GLM 4.5 Air vs GPT-3.5 Turbo
GLM 4.5 Air leads GPT-3.5 Turbo on the Artificial Analysis Intelligence Index, 11.1 to 5.5, and GLM 4.5 Air costs 1.4x less per output token ($1.10 vs $1.50 per million). Updated October 22, 2026; 3 benchmarks have a result for both.
GLM 4.5 Air or GPT-3.5 Turbo: which to pick
Neither model has a coding score yet, so the two cannot be ranked on coding.
Pick GLM 4.5 Air for output tokens 1.4x cheaper ($1.10 vs $1.50 per million) and a larger context window (131K against 16K tokens).
- Shared results
- 3
- GLM 4.5 Air only
- 46
- GPT-3.5 Turbo only
- 10
- Like-for-like categories
- 3 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 5.5.
Same board, both measured
Reasoning
GPQA Diamond
No call
Only GPT-3.5 Turbo has a GPQA Diamond result, 30.6%.
Directional only
Web design
Design Arena: websites
No call
Only GLM 4.5 Air has a Design Arena: websites result, 1146.
Directional only
Long documents
Listed context window
GLM 4.5 Air
GLM 4.5 Air takes 131K tokens against 16K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
GLM 4.5 Air
GLM 4.5 Air $0.0008, GPT-3.5 Turbo $0.0013 per turn.
List prices
At a glance
- Coding index
- GLM 4.5 Air not benchmarked, GPT-3.5 Turbo not benchmarked.
- Widest category
- Reasoning, 43.6 points apart on average over 1 shared benchmark.
- Widest single gap
- GPQA Diamond (Artificial Analysis run): GLM 4.5 Air 73.3% against GPT-3.5 Turbo 29.7%, 43.6 points apart on a 0 to 100 scale.
- Output price
- GLM 4.5 Air $1.10 against GPT-3.5 Turbo $1.50 per million output tokens, 1.4x apart.
- Context window
- GLM 4.5 Air takes 131K tokens, GPT-3.5 Turbo 16K.
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 | GPT-3.5 Turbo | Ties |
|---|---|---|---|---|
| Intelligence | 1 | 0 | ||
| Reasoning | 1 | 0 | ||
| Knowledge | 1 | 0 | ||
| All shared boards | 3 | 0 |
CodingDirectional onlySix of these boards feed the Vibe Coding Index7 boards, none shared
| Benchmark | GLM 4.5 Air | GPT-3.5 Turbo | Leader |
|---|---|---|---|
| AA Coding Index | Not measured | 10.7 | Only GPT-3.5 Turbo 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 |
| SciCode | Not measured | 0.0% | Only GPT-3.5 Turbo measured |
| Neither model has a result on the other 36 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | GLM 4.5 Air | GPT-3.5 Turbo | Leader |
|---|---|---|---|
| AA Intelligence Index | 11.1 | 5.5 | 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 index1 board, none shared
| Benchmark | GLM 4.5 Air | GPT-3.5 Turbo | Leader |
|---|---|---|---|
| τ²-Bench Telecom | 46.5% | Not measured | Only GLM 4.5 Air measured |
| Neither model has a result on the other 41 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | GLM 4.5 Air | GPT-3.5 Turbo | Leader |
|---|---|---|---|
| GPQA Diamond | Not measured | 30.6% | Only GPT-3.5 Turbo measured |
| GPQA Diamond (Artificial Analysis run) | 73.3% | 29.7% | GLM 4.5 Air |
| Humanity's Last Exam (Artificial Analysis run) | 7.0% | Not measured | Only GLM 4.5 Air measured |
| BIG-Bench Hard | Not measured | 61.6% | Only GPT-3.5 Turbo 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 15 boards here | |||
MathDirectional onlyPublic boards, shown as published, kept out of the index6 boards, none shared
| Benchmark | GLM 4.5 Air | GPT-3.5 Turbo | 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 |
| GSM8K | Not measured | 57.8% | Only GPT-3.5 Turbo 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 8 boards here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | GLM 4.5 Air | GPT-3.5 Turbo | Leader |
|---|---|---|---|
| LegalBench (Vals AI) | Not measured | 64.4% | Only GPT-3.5 Turbo measured |
| MedQA (Vals AI) | Not measured | 58.5% | Only GPT-3.5 Turbo measured |
| MMLU Pro (Artificial Analysis run) | 81.5% | 46.2% | GLM 4.5 Air |
| MMLU | Not measured | 68.5% | Only GPT-3.5 Turbo measured |
| LMArena Text: science | 1407 | Not measured | Only GLM 4.5 Air measured |
| LMArena Text: medicine and healthcare | 1402 | 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 | 1371 | Not measured | Only GLM 4.5 Air measured |
| Neither model has a result on the other 12 boards here | |||
Web designDirectional onlyPublic boards, shown as published, kept out of the index7 boards, none shared
| Benchmark | GLM 4.5 Air | GPT-3.5 Turbo | Leader |
|---|---|---|---|
| Design Arena: websites | 1146 | Not measured | Only GLM 4.5 Air measured |
| Design Arena: UI components | 1121 | Not measured | Only GLM 4.5 Air measured |
| Design Arena: game dev | 1093 | Not measured | Only GLM 4.5 Air measured |
| Design Arena: data viz | 1186 | Not measured | Only GLM 4.5 Air measured |
| Design Arena: 3D | 1122 | Not measured | Only GLM 4.5 Air measured |
| Design Arena: all code categories | 1137 | Not measured | Only GLM 4.5 Air measured |
| Design Arena: SVG | 1070 | 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 index21 boards, none shared
| Benchmark | GLM 4.5 Air | GPT-3.5 Turbo | 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 |
| DTBench | Not measured | 48.5% | Only GPT-3.5 Turbo measured |
| LMCA | Not measured | 9.7% | Only GPT-3.5 Turbo 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 | 1400 | Not measured | Only GLM 4.5 Air measured |
| LMArena Text: Spanish | 1385 | 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 | 1339 | Not measured | Only GLM 4.5 Air measured |
| Neither model has a result on the other 27 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | GLM 4.5 Air | GPT-3.5 Turbo | 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
GLM 4.5 Air costs less
Repository review
50K input + 3K output tokens
GLM 4.5 Air costs less
Agent loop
200K input + 10K output tokens
GLM 4.5 Air 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 | OpenAI GPT-3.5 Turbo |
|---|---|---|
| Maker | Z.ai | OpenAI |
| Weights | Open weights | No public weights listed |
| Released | July 25, 2025 | May 28, 2023 |
| Context window | 131K | 16K |
| Input $/Mtok | $0.20 | $0.50 |
| Output $/Mtok | $1.10 | $1.50 |
| 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 GPT-3.5 Turbo for coding?
Neither model has a coding score yet, so the two cannot be ranked on coding. Pick GLM 4.5 Air for output tokens 1.4x cheaper ($1.10 vs $1.50 per million) and a larger context window (131K against 16K tokens).
Which is cheaper, GLM 4.5 Air or GPT-3.5 Turbo?
GLM 4.5 Air costs $0.20 per million input tokens and $1.10 per million output tokens; GPT-3.5 Turbo costs $0.50 and $1.50. Cost per solved task is known for neither of them.
Which has the bigger context window, GLM 4.5 Air or GPT-3.5 Turbo?
GLM 4.5 Air, with 131K tokens against 16K.
How many benchmarks is the GLM 4.5 Air vs GPT-3.5 Turbo comparison based on?
3 benchmarks have a result for both models as of October 22, 2026. GLM 4.5 Air's coding index rests on 0 independent benchmarks and GPT-3.5 Turbo's on 0. Where only one model has a result, the page says so instead of naming a winner.