Ministral 3 14B 2512 vs Qwen3.5-122B-A10B
Qwen3.5-122B-A10B leads Ministral 3 14B 2512 on the Artificial Analysis Intelligence Index, 17.7 to 6.0, and Ministral 3 14B 2512 costs 10.4x less per output token ($0.20 vs $2.08 per million). Updated October 23, 2026; 2 benchmarks have a result for both.
Ministral 3 14B 2512 or Qwen3.5-122B-A10B: which to pick
Neither model has a coding score yet, so the two cannot be ranked on coding.
Pick Ministral 3 14B 2512 for output tokens 10.4x cheaper ($0.20 vs $2.08 per million) and work measured by AA Coding Index or AA Intelligence Index, where it leads.
- Shared results
- 2
- Ministral 3 14B 2512 only
- 5
- Qwen3.5-122B-A10B only
- 49
- 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
Qwen3.5-122B-A10B
Qwen3.5-122B-A10B leads, 17.7 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
No call
Only Ministral 3 14B 2512 has a Design Arena: websites result, 1081.
Directional only
Long documents
Listed context window
No call
Both take 262K tokens.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Ministral 3 14B 2512
Ministral 3 14B 2512 $0.0003, Qwen3.5-122B-A10B $0.0013 per turn.
List prices
At a glance
- Coding index
- Ministral 3 14B 2512 not benchmarked, Qwen3.5-122B-A10B not benchmarked.
- Widest category
- Coding, 28.9 points apart on average over 1 shared benchmark.
- Widest single gap
- AA Coding Index: Ministral 3 14B 2512 14.4 against Qwen3.5-122B-A10B 43.3, 28.9 points apart on a 0 to 100 scale.
- Output price
- Ministral 3 14B 2512 $0.20 against Qwen3.5-122B-A10B $2.08 per million output tokens, 10.4x apart.
- Context window
- Both take 262K tokens.
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 | Ministral 3 14B 2512 | Bars | Qwen3.5-122B-A10B | Ties |
|---|---|---|---|---|
| Coding | 0 | 1 | ||
| Intelligence | 0 | 1 | ||
| All shared boards | 0 | 2 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index01
| Benchmark | Ministral 3 14B 2512 | Qwen3.5-122B-A10B | Leader |
|---|---|---|---|
| LMArena WebDev | Not measured | 1361 | Only Qwen3.5-122B-A10B measured |
| AA Coding Index | 14.4 | 43.3 | Qwen3.5-122B-A10B |
| SciCode | Not measured | 39.7% | Only Qwen3.5-122B-A10B measured |
| Terminal-Bench Hard (Artificial Analysis run) | Not measured | 31.1% | Only Qwen3.5-122B-A10B measured |
| LMArena Text: coding | Not measured | 1436 | Only Qwen3.5-122B-A10B measured |
| LMArena Text: software and IT | Not measured | 1436 | Only Qwen3.5-122B-A10B measured |
| LMArena WebDev: React | Not measured | 1352 | Only Qwen3.5-122B-A10B measured |
| LMArena WebDev: HTML | Not measured | 1352 | Only Qwen3.5-122B-A10B measured |
| Neither model has a result on the other 35 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | Ministral 3 14B 2512 | Qwen3.5-122B-A10B | Leader |
|---|---|---|---|
| AA Intelligence Index | 6.0 | 17.7 | Qwen3.5-122B-A10B |
| 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 | Ministral 3 14B 2512 | Qwen3.5-122B-A10B | Leader |
|---|---|---|---|
| AA Agentic Index | 1.1 | Not measured | Only Ministral 3 14B 2512 measured |
| τ²-Bench Telecom | Not measured | 93.6% | Only Qwen3.5-122B-A10B measured |
| Neither model has a result on the other 40 boards here | |||
ReasoningDirectional onlyPublic boards, shown as published, kept out of the index8 boards, none shared
| Benchmark | Ministral 3 14B 2512 | Qwen3.5-122B-A10B | Leader |
|---|---|---|---|
| GPQA Diamond (Artificial Analysis run) | Not measured | 85.7% | Only Qwen3.5-122B-A10B measured |
| Humanity's Last Exam (Artificial Analysis run) | Not measured | 25.2% | Only Qwen3.5-122B-A10B measured |
| Mystery game puzzles | Not measured | 17.0% | Only Qwen3.5-122B-A10B measured |
| LMArena Text: hard prompts | Not measured | 1421 | Only Qwen3.5-122B-A10B measured |
| LMArena Text: expert | Not measured | 1431 | Only Qwen3.5-122B-A10B measured |
| LMArena Text: hard prompts in English | Not measured | 1431 | Only Qwen3.5-122B-A10B measured |
| LMArena Vision: diagrams | Not measured | 1249 | Only Qwen3.5-122B-A10B measured |
| LMArena Vision: homework | Not measured | 1261 | Only Qwen3.5-122B-A10B 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 | Ministral 3 14B 2512 | Qwen3.5-122B-A10B | Leader |
|---|---|---|---|
| LMArena Text: math | Not measured | 1431 | Only Qwen3.5-122B-A10B measured |
| LMArena Text: mathematical work | Not measured | 1431 | Only Qwen3.5-122B-A10B measured |
| Neither model has a result on the other 12 boards here | |||
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index4 boards, none shared
| Benchmark | Ministral 3 14B 2512 | Qwen3.5-122B-A10B | Leader |
|---|---|---|---|
| LMArena Text: science | Not measured | 1433 | Only Qwen3.5-122B-A10B measured |
| LMArena Text: medicine and healthcare | Not measured | 1423 | Only Qwen3.5-122B-A10B measured |
| LMArena Text: legal and government | Not measured | 1422 | Only Qwen3.5-122B-A10B measured |
| LMArena Text: business and finance | Not measured | 1414 | Only Qwen3.5-122B-A10B measured |
| Neither model has a result on the other 16 boards here | |||
Web designDirectional onlyPublic boards, shown as published, kept out of the index4 boards, none shared
| Benchmark | Ministral 3 14B 2512 | Qwen3.5-122B-A10B | Leader |
|---|---|---|---|
| Design Arena: websites | 1081 | Not measured | Only Ministral 3 14B 2512 measured |
| Design Arena: game dev | 1037 | Not measured | Only Ministral 3 14B 2512 measured |
| Design Arena: 3D | 991 | Not measured | Only Ministral 3 14B 2512 measured |
| Design Arena: all code categories | 1064 | Not measured | Only Ministral 3 14B 2512 measured |
| Neither model has a result on the other 5 boards here | |||
GeneralDirectional onlyPublic boards, shown as published, kept out of the index27 boards, none shared
| Benchmark | Ministral 3 14B 2512 | Qwen3.5-122B-A10B | Leader |
|---|---|---|---|
| IFBench | Not measured | 75.7% | Only Qwen3.5-122B-A10B measured |
| Long context reasoning (AA-LCR) | Not measured | 76.3% | Only Qwen3.5-122B-A10B measured |
| DTBench | Not measured | 84.3% | Only Qwen3.5-122B-A10B measured |
| LMCA | Not measured | 32.2% | Only Qwen3.5-122B-A10B measured |
| LMArena Text | Not measured | 1418 | Only Qwen3.5-122B-A10B measured |
| LMArena Text: instruction following | Not measured | 1400 | Only Qwen3.5-122B-A10B measured |
| LMArena Text: creative writing | Not measured | 1368 | Only Qwen3.5-122B-A10B measured |
| LMArena Vision | Not measured | 1244 | Only Qwen3.5-122B-A10B measured |
| LMArena Text: English | Not measured | 1428 | Only Qwen3.5-122B-A10B measured |
| LMArena Text: non-English | Not measured | 1401 | Only Qwen3.5-122B-A10B measured |
| LMArena Text: Chinese | Not measured | 1463 | Only Qwen3.5-122B-A10B measured |
| LMArena Text: German | Not measured | 1425 | Only Qwen3.5-122B-A10B measured |
| LMArena Text: Japanese | Not measured | 1367 | Only Qwen3.5-122B-A10B measured |
| LMArena Text: Korean | Not measured | 1353 | Only Qwen3.5-122B-A10B measured |
| LMArena Text: French | Not measured | 1443 | Only Qwen3.5-122B-A10B measured |
| LMArena Text: Spanish | Not measured | 1425 | Only Qwen3.5-122B-A10B measured |
| LMArena Text: Russian | Not measured | 1400 | Only Qwen3.5-122B-A10B measured |
| LMArena Text: Polish | Not measured | 1399 | Only Qwen3.5-122B-A10B measured |
| LMArena Text: multi-turn | Not measured | 1417 | Only Qwen3.5-122B-A10B measured |
| LMArena Text: longer queries | Not measured | 1411 | Only Qwen3.5-122B-A10B measured |
| LMArena Text: writing and language | Not measured | 1387 | Only Qwen3.5-122B-A10B measured |
| LMArena Text: entertainment and media | Not measured | 1366 | Only Qwen3.5-122B-A10B measured |
| LMArena Vision: English | Not measured | 1249 | Only Qwen3.5-122B-A10B measured |
| LMArena Vision: Chinese | Not measured | 1301 | Only Qwen3.5-122B-A10B measured |
| LMArena Vision: reading text | Not measured | 1251 | Only Qwen3.5-122B-A10B measured |
| LMArena Vision: humor | Not measured | 1243 | Only Qwen3.5-122B-A10B measured |
| LMArena Vision: creative writing | Not measured | 1220 | Only Qwen3.5-122B-A10B measured |
| Neither model has a result on the other 21 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | Ministral 3 14B 2512 | Qwen3.5-122B-A10B | 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 | Mistral Ministral 3 14B 2512 | Qwen3.5-122B-A10B |
|---|---|---|
| Maker | Mistral AI | Qwen |
| Weights | Open weights | Open weights |
| Released | December 2, 2025 | February 25, 2026 |
| Context window | 262K | 262K |
| Input $/Mtok | $0.20 | $0.26 |
| Output $/Mtok | $0.20 | $2.08 |
| Coding index | Not benchmarked | Not benchmarked |
| Independent measurements behind it | 0 | 1 |
| Cost per solved task | Not computable | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is Ministral 3 14B 2512 better than Qwen3.5-122B-A10B for coding?
Neither model has a coding score yet, so the two cannot be ranked on coding. Pick Ministral 3 14B 2512 for output tokens 10.4x cheaper ($0.20 vs $2.08 per million) and work measured by AA Coding Index or AA Intelligence Index, where it leads.
Which is cheaper, Ministral 3 14B 2512 or Qwen3.5-122B-A10B?
Ministral 3 14B 2512 costs $0.20 per million input tokens and $0.20 per million output tokens; Qwen3.5-122B-A10B costs $0.26 and $2.08. Cost per solved task is known for neither of them.
Which has the bigger context window, Ministral 3 14B 2512 or Qwen3.5-122B-A10B?
Neither: both take 262K tokens.
How many benchmarks is the Ministral 3 14B 2512 vs Qwen3.5-122B-A10B comparison based on?
2 benchmarks have a result for both models as of October 23, 2026. Ministral 3 14B 2512's coding index rests on 0 independent benchmarks and Qwen3.5-122B-A10B's on 1. Where only one model has a result, the page says so instead of naming a winner.