GLM-5.3 vs Muse Spark Open vs Muse Wonder
Too close to call on our weighted score (Muse Wonder 68, Muse Spark Open 68, GLM-5.3 63). The right pick depends on what you value most.
Z.ai (Zhipu)GLM-5.3
63/100- ECI156.2
- Price$1.40 / $4.40
- Context1M
MetaMuse Spark Open
68/100- ECI155.1
- Price$1.25 / $4.25
- Context1.05M
- Meta
Muse Wonder
68/100- ECI161.7
- Price$4.00 / $20.00
- Context1.05M
Too close to call
It is close. Our weighted score puts them within a point (Muse Wonder 68/100, Muse Spark Open 68/100, GLM-5.3 63/100), so choose by what matters most for your work: Muse Wonder for raw capability and Muse Spark Open on price. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.
- CapabilityMuse WonderCapabilities Index (ECI): Muse Wonder 161.7 · GLM-5.3 156.2 · Muse Spark Open 155.1
- Lowest priceMuse Spark OpenMuse Spark Open $2.00 · GLM-5.3 $2.15 · Muse Wonder $8.00 per 1M tokens (3:1 blend)
- Longest contextMuse Spark Open and Muse WonderMuse Spark Open 1,048,576 · Muse Wonder 1,048,576 · GLM-5.3 1,000,000 tokens
- Widest inputsMuse WonderGLM-5.3: Text · Muse Spark Open: Text, Images, Audio, Video · Muse Wonder: Text, Images, PDFs, 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 |
|---|---|---|---|---|
| CapabilityCapabilities Index (ECI) | 50% | 84 | 83 | 91 |
| Price | 25% | 33 | 34 | 7 |
| Inputs & features | 15% | 45 | 80 | 100 |
| Context window | 10% | 60 | 61 | 61 |
| Overall | 100% | 63/100 | 68/100 | 68/100 |
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 WonderMeta |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | 156.2 | 155.1 | 161.7 (best) |
| ECI rank | #33 of 165 | #39 of 165 | #13 of 165 (best) |
| GPQA DiamondGraduate-level science questions | 90.9% (best) | 88.6% | — |
| FrontierMath Tiers 1–3Research-level mathematics | 68.8% | 69.8% | 82.1% (best) |
| OTIS Mock AIME 2024–2025Competition mathematics | 91.1% | 98.1% | 99.4% (best) |
| SimpleQA VerifiedShort factual questions | 41.0% | 56.6% (best) | — |
| Price per million tokens | |||
| Input | $1.40 | $1.25 (best) | $4.00 |
| Output | $4.40 | $4.25 (best) | $20.00 |
| Cached input | $0.26 | — | $0.20 (best) |
| Blended (3:1) | $2.15 | $2.00 (best) | $8.00 |
| Long-context rate | Same rate | Same rate | Same rate |
| Price source | Official Z.AI API | Median of 16 providers | Official Meta API |
| 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 | 131,072 tokens |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | No | Yes | Yes |
| PDFs | No | No | Yes |
| Audio | No | Yes | Yes |
| Video | No | Yes | Yes |
| Reasoning | Yeslow · high · max | Yes | Yesminimal · low · medium · high · xhigh · max |
| Tool calling | Yes | Yes | Yes |
| Structured output | Yes | No | Yes |
| Availability | |||
| Weights | Open | OpenMuse Model License | Proprietary |
| API model ID | glm-5.3 | — | muse-wonder-1.0 |
| API providers | 83 (best) | 16 | 9 |
| 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$80.00
Which should you choose?
Which is better: GLM-5.3, Muse Spark Open or Muse Wonder?
It is close. Our weighted score puts them within a point (Muse Wonder 68/100, Muse Spark Open 68/100, GLM-5.3 63/100), so choose by what matters most for your work: Muse Wonder for raw capability and Muse Spark Open on price. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.
Which is cheaper, GLM-5.3, Muse Spark Open or Muse Wonder?
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); Muse Wonder costs $4.00 input / $20.00 output per million tokens (official Meta 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) and $8.00 for Muse Wonder (4× as much).
Which scores higher on benchmarks?
Muse Wonder scores higher on the Capabilities Index (ECI): Muse Wonder 161.7 (#13 of 165), GLM-5.3 156.2 (#33 of 165) and Muse Spark Open 155.1 (#39 of 165). Their confidence ranges do not overlap (159.2–164.6 vs 154.3–158.5), so the gap is a real one. On individual benchmarks: FrontierMath Tiers 1–3 — Muse Wonder 82.1%, Muse Spark Open 69.8%, GLM-5.3 68.8%; OTIS Mock AIME 2024–2025 — Muse Wonder 99.4%, Muse Spark Open 98.1%, GLM-5.3 91.1%.
Which is better for coding?
There are no published SWE-bench Verified results for GLM-5.3, Muse Spark Open and Muse Wonder yet, so there is no like-for-like coding score. On overall capability, Muse Wonder leads, which tends to carry over to coding, but test on your own codebase. All three support tool calling for agent workflows.
Which has the bigger context window?
Muse Spark Open and Muse Wonder 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, Muse Wonder 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 accepts text, images, PDFs, audio and video. Muse Wonder 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 is proprietary.
Which is newer?
Muse Spark Open is the newest, released Oct 15, 2026. Muse Wonder 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.
