Muse Spark 1.2 vs Muse Spark Open vs GLM-5.3
Muse Spark 1.2 comes out ahead, 71 to 68 and 63 on our weighted score.
- Our pick
Meta
Muse Spark 1.2
71/100- ECI155.2
- Price$1.25 / $4.25
- Context1.05M
Meta
Muse Spark Open
68/100- ECI155.1
- Price$1.25 / $4.25
- Context1.05M
Z.ai (Zhipu)
GLM-5.3
63/100- ECI156.2
- Price$1.40 / $4.40
- Context1M
Muse Spark 1.2 is our pick
Muse Spark 1.2 is the better all-round choice, scoring 71/100 against Muse Spark Open (68) and GLM-5.3 (63). It leads on inputs & features. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.
- CapabilityGLM-5.3Capabilities Index (ECI): GLM-5.3 156.2 · Muse Spark 1.2 155.2 · Muse Spark Open 155.1
- Lowest priceMuse Spark 1.2 and Muse Spark OpenMuse Spark 1.2 $2.00 · Muse Spark Open $2.00 · GLM-5.3 $2.15 per 1M tokens (3:1 blend)
- Longest contextMuse Spark 1.2 and Muse Spark OpenMuse Spark 1.2 1,048,576 · Muse Spark Open 1,048,576 · GLM-5.3 1,000,000 tokens
- Widest inputsMuse Spark 1.2Muse Spark 1.2: Text, Images, PDFs, Audio, Video · Muse Spark Open: Text, Images, Audio, Video · GLM-5.3: Text
- Self-hostingMuse Spark Open and GLM-5.3Publishes downloadable weights (Muse Model License)
| Measure | Weight | Muse Spark 1.2 | Muse Spark Open | GLM-5.3 |
|---|---|---|---|---|
| CapabilityCapabilities Index (ECI) | 50% | 83 | 83 | 84 |
| Price | 25% | 34 | 34 | 33 |
| Inputs & features | 15% | 100 | 80 | 45 |
| Context window | 10% | 61 | 61 | 60 |
| Overall | 100% | 71/100 | 68/100 | 63/100 |
Every spec in one table
Highlighted cells lead their row. Dashes mean the data is not published.
| Specification | |||
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | 155.2 | 155.1 | 156.2 (best) |
| ECI rank | #38 of 165 | #39 of 165 | #33 of 165 (best) |
| GPQA DiamondGraduate-level science questions | — | 88.6% | 90.9% (best) |
| FrontierMath Tiers 1–3Research-level mathematics | — | 69.8% (best) | 68.8% |
| OTIS Mock AIME 2024–2025Competition mathematics | — | 98.1% (best) | 91.1% |
| SimpleQA VerifiedShort factual questions | 60.3% (best) | 56.6% | 41.0% |
| Price per million tokens | |||
| Input | $1.25 (best) | $1.25 (best) | $1.40 |
| Output | $4.25 (best) | $4.25 (best) | $4.40 |
| Cached input | $0.15 (best) | — | $0.26 |
| Blended (3:1) | $2.00 (best) | $2.00 (best) | $2.15 |
| Long-context rate | Same rate | Same rate | Same rate |
| Price source | Official Meta API | Median of 16 providers | Official Z.AI API |
| Limits | |||
| Context window | 1,048,576 tokens (best) | 1,048,576 tokens (best) | 1,000,000 tokens |
| Max output | 131,072 tokens | 131,072 tokens | 131,072 tokens |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | Yes | Yes | No |
| PDFs | Yes | No | No |
| Audio | Yes | Yes | No |
| Video | Yes | Yes | No |
| Reasoning | Yesminimal · low · medium · high · xhigh | Yes | Yeslow · high · max |
| Tool calling | Yes | Yes | Yes |
| Structured output | Yes | No | Yes |
| Availability | |||
| Weights | Proprietary | OpenMuse Model License | Open |
| API model ID | muse-spark-1.2 | — | glm-5.3 |
| API providers | 18 | 16 | 83 (best) |
| Released | Aug 5, 2026 | Oct 15, 2026 | Aug 14, 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.
Muse Spark 1.2$21.00
Muse Spark Open$21.00
GLM-5.3$22.80
Which should you choose?
Which is better: Muse Spark 1.2, Muse Spark Open or GLM-5.3?
Muse Spark 1.2 is the better all-round choice, scoring 71/100 against Muse Spark Open (68) and GLM-5.3 (63). It leads on inputs & features. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.
Which is cheaper, Muse Spark 1.2, Muse Spark Open or GLM-5.3?
Muse Spark 1.2 is cheaper at $1.25 input / $4.25 output per million tokens (official Meta API price). Muse Spark Open costs $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 1.2 versus $2.00 for Muse Spark Open (1× as much) and $2.15 for GLM-5.3 (1.1× as much).
Which scores higher on benchmarks?
GLM-5.3 scores higher on the Capabilities Index (ECI): GLM-5.3 156.2 (#33 of 165), Muse Spark 1.2 155.2 (#38 of 165) and Muse Spark Open 155.1 (#39 of 165). The confidence ranges of the top two overlap (154.3–158.5 vs 152.9–157.6), so treat the gap as small. On individual benchmarks: SimpleQA Verified — Muse Spark 1.2 60.3%, Muse Spark Open 56.6%, GLM-5.3 41.0%.
Which is better for coding?
There are no published SWE-bench Verified results for Muse Spark 1.2, Muse Spark Open and GLM-5.3 yet, so there is no like-for-like coding score. On overall capability, GLM-5.3 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 1.2 and Muse Spark Open 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: Muse Spark 1.2 up to 131,072, Muse Spark Open up to 131,072, GLM-5.3 up to 131,072 tokens.
Which can read images, PDFs, audio or video?
Muse Spark 1.2 accepts text, images, PDFs, audio and video; Muse Spark Open accepts text, images, audio and video; GLM-5.3 accepts text. Muse Spark 1.2 handles the widest range of inputs.
Are any of these open source?
Muse Spark Open and GLM-5.3 publishes its weights (Muse Model License) and can be self-hosted; Muse Spark 1.2 is proprietary.
Which is newer?
Muse Spark Open is the newest, released Oct 15, 2026. GLM-5.3 came out Aug 14, 2026; Muse Spark 1.2 came out Aug 5, 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.