Nova Pro 1.0 vs GLM 5 Turbo
GLM 5 Turbo leads Nova Pro 1.0 on the Artificial Analysis Intelligence Index, 26.6 to 7.0, and Nova Pro 1.0 costs 1.3x less per output token ($3.20 vs $4.00 per million). Updated October 21, 2026; 8 benchmarks have a result for both.
Nova Pro 1.0 or GLM 5 Turbo: which to pick
Neither model has a coding score yet, so the two cannot be ranked on coding.
Pick Nova Pro 1.0 for output tokens 1.3x cheaper ($3.20 vs $4.00 per million) and a larger context window (300K against 203K tokens).
- Shared results
- 8
- Nova Pro 1.0 only
- 34
- GLM 5 Turbo only
- 8
- 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 5 Turbo
GLM 5 Turbo leads, 26.6 against 7.0.
Same board, both measured
Web design
Design Arena: websites
GLM 5 Turbo
GLM 5 Turbo leads, 1262 against 796.
Same board, both measured
Long documents
Listed context window
Nova Pro 1.0
Nova Pro 1.0 takes 300K tokens against 203K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Nova Pro 1.0
Nova Pro 1.0 $0.0024, GLM 5 Turbo $0.0032 per turn.
List prices
At a glance
- Coding index
- Nova Pro 1.0 not benchmarked, GLM 5 Turbo not benchmarked.
- Widest category
- Agentic work, 84.5 points apart on average over 1 shared benchmark.
- Widest single gap
- τ²-Bench Telecom: Nova Pro 1.0 14.0% against GLM 5 Turbo 98.5%, 84.5 points apart on a 0 to 100 scale.
- Output price
- Nova Pro 1.0 $3.20 against GLM 5 Turbo $4.00 per million output tokens, 1.3x apart.
- Context window
- Nova Pro 1.0 takes 300K tokens, GLM 5 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 Pro 1.0 | Bars | GLM 5 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 Pro 1.0 | GLM 5 Turbo | Leader |
|---|---|---|---|
| LiveCodeBench (Artificial Analysis run) | 23.3% | Not measured | Only Nova Pro 1.0 measured |
| Terminal-Bench Hard (Artificial Analysis run) | 6.1% | 33.3% | GLM 5 Turbo |
| ALE-Bench | Not measured | 634.0 | Only GLM 5 Turbo measured |
| LMArena Text: coding | 1270 | Not measured | Only Nova Pro 1.0 measured |
| LMArena Text: software and IT | 1271 | Not measured | Only Nova Pro 1.0 measured |
| Neither model has a result on the other 34 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | Nova Pro 1.0 | GLM 5 Turbo | Leader |
|---|---|---|---|
| AA Intelligence Index | 7.0 | 26.6 | GLM 5 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 Pro 1.0 | GLM 5 Turbo | Leader |
|---|---|---|---|
| τ²-Bench Telecom | 14.0% | 98.5% | GLM 5 Turbo |
| Neither model has a result on the other 40 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index02
| Benchmark | Nova Pro 1.0 | GLM 5 Turbo | Leader |
|---|---|---|---|
| GPQA Diamond (Artificial Analysis run) | 49.9% | 84.7% | GLM 5 Turbo |
| Humanity's Last Exam (Artificial Analysis run) | 3.2% | 27.8% | GLM 5 Turbo |
| LMArena Text: hard prompts | 1246 | Not measured | Only Nova Pro 1.0 measured |
| LMArena Text: expert | 1211 | Not measured | Only Nova Pro 1.0 measured |
| LMArena Text: hard prompts in English | 1259 | Not measured | Only Nova Pro 1.0 measured |
| Neither model has a result on the other 17 boards here | |||
MathDirectional onlyPublic boards, shown as published, kept out of the index4 boards, none shared
| Benchmark | Nova Pro 1.0 | GLM 5 Turbo | Leader |
|---|---|---|---|
| AA Math Index | 7.0 | Not measured | Only Nova Pro 1.0 measured |
| AIME 2025 (Artificial Analysis run) | 7.0% | Not measured | Only Nova Pro 1.0 measured |
| LMArena Text: math | 1252 | Not measured | Only Nova Pro 1.0 measured |
| LMArena Text: mathematical work | 1261 | Not measured | Only Nova Pro 1.0 measured |
| Neither model has a result on the other 9 boards here | |||
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index6 boards, none shared
| Benchmark | Nova Pro 1.0 | GLM 5 Turbo | Leader |
|---|---|---|---|
| MMLU Pro (Artificial Analysis run) | 69.1% | Not measured | Only Nova Pro 1.0 measured |
| MMLU | 82.0% | Not measured | Only Nova Pro 1.0 measured |
| LMArena Text: science | 1255 | Not measured | Only Nova Pro 1.0 measured |
| LMArena Text: medicine and healthcare | 1260 | Not measured | Only Nova Pro 1.0 measured |
| LMArena Text: legal and government | 1281 | Not measured | Only Nova Pro 1.0 measured |
| LMArena Text: business and finance | 1229 | Not measured | Only Nova Pro 1.0 measured |
| Neither model has a result on the other 12 boards here | |||
Web designLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | Nova Pro 1.0 | GLM 5 Turbo | Leader |
|---|---|---|---|
| Design Arena: websites | 796 | 1262 | GLM 5 Turbo |
| Design Arena: UI components | Not measured | 1263 | Only GLM 5 Turbo measured |
| Design Arena: game dev | Not measured | 1248 | Only GLM 5 Turbo measured |
| Design Arena: data viz | Not measured | 1264 | Only GLM 5 Turbo measured |
| Design Arena: 3D | Not measured | 1248 | Only GLM 5 Turbo measured |
| Design Arena: all code categories | Not measured | 1262 | Only GLM 5 Turbo measured |
| Design Arena: SVG | Not measured | 1206 | Only GLM 5 Turbo measured |
| Design Arena: ASCII art | Not measured | 1160 | Only GLM 5 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 Pro 1.0 | GLM 5 Turbo | Leader |
|---|---|---|---|
| IFBench | 38.1% | 73.2% | GLM 5 Turbo |
| Long context reasoning (AA-LCR) | 21.0% | 71.7% | GLM 5 Turbo |
| LMArena Text | 1259 | Not measured | Only Nova Pro 1.0 measured |
| LMArena Text: instruction following | 1235 | Not measured | Only Nova Pro 1.0 measured |
| LMArena Text: creative writing | 1212 | Not measured | Only Nova Pro 1.0 measured |
| LMArena Vision | 980 | Not measured | Only Nova Pro 1.0 measured |
| LMArena Text: English | 1276 | Not measured | Only Nova Pro 1.0 measured |
| LMArena Text: non-English | 1233 | Not measured | Only Nova Pro 1.0 measured |
| LMArena Text: Chinese | 1244 | Not measured | Only Nova Pro 1.0 measured |
| LMArena Text: German | 1243 | Not measured | Only Nova Pro 1.0 measured |
| LMArena Text: Japanese | 1200 | Not measured | Only Nova Pro 1.0 measured |
| LMArena Text: Korean | 1203 | Not measured | Only Nova Pro 1.0 measured |
| LMArena Text: French | 1271 | Not measured | Only Nova Pro 1.0 measured |
| LMArena Text: Spanish | 1182 | Not measured | Only Nova Pro 1.0 measured |
| LMArena Text: Russian | 1240 | Not measured | Only Nova Pro 1.0 measured |
| LMArena Text: multi-turn | 1246 | Not measured | Only Nova Pro 1.0 measured |
| LMArena Text: longer queries | 1255 | Not measured | Only Nova Pro 1.0 measured |
| LMArena Text: writing and language | 1247 | Not measured | Only Nova Pro 1.0 measured |
| LMArena Text: entertainment and media | 1210 | Not measured | Only Nova Pro 1.0 measured |
| LMArena Vision: English | 987 | Not measured | Only Nova Pro 1.0 measured |
| Neither model has a result on the other 26 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | Nova Pro 1.0 | GLM 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
Nova Pro 1.0 costs less
Repository review
50K input + 3K output tokens
Nova Pro 1.0 costs less
Agent loop
200K input + 10K output tokens
Nova Pro 1.0 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 Pro 1.0 | Z.ai GLM 5 Turbo |
|---|---|---|
| Maker | Amazon | Z.ai |
| Weights | No public weights listed | No public weights listed |
| Released | December 5, 2024 | March 15, 2026 |
| Context window | 300K | 203K |
| Input $/Mtok | $0.80 | $1.20 |
| Output $/Mtok | $3.20 | $4.00 |
| 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 Nova Pro 1.0 better than GLM 5 Turbo for coding?
Neither model has a coding score yet, so the two cannot be ranked on coding. Pick Nova Pro 1.0 for output tokens 1.3x cheaper ($3.20 vs $4.00 per million) and a larger context window (300K against 203K tokens).
Which is cheaper, Nova Pro 1.0 or GLM 5 Turbo?
Nova Pro 1.0 costs $0.80 per million input tokens and $3.20 per million output tokens; GLM 5 Turbo costs $1.20 and $4.00. Cost per solved task is known for neither of them.
Which has the bigger context window, Nova Pro 1.0 or GLM 5 Turbo?
Nova Pro 1.0, with 300K tokens against 203K.
How many benchmarks is the Nova Pro 1.0 vs GLM 5 Turbo comparison based on?
8 benchmarks have a result for both models as of October 21, 2026. Nova Pro 1.0's coding index rests on 0 independent benchmarks and GLM 5 Turbo's on 0. Where only one model has a result, the page says so instead of naming a winner.