GLM-5.3 vs Muse Wonder Full
Muse Wonder Full comes out ahead, 72 to 51 on our weighted score.
Z.ai (Zhipu)GLM-5.3
51/100- ECI156.2
- Price$1.40 / $4.40
- Context1M
- Our pick
MetaMuse Wonder Full
72/100- ECI—
- Price—
- Context1.05M
Add a model
Make it a three-way comparison.
Muse Wonder Full is our pick
Muse Wonder Full is the better all-round choice, scoring 72/100 against GLM-5.3 (51). It leads on inputs & features. The score weighs inputs & features 60%, context window 40%. None of the shared benchmarks cover every model here yet, so capability is left out of this verdict.
- CapabilityNot enough dataNo independent benchmark covers every model here yet
- Lowest priceGLM-5.3GLM-5.3 $2.15 per 1M tokens (3:1 blend) · Muse Wonder Full unpriced
- Longest contextMuse Wonder FullMuse Wonder Full 1,048,576 · GLM-5.3 1,000,000 tokens
- Widest inputsMuse Wonder FullGLM-5.3: Text · Muse Wonder Full: Text, Images, Audio, Video
- Self-hostingGLM-5.3Publishes downloadable weights
| Measure | Weight | GLM-5.3 | Muse Wonder Full |
|---|---|---|---|
| Inputs & features | 60% | 45 | 80 |
| Context window | 40% | 60 | 61 |
| Overall | 100% | 51/100 | 72/100 |
Left out because at least one model lacks the data: capability and price. The remaining weights were rescaled.
Every spec in one table
Highlighted cells lead their row. Dashes mean the data is not published.
| Specification | GLM-5.3Z.ai (Zhipu) | Muse Wonder FullMeta |
|---|---|---|
| Capability | ||
| Capabilities Index (ECI) | 156.2 | — |
| ECI rank | #33 of 165 | — |
| GPQA DiamondGraduate-level science questions | 90.9% | — |
| FrontierMath Tiers 1–3Research-level mathematics | 68.8% | — |
| OTIS Mock AIME 2024–2025Competition mathematics | 91.1% | — |
| SimpleQA VerifiedShort factual questions | 41.0% | — |
| Price per million tokens | ||
| Input | $1.40 | — |
| Output | $4.40 | — |
| Cached input | $0.26 | — |
| Blended (3:1) | $2.15 | — |
| Long-context rate | Same rate | — |
| Price source | Official Z.AI API | — |
| Limits | ||
| Context window | 1,000,000 tokens | 1,048,576 tokens (best) |
| Max output | 131,072 tokens | — |
| Inputs and features | ||
| Text | Yes | Yes |
| Images | No | Yes |
| PDFs | No | No |
| Audio | No | Yes |
| Video | No | Yes |
| Reasoning | Yeslow · high · max | Yes |
| Tool calling | Yes | Yes |
| Structured output | Yes | No |
| Availability | ||
| Weights | Open | Proprietary |
| API model ID | glm-5.3 | — |
| API providers | 83 | — |
| Released | Aug 14, 2026 | Oct 12, 2026 |
| Knowledge cutoff | — | — |
What would a month cost?
Enter your expected volume in millions of tokens. List prices only; caching and batch discounts would lower these.
- GLM-5.3$22.80
- Muse Wonder Full—
Which should you choose?
Which is better: GLM-5.3 or Muse Wonder Full?
Muse Wonder Full is the better all-round choice, scoring 72/100 against GLM-5.3 (51). It leads on inputs & features. The score weighs inputs & features 60%, context window 40%. None of the shared benchmarks cover every model here yet, so capability is left out of this verdict.
Which is cheaper, GLM-5.3 or Muse Wonder Full?
GLM-5.3 is cheaper at $1.40 input / $4.40 output per million tokens (official Z.AI API price). . At a typical mix of three input tokens to one output token, that is $2.15 per million tokens for GLM-5.3 versus . Muse Wonder Full has no published per-token price.
Which scores higher on benchmarks?
There is no independent benchmark that covers both models yet. GLM-5.3 has an ECI of 156.2 and Muse Wonder Full has not been scored yet.
Which is better for coding?
There are no published SWE-bench Verified results for GLM-5.3 and Muse Wonder Full yet, so there is no like-for-like coding score. Test both on a sample of your own tasks. Both support tool calling for agent workflows.
Which has the bigger context window?
Muse Wonder Full has the largest context window at 1,048,576 tokens, against 1,000,000 for GLM-5.3. Maximum output per response: GLM-5.3 up to 131,072 tokens.
Which can read images, PDFs, audio or video?
GLM-5.3 accepts text; Muse Wonder Full accepts text, images, audio and video. Muse Wonder Full handles the widest range of inputs.
Are any of these open source?
GLM-5.3 publishes its weights and can be self-hosted; Muse Wonder Full is proprietary.
Which is newer?
Muse Wonder Full is the newest, released Oct 12, 2026. GLM-5.3 came out Aug 14, 2026.
How do you decide the winner?
Each model gets a 0–100 score on capability (50%, independent benchmark results); price (25%, blended price per million tokens (3 input : 1 output), log scale); inputs & features (15%, image, PDF, audio and video input, tool calling, structured output and reasoning); context window (10%, maximum tokens per request, log scale). Dimensions missing for any model are dropped and the remaining weights rescaled, so every model is judged on the same evidence. Specs and prices come from public model listings and the labs’ own API pages; capability scores come from independent benchmark runs. Data updated Nov 2, 2026.
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