GLM 4.5 Air vs Ministral 3 3B 2512
GLM 4.5 Air leads Ministral 3 3B 2512 on the Artificial Analysis Intelligence Index, 11.1 to 4.8, and Ministral 3 3B 2512 costs 11.0x less per output token ($0.10 vs $1.10 per million). Updated October 23, 2026; 5 benchmarks have a result for both.
GLM 4.5 Air or Ministral 3 3B 2512: which to pick
Neither model has a coding score yet, so the two cannot be ranked on coding.
Compare them on price, context and the boards below.
- Shared results
- 5
- GLM 4.5 Air only
- 44
- Ministral 3 3B 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
GLM 4.5 Air
GLM 4.5 Air leads, 11.1 against 4.8.
Same board, both measured
Agentic work
AA Agentic Index
No call
Only Ministral 3 3B 2512 has a AA Agentic Index result, 0.8.
Directional only
Web design
Design Arena: websites
GLM 4.5 Air
GLM 4.5 Air leads, 1146 against 1027.
Same board, both measured
Long documents
Listed context window
No call
Both take 131K tokens.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Ministral 3 3B 2512
GLM 4.5 Air $0.0008, Ministral 3 3B 2512 $0.0001 per turn.
List prices
At a glance
- Coding index
- GLM 4.5 Air not benchmarked, Ministral 3 3B 2512 not benchmarked.
- Widest category
- Web design, 17.3 points apart on average over 4 shared benchmarks.
- Widest single gap
- Design Arena: 3D: GLM 4.5 Air 1123 against Ministral 3 3B 2512 963, 20.0 points apart on a 0 to 100 scale.
- Output price
- GLM 4.5 Air $1.10 against Ministral 3 3B 2512 $0.10 per million output tokens, 11.0x apart.
- Context window
- Both take 131K 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 | GLM 4.5 Air | Bars | Ministral 3 3B 2512 | Ties |
|---|---|---|---|---|
| Intelligence | 1 | 0 | ||
| Web design | 4 | 0 | ||
| All shared boards | 5 | 0 |
CodingDirectional onlySix of these boards feed the Vibe Coding Index6 boards, none shared
| Benchmark | GLM 4.5 Air | Ministral 3 3B 2512 | Leader |
|---|---|---|---|
| AA Coding Index | Not measured | 4.8 | Only Ministral 3 3B 2512 measured |
| LiveCodeBench (Artificial Analysis run) | 68.4% | Not measured | Only GLM 4.5 Air measured |
| Terminal-Bench Hard (Artificial Analysis run) | 20.5% | Not measured | Only GLM 4.5 Air measured |
| GSO-Bench | 2.9% | Not measured | Only GLM 4.5 Air measured |
| LMArena Text: coding | 1397 | Not measured | Only GLM 4.5 Air measured |
| LMArena Text: software and IT | 1401 | Not measured | Only GLM 4.5 Air 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 | GLM 4.5 Air | Ministral 3 3B 2512 | Leader |
|---|---|---|---|
| AA Intelligence Index | 11.1 | 4.8 | GLM 4.5 Air |
| 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 | GLM 4.5 Air | Ministral 3 3B 2512 | Leader |
|---|---|---|---|
| AA Agentic Index | Not measured | 0.8 | Only Ministral 3 3B 2512 measured |
| τ²-Bench Telecom | 46.5% | Not measured | Only GLM 4.5 Air measured |
| Neither model has a result on the other 40 boards here | |||
ReasoningDirectional onlyPublic boards, shown as published, kept out of the index6 boards, none shared
| Benchmark | GLM 4.5 Air | Ministral 3 3B 2512 | Leader |
|---|---|---|---|
| GPQA Diamond (Artificial Analysis run) | 73.3% | Not measured | Only GLM 4.5 Air measured |
| Humanity's Last Exam (Artificial Analysis run) | 7.0% | Not measured | Only GLM 4.5 Air measured |
| LMArena Text: hard prompts | 1379 | Not measured | Only GLM 4.5 Air measured |
| LMArena Text: expert | 1370 | Not measured | Only GLM 4.5 Air measured |
| LMArena Text: hard prompts in English | 1388 | Not measured | Only GLM 4.5 Air measured |
| Kagi LLM Benchmark | 43.0% | Not measured | Only GLM 4.5 Air measured |
| Neither model has a result on the other 17 boards here | |||
MathDirectional onlyPublic boards, shown as published, kept out of the index5 boards, none shared
| Benchmark | GLM 4.5 Air | Ministral 3 3B 2512 | Leader |
|---|---|---|---|
| AA Math Index | 80.7 | Not measured | Only GLM 4.5 Air measured |
| AIME 2025 (Artificial Analysis run) | 80.7% | Not measured | Only GLM 4.5 Air measured |
| LMArena Text: math | 1396 | Not measured | Only GLM 4.5 Air measured |
| LMArena Text: mathematical work | 1396 | Not measured | Only GLM 4.5 Air measured |
| MathArena | 12.0% | Not measured | Only GLM 4.5 Air measured |
| Neither model has a result on the other 9 boards here | |||
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index5 boards, none shared
| Benchmark | GLM 4.5 Air | Ministral 3 3B 2512 | Leader |
|---|---|---|---|
| MMLU Pro (Artificial Analysis run) | 81.5% | Not measured | Only GLM 4.5 Air measured |
| LMArena Text: science | 1407 | Not measured | Only GLM 4.5 Air measured |
| LMArena Text: medicine and healthcare | 1401 | Not measured | Only GLM 4.5 Air measured |
| LMArena Text: legal and government | 1382 | Not measured | Only GLM 4.5 Air measured |
| LMArena Text: business and finance | 1370 | Not measured | Only GLM 4.5 Air measured |
| Neither model has a result on the other 15 boards here | |||
Web designLike-for-likePublic boards, shown as published, kept out of the index40
| Benchmark | GLM 4.5 Air | Ministral 3 3B 2512 | Leader |
|---|---|---|---|
| Design Arena: websites | 1146 | 1027 | GLM 4.5 Air |
| Design Arena: UI components | 1121 | Not measured | Only GLM 4.5 Air measured |
| Design Arena: game dev | 1094 | 948 | GLM 4.5 Air |
| Design Arena: data viz | 1187 | Not measured | Only GLM 4.5 Air measured |
| Design Arena: 3D | 1123 | 963 | GLM 4.5 Air |
| Design Arena: all code categories | 1137 | 1009 | GLM 4.5 Air |
| Design Arena: SVG | 1071 | Not measured | Only GLM 4.5 Air measured |
| Neither model has a result on the other 2 boards here | |||
GeneralDirectional onlyPublic boards, shown as published, kept out of the index19 boards, none shared
| Benchmark | GLM 4.5 Air | Ministral 3 3B 2512 | Leader |
|---|---|---|---|
| IFBench | 37.6% | Not measured | Only GLM 4.5 Air measured |
| Long context reasoning (AA-LCR) | 46.7% | Not measured | Only GLM 4.5 Air measured |
| LMArena Text | 1384 | Not measured | Only GLM 4.5 Air measured |
| LMArena Text: instruction following | 1354 | Not measured | Only GLM 4.5 Air measured |
| LMArena Text: creative writing | 1343 | Not measured | Only GLM 4.5 Air measured |
| LMArena Text: English | 1397 | Not measured | Only GLM 4.5 Air measured |
| LMArena Text: non-English | 1366 | Not measured | Only GLM 4.5 Air measured |
| LMArena Text: Chinese | 1426 | Not measured | Only GLM 4.5 Air measured |
| LMArena Text: German | 1377 | Not measured | Only GLM 4.5 Air measured |
| LMArena Text: Japanese | 1348 | Not measured | Only GLM 4.5 Air measured |
| LMArena Text: Korean | 1308 | Not measured | Only GLM 4.5 Air measured |
| LMArena Text: French | 1399 | Not measured | Only GLM 4.5 Air measured |
| LMArena Text: Spanish | 1386 | Not measured | Only GLM 4.5 Air measured |
| LMArena Text: Russian | 1373 | Not measured | Only GLM 4.5 Air measured |
| LMArena Text: Polish | 1368 | Not measured | Only GLM 4.5 Air measured |
| LMArena Text: multi-turn | 1371 | Not measured | Only GLM 4.5 Air measured |
| LMArena Text: longer queries | 1366 | Not measured | Only GLM 4.5 Air measured |
| LMArena Text: writing and language | 1354 | Not measured | Only GLM 4.5 Air measured |
| LMArena Text: entertainment and media | 1340 | Not measured | Only GLM 4.5 Air measured |
| Neither model has a result on the other 29 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | GLM 4.5 Air | Ministral 3 3B 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 3B 2512 costs less
Repository review
50K input + 3K output tokens
Ministral 3 3B 2512 costs less
Agent loop
200K input + 10K output tokens
Ministral 3 3B 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 | Z.ai GLM 4.5 Air | Mistral Ministral 3 3B 2512 |
|---|---|---|
| Maker | Z.ai | Mistral AI |
| Weights | Open weights | Open weights |
| Released | July 25, 2025 | December 2, 2025 |
| Context window | 131K | 131K |
| Input $/Mtok | $0.20 | $0.10 |
| Output $/Mtok | $1.10 | $0.10 |
| Coding index | Not benchmarked | Not benchmarked |
| Independent measurements behind it | 0 | 0 |
| Cost per solved task | Not computable | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is GLM 4.5 Air better than Ministral 3 3B 2512 for coding?
Neither model has a coding score yet, so the two cannot be ranked on coding. Compare them on price, context and the boards below.
Which is cheaper, GLM 4.5 Air or Ministral 3 3B 2512?
GLM 4.5 Air costs $0.20 per million input tokens and $1.10 per million output tokens; Ministral 3 3B 2512 costs $0.10 and $0.10. Cost per solved task is known for neither of them.
Which has the bigger context window, GLM 4.5 Air or Ministral 3 3B 2512?
Neither: both take 131K tokens.
How many benchmarks is the GLM 4.5 Air vs Ministral 3 3B 2512 comparison based on?
5 benchmarks have a result for both models as of October 23, 2026. GLM 4.5 Air's coding index rests on 0 independent benchmarks and Ministral 3 3B 2512's on 0. Where only one model has a result, the page says so instead of naming a winner.