GLM 5 Turbo vs Hy3
Hy3 costs 7.6x less per output token than GLM 5 Turbo ($0.528 vs $4.00 per million). Updated October 22, 2026; 12 benchmarks have a result for both.
GLM 5 Turbo or Hy3: which to pick
Neither model has a coding score yet, so the two cannot be ranked on coding.
Pick GLM 5 Turbo for work measured by ALE-Bench or GPQA Diamond (Artificial Analysis run), where it leads.
- Shared results
- 12
- GLM 5 Turbo only
- 4
- Hy3 only
- 32
- Like-for-like categories
- 4 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
No call
Only GLM 5 Turbo has a AA Intelligence Index result, 26.6.
Directional only
Web design
Design Arena: websites
GLM 5 Turbo
GLM 5 Turbo leads, 1262 against 1230.
Same board, both measured
Long documents
Listed context window
Hy3
Hy3 takes 262K tokens against 203K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Hy3
GLM 5 Turbo $0.0032, Hy3 $0.0004 per turn.
List prices
At a glance
- Coding index
- GLM 5 Turbo not benchmarked, Hy3 not benchmarked.
- Widest category
- General, 7.3 points apart on average over 1 shared benchmark.
- Widest single gap
- Design Arena: data viz: GLM 5 Turbo 1264 against Hy3 1164, 12.5 points apart on a 0 to 100 scale.
- Output price
- GLM 5 Turbo $4.00 against Hy3 $0.528 per million output tokens, 7.6x apart.
- Context window
- GLM 5 Turbo takes 203K tokens, Hy3 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 | GLM 5 Turbo | Bars | Hy3 | Ties |
|---|---|---|---|---|
| Coding | 0 | 1 | ||
| Reasoning | 0 | 2 | ||
| Web design | 8 | 0 | ||
| General | 0 | 1 | ||
| All shared boards | 8 | 4 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index01
| Benchmark | GLM 5 Turbo | Hy3 | Leader |
|---|---|---|---|
| LMArena WebDev | Not measured | 1507 | Only Hy3 measured |
| SciCode | Not measured | 48.6% | Only Hy3 measured |
| Terminal-Bench Hard (Artificial Analysis run) | 33.3% | Not measured | Only GLM 5 Turbo measured |
| ALE-Bench | 634.0 | 838.6 | Hy3 |
| LMArena Text: coding | Not measured | 1466 | Only Hy3 measured |
| LMArena Text: software and IT | Not measured | 1463 | Only Hy3 measured |
| LMArena WebDev: React | Not measured | 1511 | Only Hy3 measured |
| LMArena WebDev: HTML | Not measured | 1487 | Only Hy3 measured |
| Neither model has a result on the other 31 boards here | |||
IntelligenceDirectional onlyPublic boards, shown as published, kept out of the index1 board, none shared
| Benchmark | GLM 5 Turbo | Hy3 | Leader |
|---|---|---|---|
| AA Intelligence Index | 26.6 | Not measured | Only GLM 5 Turbo measured |
| 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 5 Turbo | Hy3 | Leader |
|---|---|---|---|
| τ²-Bench Telecom | 98.5% | Not measured | Only GLM 5 Turbo measured |
| Neither model has a result on the other 40 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index02
| Benchmark | GLM 5 Turbo | Hy3 | Leader |
|---|---|---|---|
| GPQA Diamond (Artificial Analysis run) | 84.7% | 89.7% | Hy3 |
| Humanity's Last Exam (Artificial Analysis run) | 27.8% | 33.5% | Hy3 |
| LMArena Text: hard prompts | Not measured | 1447 | Only Hy3 measured |
| LMArena Text: expert | Not measured | 1461 | Only Hy3 measured |
| LMArena Text: hard prompts in English | Not measured | 1455 | Only Hy3 measured |
| Neither model has a result on the other 17 boards here | |||
MathDirectional onlyPublic boards, shown as published, kept out of the index2 boards, none shared
| Benchmark | GLM 5 Turbo | Hy3 | Leader |
|---|---|---|---|
| LMArena Text: math | Not measured | 1473 | Only Hy3 measured |
| LMArena Text: mathematical work | Not measured | 1482 | Only Hy3 measured |
| Neither model has a result on the other 11 boards here | |||
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index4 boards, none shared
| Benchmark | GLM 5 Turbo | Hy3 | Leader |
|---|---|---|---|
| LMArena Text: science | Not measured | 1457 | Only Hy3 measured |
| LMArena Text: medicine and healthcare | Not measured | 1452 | Only Hy3 measured |
| LMArena Text: legal and government | Not measured | 1422 | Only Hy3 measured |
| LMArena Text: business and finance | Not measured | 1424 | Only Hy3 measured |
| Neither model has a result on the other 14 boards here | |||
Web designLike-for-likePublic boards, shown as published, kept out of the index80
| Benchmark | GLM 5 Turbo | Hy3 | Leader |
|---|---|---|---|
| Design Arena: websites | 1262 | 1230 | GLM 5 Turbo |
| Design Arena: UI components | 1260 | 1204 | GLM 5 Turbo |
| Design Arena: game dev | 1248 | 1208 | GLM 5 Turbo |
| Design Arena: data viz | 1264 | 1164 | GLM 5 Turbo |
| Design Arena: 3D | 1247 | 1232 | GLM 5 Turbo |
| Design Arena: all code categories | 1261 | 1227 | GLM 5 Turbo |
| Design Arena: SVG | 1205 | 1200 | GLM 5 Turbo |
| Design Arena: ASCII art | 1160 | 1152 | GLM 5 Turbo |
| Neither model has a result on the other 1 board here | |||
GeneralLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | GLM 5 Turbo | Hy3 | Leader |
|---|---|---|---|
| IFBench | 73.2% | Not measured | Only GLM 5 Turbo measured |
| Long context reasoning (AA-LCR) | 71.7% | 79.0% | Hy3 |
| LMArena Text | Not measured | 1438 | Only Hy3 measured |
| LMArena Text: instruction following | Not measured | 1426 | Only Hy3 measured |
| LMArena Text: creative writing | Not measured | 1403 | Only Hy3 measured |
| LMArena Text: English | Not measured | 1448 | Only Hy3 measured |
| LMArena Text: non-English | Not measured | 1426 | Only Hy3 measured |
| LMArena Text: Chinese | Not measured | 1485 | Only Hy3 measured |
| LMArena Text: German | Not measured | 1449 | Only Hy3 measured |
| LMArena Text: Japanese | Not measured | 1397 | Only Hy3 measured |
| LMArena Text: Korean | Not measured | 1396 | Only Hy3 measured |
| LMArena Text: French | Not measured | 1456 | Only Hy3 measured |
| LMArena Text: Spanish | Not measured | 1457 | Only Hy3 measured |
| LMArena Text: Russian | Not measured | 1432 | Only Hy3 measured |
| LMArena Text: Polish | Not measured | 1447 | Only Hy3 measured |
| LMArena Text: multi-turn | Not measured | 1436 | Only Hy3 measured |
| LMArena Text: longer queries | Not measured | 1442 | Only Hy3 measured |
| LMArena Text: writing and language | Not measured | 1414 | Only Hy3 measured |
| LMArena Text: entertainment and media | Not measured | 1400 | Only Hy3 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 5 Turbo | Hy3 | 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
Hy3 costs less
Repository review
50K input + 3K output tokens
Hy3 costs less
Agent loop
200K input + 10K output tokens
Hy3 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 5 Turbo | Tencent Hy3 |
|---|---|---|
| Maker | Z.ai | Tencent |
| Weights | No public weights listed | Open weights |
| Released | March 15, 2026 | July 6, 2026 |
| Context window | 203K | 262K |
| Input $/Mtok | $1.20 | $0.132 |
| Output $/Mtok | $4.00 | $0.528 |
| 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 GLM 5 Turbo better than Hy3 for coding?
Neither model has a coding score yet, so the two cannot be ranked on coding. Pick GLM 5 Turbo for work measured by ALE-Bench or GPQA Diamond (Artificial Analysis run), where it leads.
Which is cheaper, GLM 5 Turbo or Hy3?
GLM 5 Turbo costs $1.20 per million input tokens and $4.00 per million output tokens; Hy3 costs $0.132 and $0.528. Cost per solved task is known for neither of them.
Which has the bigger context window, GLM 5 Turbo or Hy3?
Hy3, with 262K tokens against 203K.
How many benchmarks is the GLM 5 Turbo vs Hy3 comparison based on?
12 benchmarks have a result for both models as of October 22, 2026. GLM 5 Turbo's coding index rests on 0 independent benchmarks and Hy3's on 1. Where only one model has a result, the page says so instead of naming a winner.