GLM-5.3 vs Muse Spark Open vs Muse Wonder Full
Too close to call on our weighted score (Muse Spark Open 72, Muse Wonder Full 72, GLM-5.3 51). The right pick depends on what you value most.
Z.ai (Zhipu)GLM-5.3
51/100- ECI156.2
- Price$1.40 / $4.40
- Context1M
MetaMuse Spark Open
72/100- ECI155.1
- Price$1.25 / $4.25
- Context1.05M
- Meta
Muse Wonder Full
72/100- ECI—
- Price—
- Context1.05M
Too close to call
It is close. Our weighted score puts them within a point (Muse Spark Open 72/100, Muse Wonder Full 72/100, GLM-5.3 51/100), so choose by what matters most for your work: Muse Spark Open on price. 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 priceMuse Spark OpenMuse Spark Open $2.00 · GLM-5.3 $2.15 per 1M tokens (3:1 blend) · Muse Wonder Full unpriced
- Longest contextMuse Spark Open and Muse Wonder FullMuse Spark Open 1,048,576 · Muse Wonder Full 1,048,576 · GLM-5.3 1,000,000 tokens
- Widest inputsMuse Spark Open and Muse Wonder FullGLM-5.3: Text · Muse Spark Open: Text, Images, Audio, Video · Muse Wonder Full: Text, Images, Audio, Video
- Self-hostingGLM-5.3 and Muse Spark OpenPublishes downloadable weights (Muse Model License)
| Measure | Weight | GLM-5.3 | Muse Spark Open | Muse Wonder Full |
|---|---|---|---|---|
| Inputs & features | 60% | 45 | 80 | 80 |
| Context window | 40% | 60 | 61 | 61 |
| Overall | 100% | 51/100 | 72/100 | 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 Spark OpenMeta | Muse Wonder FullMeta |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | 156.2 (best) | 155.1 | — |
| ECI rank | #33 of 165 (best) | #39 of 165 | — |
| GPQA DiamondGraduate-level science questions | 90.9% (best) | 88.6% | — |
| FrontierMath Tiers 1–3Research-level mathematics | 68.8% | 69.8% (best) | — |
| OTIS Mock AIME 2024–2025Competition mathematics | 91.1% | 98.1% (best) | — |
| SimpleQA VerifiedShort factual questions | 41.0% | 56.6% (best) | — |
| Price per million tokens | |||
| Input | $1.40 | $1.25 (best) | — |
| Output | $4.40 | $4.25 (best) | — |
| Cached input | $0.26 | — | — |
| Blended (3:1) | $2.15 | $2.00 (best) | — |
| Long-context rate | Same rate | Same rate | — |
| Price source | Official Z.AI API | Median of 16 providers | — |
| Limits | |||
| Context window | 1,000,000 tokens | 1,048,576 tokens (best) | 1,048,576 tokens (best) |
| Max output | 131,072 tokens | 131,072 tokens | — |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | No | Yes | Yes |
| PDFs | No | No | No |
| Audio | No | Yes | Yes |
| Video | No | Yes | Yes |
| Reasoning | Yeslow · high · max | Yes | Yes |
| Tool calling | Yes | Yes | Yes |
| Structured output | Yes | No | No |
| Availability | |||
| Weights | Open | OpenMuse Model License | Proprietary |
| API model ID | glm-5.3 | — | — |
| API providers | 83 (best) | 16 | — |
| Released | Aug 14, 2026 | Oct 15, 2026 | Oct 12, 2026 |
| Knowledge cutoff | — | Jan 4, 2026 | — |
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 Spark Open$21.00
- Muse Wonder Full—
Which should you choose?
Which is better: GLM-5.3, Muse Spark Open or Muse Wonder Full?
It is close. Our weighted score puts them within a point (Muse Spark Open 72/100, Muse Wonder Full 72/100, GLM-5.3 51/100), so choose by what matters most for your work: Muse Spark Open on price. 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, Muse Spark Open or Muse Wonder Full?
Muse Spark Open is cheaper at $1.25 input / $4.25 output per million tokens (median across 16 API providers). GLM-5.3 costs $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 $2.00 per million tokens for Muse Spark Open versus $2.15 for GLM-5.3 (1.1× as much). Muse Wonder Full has no published per-token price.
Which scores higher on benchmarks?
There is no independent benchmark that covers all three models yet. GLM-5.3 has an ECI of 156.2, Muse Spark Open has an ECI of 155.1 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, Muse Spark Open and Muse Wonder Full yet, so there is no like-for-like coding score. Test both on a sample of your own tasks. All three support tool calling for agent workflows.
Which has the bigger context window?
Muse Spark Open and Muse Wonder Full have the largest context windows (1,048,576 and 1,048,576 tokens), against 1,000,000 for GLM-5.3. Maximum output per response: GLM-5.3 up to 131,072, Muse Spark Open up to 131,072 tokens.
Which can read images, PDFs, audio or video?
GLM-5.3 accepts text; Muse Spark Open accepts text, images, audio and video; Muse Wonder Full accepts text, images, audio and video. Muse Spark Open handles the widest range of inputs.
Are any of these open source?
GLM-5.3 and Muse Spark Open publishes its weights (Muse Model License) and can be self-hosted; Muse Wonder Full is proprietary.
Which is newer?
Muse Spark Open is the newest, released Oct 15, 2026. Muse Wonder Full came out Oct 12, 2026; GLM-5.3 came out Aug 14, 2026. Knowledge cutoff: Muse Spark Open Jan 4, 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.
