Compare / Muse Wonder vs GLM-5V-Turbo
Muse Wonder vs GLM-5V-Turbo
Which is cheaper, which is more capable, and which does better at each kind of work, from 34 results on 2 sources that measured both models.
Of the 34 results both models have, the better value on each. Results whose reported ranges overlap are too close to call.
Results as of 14 October 2026 (catalogue release 2026-10-14-7d7cf32c3f6d). See also Meta vs Z.ai, every model from both labs.
Muse Wonder or GLM-5V-Turbo? The short answer
Pick Muse Wonder if quality matters most: it scores higher (Spring Prompt overall 71 against 10). Pick GLM-5V-Turbo if cost matters more: it costs 5.1 times less per product listing on CatalogBench.
- Spring Prompt overall: Muse Wonder 71, GLM-5V-Turbo 10 (out of 100; how the score works).
- GLM-5V-Turbo is cheaper to run: $0.007 against $0.036 per product listing on CatalogBench (5.1 times less).
- Muse Wonder scores higher on the Artificial Analysis Intelligence Index: 52.4 against 23.5.
- Muse Wonder is newer: released 12 Oct 2026, against 1 Apr 2026 for GLM-5V-Turbo.
- On our own benchmarks, on the results both models have: Muse Wonder does better for product listings.
- On third-party benchmarks, on the results both models have: Muse Wonder does better for reasoning and knowledge.
Head to head
Every fact side by side
| Muse Wonder | GLM-5V-Turbo | |
|---|---|---|
| Price per million tokens | $4.00 in · $20.00 out | $1.20 in · $4.00 out |
| Blended (3 in : 1 out) | $8.00 | $1.90 |
| Cheapest host, blended | – | – |
| Cost per product listing (CatalogBench) | $0.036 | $0.007 |
| Cached input, per million | $0.20 cached input | – |
| Intelligence Index | 52.4 | 23.5 |
| Spring Prompt overall | 71 | 10 |
| Output speed, tokens a second | 117 | – |
| Context window | 1,048,576 tokens | 202,752 tokens |
| Released | 12 Oct 2026 (newer) | 1 Apr 2026 |
| Weights | Closed | Closed |
| Developer based in | the US | China |
Prices are the developer's list price where we have read it, otherwise the typical host on OpenRouter; see every model's price. Intelligence and speed from Artificial Analysis.
Which is better for what
Each model's rank among the models on sale today, for each kind of work, from our own benchmarks and licensed sources. Further right is better; the better rank is in green.
From our research
Every shared result
Each model's best result on every measure both have, grouped by benchmark, with the setting that produced it. Under each measure, every model that benchmark has measured is a grey tick, best to the right, so you can see where the two sit in the field. The headline measures of each benchmark come first; the rest are under "Show all". Green marks the better value; where a source reports ranges that overlap, neither is marked.
| Measure | Muse Wonder | GLM-5V-Turbo |
|---|---|---|
| CatalogBench measured by Spring Prompt · 3 results | ||
| Cost per productUS dollars, lower is better 18 · 7 of 22 measured | $0.0361 | $0.0070 |
| Reliably publish-ready% of products, higher is better 3 · 21 of 22 measured | 66.1% | 1.8% |
| Reliably publish-ready · sales brief% of products, higher is better 4 · 20 of 22 measured | 51.8% | 0.0% |
| Artificial Analysis reported by Artificial Analysis · 3 results | ||
| Artificial Analysis Intelligence Indexindex score, higher is better 6 · 84 of 244 measured | 52.4max reasoning | 23.5 |
| Humanity's Last Exam% of questions, higher is better 9 · 119 of 243 measured | 50.1%max reasoning | 17.1% |
| Long-context reasoning (AA-LCR)% of questions, higher is better 33 · 108 of 234 measured | 80.7%max reasoning | 70.3% |
Show all 34 results (28 more)
| Measure | Muse Wonder | GLM-5V-Turbo |
|---|---|---|
| CatalogBench measured by Spring Prompt · 28 results | ||
| Channel compliance% of products, higher is better 15 · 21 of 22 measured | 99.4% | 98.3% |
| Channel rules broken% of products, lower is better 12 · 18 of 22 measured | 0.6% | 1.2% |
| Channel rules broken · sales brief% of products, lower is better 1 · 11 of 22 measured | 0.0% | 0.6% |
| Claims to check% of products, lower is better 1 · 21 of 22 measured | 0.0% | 11.5% |
| Claims to check · sales brief% of products, lower is better 1 · 21 of 22 measured | 0.0% | 28.9% |
| Conflicts caught% of conflicts, higher is better 1 · 1 of 22 measured | 100.0% | 100.0% |
| Content quality% of checks, higher is better 3 · 22 of 22 measured | 98.3% | 63.3% |
| Content quality · sales brief% of checks, higher is better 3 · 22 of 22 measured | 98.5% | 16.8% |
| Decision accuracy% of decisions, higher is better 3 · 22 of 22 measured | 98.3% | 61.0% |
| Failed outputs% of products, lower is better 1 · 22 of 22 measured | 0.0% | 32.1% |
| Failed outputs · sales brief% of products, lower is better 1 · 22 of 22 measured | 0.0% | 82.1% |
| Field accuracy% of missing fields, higher is better 1 · 22 of 22 measured | 96.1% | 59.6% |
| Invented values% of filled values, lower is better 11 · 20 of 22 measured | 1.4% | 3.8% |
| Missing UK information% of products, lower is better 1 · 1 of 22 measured | 0.0% | 0.0% |
| Missing UK information · sales brief% of products, lower is better 1 · 1 of 22 measured | 0.0% | 0.0% |
| Not findable% of products, lower is better 5 · 11 of 22 measured | 3.6% | 5.4% |
| Not findable · sales brief% of products, lower is better 9 · 2 of 22 measured | 3.6% | 1.8% |
| Publish-ready listings% of products, higher is better 3 · 22 of 22 measured | 75.0% | 10.1% |
| Publish-ready listings · sales brief% of products, higher is better 5 · 22 of 22 measured | 67.3% | 0.0% |
| Time per productseconds, lower is better 8 · 20 of 22 measured | 10.2 | 62.3 |
| Unsupported claimsclaims per product, lower is better 4 · 21 of 22 measured | 0.21 | 2.49 |
| Unsupported claims% of products, lower is better 4 · 21 of 22 measured | 7.1% | 55.4% |
| Unsupported claims · sales brief% of products, lower is better 5 · 5 of 22 measured | 17.9% | 17.9% |
| Unsupported claims · sales briefclaims per product, lower is better 5 · 8 of 22 measured | 0.36 | 1.31 |
| Wrong attributes% of products, lower is better 2 · 2 of 22 measured | 13.1% | 13.1% |
| Wrong attributes · sales brief% of products, lower is better 4 · 1 of 22 measured | 14.3% | 3.6% |
| Wrong category or variant% of products, lower is better 11 · 2 of 22 measured | 2.4% | 1.2% |
| Wrong category or variant · sales brief% of products, lower is better 11 · 3 of 22 measured | 2.4% | 1.2% |
Compare them with other models
- Meta vs Z.aiEvery model from both labs, best against best
- Muse Wonder vs Claude Opus 5.5Most intelligent at $3–10 per million tokens
- Muse Wonder vs Claude Sonnet 5.5Cheapest with similar intelligence
- Muse Wonder vs Gemini 4 ArgonJust above overall
- Muse Wonder vs GPT-6 SolJust below overall
- GLM-5V-Turbo vs Muse Spark 1.3Most intelligent at $1–3 per million tokens
- GLM-5V-Turbo vs Claude Opus 5.5Most intelligent available today
Quick answers
Is Muse Wonder better than GLM-5V-Turbo?
Pick Muse Wonder if quality matters most: it scores higher (Spring Prompt overall 71 against 10). Pick GLM-5V-Turbo if cost matters more: it costs 5.1 times less per product listing on CatalogBench.
Which is cheaper, Muse Wonder or GLM-5V-Turbo?
GLM-5V-Turbo is cheaper to run: $0.007 against $0.036 per product listing on CatalogBench (5.1 times less).
Which is better for product listings, Muse Wonder or GLM-5V-Turbo?
Muse Wonder ranks 4 of 22 models on sale for turning a sparse product feed and photos into listings that can go live, against 21 for GLM-5V-Turbo.
Which is better for reasoning and knowledge, Muse Wonder or GLM-5V-Turbo?
Muse Wonder ranks 7 of 200 models on sale for hard questions across science, maths and general knowledge, against 99 for GLM-5V-Turbo.
Which has the bigger context window, Muse Wonder or GLM-5V-Turbo?
Muse Wonder: 1,048,576 tokens, against 202,752 for GLM-5V-Turbo.
Run Muse Wonder and GLM-5V-Turbo on your own prompt
Benchmarks aren't your data. Try both side by side in the playground, with the cost of every answer.