GLM 5 Turbo vs Qwen3 Next 80B A3B Instruct
GLM 5 Turbo leads Qwen3 Next 80B A3B Instruct on the Artificial Analysis Intelligence Index, 26.6 to 9.6, and Qwen3 Next 80B A3B Instruct costs 3.6x less per output token ($1.10 vs $4.00 per million). Updated October 22, 2026; 7 benchmarks have a result for both.
GLM 5 Turbo or Qwen3 Next 80B A3B Instruct: 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
- 7
- GLM 5 Turbo only
- 9
- Qwen3 Next 80B A3B Instruct only
- 34
- Like-for-like categories
- 5 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 9.6.
Same board, both measured
Web design
Design Arena: websites
No call
Only GLM 5 Turbo has a Design Arena: websites result, 1262.
Directional only
Long documents
Listed context window
Qwen3 Next 80B A3B Instruct
Qwen3 Next 80B A3B Instruct takes 262K tokens against 203K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Qwen3 Next 80B A3B Instruct
GLM 5 Turbo $0.0032, Qwen3 Next 80B A3B Instruct $0.0006 per turn.
List prices
At a glance
- Coding index
- GLM 5 Turbo not benchmarked, Qwen3 Next 80B A3B Instruct not benchmarked.
- Widest category
- Agentic work, 57.0 points apart on average over 1 shared benchmark.
- Widest single gap
- τ²-Bench Telecom: GLM 5 Turbo 98.5% against Qwen3 Next 80B A3B Instruct 41.5%, 57.0 points apart on a 0 to 100 scale.
- Output price
- GLM 5 Turbo $4.00 against Qwen3 Next 80B A3B Instruct $1.10 per million output tokens, 3.6x apart.
- Context window
- GLM 5 Turbo takes 203K tokens, Qwen3 Next 80B A3B Instruct 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 | Qwen3 Next 80B A3B Instruct | Ties |
|---|---|---|---|---|
| Coding | 1 | 0 | ||
| Intelligence | 1 | 0 | ||
| Agentic work | 1 | 0 | ||
| Reasoning | 2 | 0 | ||
| General | 2 | 0 | ||
| All shared boards | 7 | 0 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index10
| Benchmark | GLM 5 Turbo | Qwen3 Next 80B A3B Instruct | Leader |
|---|---|---|---|
| LiveCodeBench (Artificial Analysis run) | Not measured | 78.4% | Only Qwen3 Next 80B A3B Instruct measured |
| Terminal-Bench Hard (Artificial Analysis run) | 33.3% | 9.8% | GLM 5 Turbo |
| ALE-Bench | 634.0 | Not measured | Only GLM 5 Turbo measured |
| LMArena Text: coding | Not measured | 1440 | Only Qwen3 Next 80B A3B Instruct measured |
| LMArena Text: software and IT | Not measured | 1447 | Only Qwen3 Next 80B A3B Instruct measured |
| Neither model has a result on the other 38 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | GLM 5 Turbo | Qwen3 Next 80B A3B Instruct | Leader |
|---|---|---|---|
| AA Intelligence Index | 26.6 | 9.6 | 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 index10
| Benchmark | GLM 5 Turbo | Qwen3 Next 80B A3B Instruct | Leader |
|---|---|---|---|
| τ²-Bench Telecom | 98.5% | 41.5% | GLM 5 Turbo |
| Neither model has a result on the other 41 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index20
| Benchmark | GLM 5 Turbo | Qwen3 Next 80B A3B Instruct | Leader |
|---|---|---|---|
| GPQA Diamond (Artificial Analysis run) | 84.7% | 75.9% | GLM 5 Turbo |
| Humanity's Last Exam (Artificial Analysis run) | 27.8% | 12.6% | GLM 5 Turbo |
| LMArena Text: hard prompts | Not measured | 1428 | Only Qwen3 Next 80B A3B Instruct measured |
| LMArena Text: expert | Not measured | 1417 | Only Qwen3 Next 80B A3B Instruct measured |
| LMArena Text: hard prompts in English | Not measured | 1431 | Only Qwen3 Next 80B A3B Instruct measured |
| Kagi LLM Benchmark | Not measured | 66.7% | Only Qwen3 Next 80B A3B Instruct 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 | GLM 5 Turbo | Qwen3 Next 80B A3B Instruct | Leader |
|---|---|---|---|
| AA Math Index | Not measured | 84.3 | Only Qwen3 Next 80B A3B Instruct measured |
| AIME 2025 (Artificial Analysis run) | Not measured | 84.3% | Only Qwen3 Next 80B A3B Instruct measured |
| LMArena Text: math | Not measured | 1440 | Only Qwen3 Next 80B A3B Instruct measured |
| LMArena Text: mathematical work | Not measured | 1434 | Only Qwen3 Next 80B A3B Instruct measured |
| Neither model has a result on the other 10 boards here | |||
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index5 boards, none shared
| Benchmark | GLM 5 Turbo | Qwen3 Next 80B A3B Instruct | Leader |
|---|---|---|---|
| MMLU Pro (Artificial Analysis run) | Not measured | 82.4% | Only Qwen3 Next 80B A3B Instruct measured |
| LMArena Text: science | Not measured | 1434 | Only Qwen3 Next 80B A3B Instruct measured |
| LMArena Text: medicine and healthcare | Not measured | 1455 | Only Qwen3 Next 80B A3B Instruct measured |
| LMArena Text: legal and government | Not measured | 1431 | Only Qwen3 Next 80B A3B Instruct measured |
| LMArena Text: business and finance | Not measured | 1422 | Only Qwen3 Next 80B A3B Instruct measured |
| Neither model has a result on the other 15 boards here | |||
Web designDirectional onlyPublic boards, shown as published, kept out of the index8 boards, none shared
| Benchmark | GLM 5 Turbo | Qwen3 Next 80B A3B Instruct | Leader |
|---|---|---|---|
| Design Arena: websites | 1262 | Not measured | Only GLM 5 Turbo measured |
| Design Arena: UI components | 1260 | Not measured | Only GLM 5 Turbo measured |
| Design Arena: game dev | 1248 | Not measured | Only GLM 5 Turbo measured |
| Design Arena: data viz | 1264 | Not measured | Only GLM 5 Turbo measured |
| Design Arena: 3D | 1247 | Not measured | Only GLM 5 Turbo measured |
| Design Arena: all code categories | 1261 | Not measured | Only GLM 5 Turbo measured |
| Design Arena: SVG | 1205 | Not measured | Only GLM 5 Turbo measured |
| Design Arena: ASCII art | 1160 | Not measured | 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 index20
| Benchmark | GLM 5 Turbo | Qwen3 Next 80B A3B Instruct | Leader |
|---|---|---|---|
| IFBench | 73.2% | 60.7% | GLM 5 Turbo |
| Long context reasoning (AA-LCR) | 71.7% | 63.7% | GLM 5 Turbo |
| Fiction.LiveBench | Not measured | 55.6% | Only Qwen3 Next 80B A3B Instruct measured |
| LMArena Text | Not measured | 1417 | Only Qwen3 Next 80B A3B Instruct measured |
| LMArena Text: instruction following | Not measured | 1388 | Only Qwen3 Next 80B A3B Instruct measured |
| LMArena Text: creative writing | Not measured | 1333 | Only Qwen3 Next 80B A3B Instruct measured |
| LMArena Text: English | Not measured | 1421 | Only Qwen3 Next 80B A3B Instruct measured |
| LMArena Text: non-English | Not measured | 1407 | Only Qwen3 Next 80B A3B Instruct measured |
| LMArena Text: Chinese | Not measured | 1460 | Only Qwen3 Next 80B A3B Instruct measured |
| LMArena Text: German | Not measured | 1416 | Only Qwen3 Next 80B A3B Instruct measured |
| LMArena Text: Japanese | Not measured | 1395 | Only Qwen3 Next 80B A3B Instruct measured |
| LMArena Text: Korean | Not measured | 1363 | Only Qwen3 Next 80B A3B Instruct measured |
| LMArena Text: French | Not measured | 1414 | Only Qwen3 Next 80B A3B Instruct measured |
| LMArena Text: Spanish | Not measured | 1435 | Only Qwen3 Next 80B A3B Instruct measured |
| LMArena Text: Russian | Not measured | 1404 | Only Qwen3 Next 80B A3B Instruct measured |
| LMArena Text: Polish | Not measured | 1398 | Only Qwen3 Next 80B A3B Instruct measured |
| LMArena Text: multi-turn | Not measured | 1416 | Only Qwen3 Next 80B A3B Instruct measured |
| LMArena Text: longer queries | Not measured | 1402 | Only Qwen3 Next 80B A3B Instruct measured |
| LMArena Text: writing and language | Not measured | 1355 | Only Qwen3 Next 80B A3B Instruct measured |
| LMArena Text: entertainment and media | Not measured | 1349 | Only Qwen3 Next 80B A3B Instruct measured |
| Neither model has a result on the other 28 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | GLM 5 Turbo | Qwen3 Next 80B A3B Instruct | 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
Qwen3 Next 80B A3B Instruct costs less
Repository review
50K input + 3K output tokens
Qwen3 Next 80B A3B Instruct costs less
Agent loop
200K input + 10K output tokens
Qwen3 Next 80B A3B Instruct 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 | Qwen3 Next 80B A3B Instruct |
|---|---|---|
| Maker | Z.ai | Qwen |
| Weights | No public weights listed | Open weights |
| Released | March 15, 2026 | September 11, 2025 |
| Context window | 203K | 262K |
| Input $/Mtok | $1.20 | $0.10 |
| Output $/Mtok | $4.00 | $1.10 |
| 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 5 Turbo better than Qwen3 Next 80B A3B Instruct 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 5 Turbo or Qwen3 Next 80B A3B Instruct?
GLM 5 Turbo costs $1.20 per million input tokens and $4.00 per million output tokens; Qwen3 Next 80B A3B Instruct costs $0.10 and $1.10. Cost per solved task is known for neither of them.
Which has the bigger context window, GLM 5 Turbo or Qwen3 Next 80B A3B Instruct?
Qwen3 Next 80B A3B Instruct, with 262K tokens against 203K.
How many benchmarks is the GLM 5 Turbo vs Qwen3 Next 80B A3B Instruct comparison based on?
7 benchmarks have a result for both models as of October 22, 2026. GLM 5 Turbo's coding index rests on 0 independent benchmarks and Qwen3 Next 80B A3B Instruct's on 0. Where only one model has a result, the page says so instead of naming a winner.