Only GPT-5.1-Codex-Mini measured |
| Design Arena: 3D | 989 | 991 | Ministral 3 14B 2512 |
| Design Arena: all code categories | 1093 | 1064 | GPT-5.1-Codex-Mini |
| Design Arena: SVG | 977 | Not measured | Only GPT-5.1-Codex-Mini measured |
| Design Arena: ASCII art | 1105 | Not measured | Only GPT-5.1-Codex-Mini measured |
| Neither model has a result on the other 1 board here | |||
GeneralDirectional onlyPublic boards, shown as published, kept out of the index2 boards, none shared
| Benchmark | GPT-5.1-Codex-Mini | Ministral 3 14B 2512 | Leader |
|---|---|---|---|
| IFBench | 67.9% | Not measured | Only GPT-5.1-Codex-Mini measured |
| Long context reasoning (AA-LCR) | 66.7% | Not measured | Only GPT-5.1-Codex-Mini measured |
| Neither model has a result on the other 46 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | GPT-5.1-Codex-Mini | Ministral 3 14B 2512 | 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
Ministral 3 14B 2512 costs less
Repository review
50K input + 3K output tokens
Ministral 3 14B 2512 costs less
Agent loop
200K input + 10K output tokens
Ministral 3 14B 2512 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 | Mistral Ministral 3 14B 2512 |
|---|---|---|
| Maker | OpenAI | Mistral AI |
| Weights | No public weights listed | Open weights |
| Released | November 13, 2025 | December 2, 2025 |
| Context window | 400K | 262K |
| Input $/Mtok | $0.25 | $0.20 |
| Output $/Mtok | $2.00 | $0.20 |
| 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 Ministral 3 14B 2512 for coding?
Neither model has a coding score yet, so the two cannot be ranked on coding. Pick GPT-5.1-Codex-Mini for a larger context window (400K against 262K tokens) and work measured by Design Arena: 3D, where it leads.
Which is cheaper, GPT-5.1-Codex-Mini or Ministral 3 14B 2512?
GPT-5.1-Codex-Mini costs $0.25 per million input tokens and $2.00 per million output tokens; Ministral 3 14B 2512 costs $0.20 and $0.20. Cost per solved task is known for neither of them.
Which has the bigger context window, GPT-5.1-Codex-Mini or Ministral 3 14B 2512?
GPT-5.1-Codex-Mini, with 400K tokens against 262K.
How many benchmarks is the GPT-5.1-Codex-Mini vs Ministral 3 14B 2512 comparison based on?
5 benchmarks have a result for both models as of October 23, 2026. GPT-5.1-Codex-Mini's coding index rests on 1 independent benchmark and Ministral 3 14B 2512's on 0. Where only one model has a result, the page says so instead of naming a winner.