Nova Premier 1.0 vs GLM 5V Turbo
GLM 5V Turbo leads Nova Premier 1.0 on the Artificial Analysis Intelligence Index, 23.5 to 9.2, and GLM 5V Turbo costs 3.1x less per output token ($4.00 vs $12.50 per million). Updated October 22, 2026; 8 benchmarks have a result for both.
Nova Premier 1.0 or GLM 5V Turbo: which to pick
Neither model has a coding score yet, so the two cannot be ranked on coding.
Pick Nova Premier 1.0 for a larger context window (1M against 203K tokens) and work measured by Terminal-Bench Hard (Artificial Analysis run) or AA Intelligence Index, where it leads.
- Shared results
- 8
- Nova Premier 1.0 only
- 6
- GLM 5V Turbo only
- 57
- Like-for-like categories
- 6 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 5V Turbo
GLM 5V Turbo leads, 23.5 against 9.2.
Same board, both measured
Web design
Design Arena: websites
GLM 5V Turbo
GLM 5V Turbo leads, 1230 against 835.
Same board, both measured
Long documents
Listed context window
Nova Premier 1.0
Nova Premier 1.0 takes 1M tokens against 203K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
GLM 5V Turbo
Nova Premier 1.0 $0.0088, GLM 5V Turbo $0.0032 per turn.
List prices
At a glance
- Coding index
- Nova Premier 1.0 not benchmarked, GLM 5V Turbo not benchmarked.
- Widest category
- Agentic work, 60.2 points apart on average over 1 shared benchmark.
- Widest single gap
- τ²-Bench Telecom: Nova Premier 1.0 38.3% against GLM 5V Turbo 98.5%, 60.2 points apart on a 0 to 100 scale.
- Output price
- Nova Premier 1.0 $12.50 against GLM 5V Turbo $4.00 per million output tokens, 3.1x apart.
- Context window
- Nova Premier 1.0 takes 1M tokens, GLM 5V Turbo 203K.
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 | Nova Premier 1.0 | Bars | GLM 5V Turbo | Ties |
|---|---|---|---|---|
| Coding | 0 | 1 | ||
| Intelligence | 0 | 1 | ||
| Agentic work | 0 | 1 | ||
| Reasoning | 0 | 2 | ||
| Web design | 0 | 1 | ||
| General | 0 | 2 | ||
| All shared boards | 0 | 8 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index01
| Benchmark | Nova Premier 1.0 | GLM 5V Turbo | Leader |
|---|---|---|---|
| LMArena WebDev | Not measured | 1402 | Only GLM 5V Turbo measured |
| LiveCodeBench (Artificial Analysis run) | 31.7% | Not measured | Only Nova Premier 1.0 measured |
| Terminal-Bench Hard (Artificial Analysis run) | 6.8% | 32.6% | GLM 5V Turbo |
| ALE-Bench | 147.4 | Not measured | Only Nova Premier 1.0 measured |
| LMArena Text: coding | Not measured | 1466 | Only GLM 5V Turbo measured |
| LMArena Text: software and IT | Not measured | 1460 | Only GLM 5V Turbo measured |
| LMArena WebDev: React | Not measured | 1386 | Only GLM 5V Turbo measured |
| LMArena WebDev: HTML | Not measured | 1356 | Only GLM 5V Turbo measured |
| LMArena WebDev: from an image | Not measured | 1425 | Only GLM 5V Turbo measured |
| Neither model has a result on the other 30 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | Nova Premier 1.0 | GLM 5V Turbo | Leader |
|---|---|---|---|
| AA Intelligence Index | 9.2 | 23.5 | GLM 5V Turbo |
| Neither model has a result on the other 1 board here | |||
Agentic workLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | Nova Premier 1.0 | GLM 5V Turbo | Leader |
|---|---|---|---|
| Design Arena: agents building web apps | Not measured | 1124 | Only GLM 5V Turbo measured |
| Design Arena: agents building full-stack apps | Not measured | 1149 | Only GLM 5V Turbo measured |
| Design Arena: agents building mobile apps | Not measured | 1134 | Only GLM 5V Turbo measured |
| Design Arena: agents building Android apps | Not measured | 1267 | Only GLM 5V Turbo measured |
| Design Arena: agents building Godot games | Not measured | 957 | Only GLM 5V Turbo measured |
| Design Arena: agents building games | Not measured | 1102 | Only GLM 5V Turbo measured |
| Design Arena: HTML slides | Not measured | 1070 | Only GLM 5V Turbo measured |
| Design Arena: PowerPoint slides | Not measured | 1127 | Only GLM 5V Turbo measured |
| τ²-Bench Telecom | 38.3% | 98.5% | GLM 5V Turbo |
| Neither model has a result on the other 32 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index02
| Benchmark | Nova Premier 1.0 | GLM 5V Turbo | Leader |
|---|---|---|---|
| GPQA Diamond (Artificial Analysis run) | 56.9% | 80.9% | GLM 5V Turbo |
| Humanity's Last Exam (Artificial Analysis run) | 4.2% | 17.1% | GLM 5V Turbo |
| LMArena Text: hard prompts | Not measured | 1443 | Only GLM 5V Turbo measured |
| LMArena Text: expert | Not measured | 1453 | Only GLM 5V Turbo measured |
| LMArena Text: hard prompts in English | Not measured | 1456 | Only GLM 5V Turbo measured |
| LMArena Vision: diagrams | Not measured | 1286 | Only GLM 5V Turbo measured |
| LMArena Vision: homework | Not measured | 1273 | Only GLM 5V Turbo measured |
| Kagi LLM Benchmark | 44.8% | Not measured | Only Nova Premier 1.0 measured |
| Neither model has a result on the other 14 boards here | |||
MathDirectional onlyPublic boards, shown as published, kept out of the index4 boards, none shared
| Benchmark | Nova Premier 1.0 | GLM 5V Turbo | Leader |
|---|---|---|---|
| AA Math Index | 17.3 | Not measured | Only Nova Premier 1.0 measured |
| AIME 2025 (Artificial Analysis run) | 17.3% | Not measured | Only Nova Premier 1.0 measured |
| LMArena Text: math | Not measured | 1442 | Only GLM 5V Turbo measured |
| LMArena Text: mathematical work | Not measured | 1447 | Only GLM 5V Turbo 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 | Nova Premier 1.0 | GLM 5V Turbo | Leader |
|---|---|---|---|
| MMLU Pro (Artificial Analysis run) | 73.3% | Not measured | Only Nova Premier 1.0 measured |
| LMArena Text: science | Not measured | 1448 | Only GLM 5V Turbo measured |
| LMArena Text: medicine and healthcare | Not measured | 1433 | Only GLM 5V Turbo measured |
| LMArena Text: legal and government | Not measured | 1436 | Only GLM 5V Turbo measured |
| LMArena Text: business and finance | Not measured | 1435 | Only GLM 5V Turbo measured |
| Neither model has a result on the other 13 boards here | |||
Web designLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | Nova Premier 1.0 | GLM 5V Turbo | Leader |
|---|---|---|---|
| Design Arena: websites | 835 | 1230 | GLM 5V Turbo |
| Design Arena: UI components | Not measured | 1210 | Only GLM 5V Turbo measured |
| Design Arena: game dev | Not measured | 1218 | Only GLM 5V Turbo measured |
| Design Arena: data viz | Not measured | 1202 | Only GLM 5V Turbo measured |
| Design Arena: 3D | Not measured | 1208 | Only GLM 5V Turbo measured |
| Design Arena: all code categories | Not measured | 1228 | Only GLM 5V Turbo measured |
| Design Arena: SVG | Not measured | 1151 | Only GLM 5V Turbo measured |
| Design Arena: ASCII art | Not measured | 1117 | Only GLM 5V Turbo measured |
| Neither model has a result on the other 1 board here | |||
GeneralLike-for-likePublic boards, shown as published, kept out of the index02
| Benchmark | Nova Premier 1.0 | GLM 5V Turbo | Leader |
|---|---|---|---|
| IFBench | 36.2% | 61.1% | GLM 5V Turbo |
| Long context reasoning (AA-LCR) | 34.3% | 70.3% | GLM 5V Turbo |
| LMArena Text | Not measured | 1437 | Only GLM 5V Turbo measured |
| LMArena Text: instruction following | Not measured | 1423 | Only GLM 5V Turbo measured |
| LMArena Text: creative writing | Not measured | 1417 | Only GLM 5V Turbo measured |
| LMArena Vision | Not measured | 1264 | Only GLM 5V Turbo measured |
| LMArena Text: English | Not measured | 1454 | Only GLM 5V Turbo measured |
| LMArena Text: non-English | Not measured | 1420 | Only GLM 5V Turbo measured |
| LMArena Text: Chinese | Not measured | 1491 | Only GLM 5V Turbo measured |
| LMArena Text: German | Not measured | 1422 | Only GLM 5V Turbo measured |
| LMArena Text: Korean | Not measured | 1397 | Only GLM 5V Turbo measured |
| LMArena Text: French | Not measured | 1443 | Only GLM 5V Turbo measured |
| LMArena Text: Spanish | Not measured | 1452 | Only GLM 5V Turbo measured |
| LMArena Text: Russian | Not measured | 1432 | Only GLM 5V Turbo measured |
| LMArena Text: Polish | Not measured | 1432 | Only GLM 5V Turbo measured |
| LMArena Text: multi-turn | Not measured | 1431 | Only GLM 5V Turbo measured |
| LMArena Text: longer queries | Not measured | 1438 | Only GLM 5V Turbo measured |
| LMArena Text: writing and language | Not measured | 1420 | Only GLM 5V Turbo measured |
| LMArena Text: entertainment and media | Not measured | 1407 | Only GLM 5V Turbo measured |
| LMArena Vision: English | Not measured | 1274 | Only GLM 5V Turbo measured |
| LMArena Vision: Chinese | Not measured | 1329 | Only GLM 5V Turbo measured |
| LMArena Vision: reading text | Not measured | 1270 | Only GLM 5V Turbo measured |
| LMArena Vision: humor | Not measured | 1268 | Only GLM 5V Turbo measured |
| LMArena Vision: captioning | Not measured | 1264 | Only GLM 5V Turbo measured |
| LMArena Vision: recognizing things | Not measured | 1241 | Only GLM 5V Turbo measured |
| LMArena Vision: creative writing | Not measured | 1252 | Only GLM 5V Turbo measured |
| LMArena Document | Not measured | 1416 | Only GLM 5V Turbo measured |
| Neither model has a result on the other 19 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | Nova Premier 1.0 | GLM 5V 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 5V Turbo costs less
Repository review
50K input + 3K output tokens
GLM 5V Turbo costs less
Agent loop
200K input + 10K output tokens
GLM 5V Turbo 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 | Amazon Nova Premier 1.0 | Z.ai GLM 5V Turbo |
|---|---|---|
| Maker | Amazon | Z.ai |
| Weights | No public weights listed | No public weights listed |
| Released | October 31, 2025 | April 1, 2026 |
| Context window | 1M | 203K |
| Input $/Mtok | $2.50 | $1.20 |
| Output $/Mtok | $12.50 | $4.00 |
| 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 Nova Premier 1.0 better than GLM 5V Turbo for coding?
Neither model has a coding score yet, so the two cannot be ranked on coding. Pick Nova Premier 1.0 for a larger context window (1M against 203K tokens) and work measured by Terminal-Bench Hard (Artificial Analysis run) or AA Intelligence Index, where it leads.
Which is cheaper, Nova Premier 1.0 or GLM 5V Turbo?
Nova Premier 1.0 costs $2.50 per million input tokens and $12.50 per million output tokens; GLM 5V Turbo costs $1.20 and $4.00. Cost per solved task is known for neither of them.
Which has the bigger context window, Nova Premier 1.0 or GLM 5V Turbo?
Nova Premier 1.0, with 1M tokens against 203K.
How many benchmarks is the Nova Premier 1.0 vs GLM 5V Turbo comparison based on?
8 benchmarks have a result for both models as of October 22, 2026. Nova Premier 1.0's coding index rests on 0 independent benchmarks and GLM 5V Turbo's on 1. Where only one model has a result, the page says so instead of naming a winner.