GLM-5.3 vs Muse Glimmer 30B vs Muse Spark 1.2
Too close to call on our weighted score (Muse Spark 1.2 60, Muse Glimmer 30B 57, GLM-5.3 43). The right pick depends on what you value most.
Z.ai (Zhipu)GLM-5.3
43/100- ECI155.8
- Price$1.40 / $4.40
- Context1M
MetaMuse Glimmer 30B
57/100- ECI—
- Price$0.30 / $1.20
- Context131K
- Meta
Muse Spark 1.2
60/100- ECI155.0
- Price$1.25 / $4.25
- Context1.05M
Too close to call
It is close. Our weighted score puts them within 2 points (Muse Spark 1.2 60/100, Muse Glimmer 30B 57/100, GLM-5.3 43/100), so choose by what matters most for your work: Muse Glimmer 30B on price and Muse Spark 1.2 for long inputs. The score weighs price 50%, inputs & features 30%, context window 20%. 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 Glimmer 30BMuse Glimmer 30B $0.525 · Muse Spark 1.2 $2.00 · GLM-5.3 $2.15 per 1M tokens (3:1 blend)
- Longest contextMuse Spark 1.2Muse Spark 1.2 1,048,576 · GLM-5.3 1,000,000 · Muse Glimmer 30B 131,072 tokens
- Widest inputsMuse Spark 1.2GLM-5.3: Text · Muse Glimmer 30B: Text, Images · Muse Spark 1.2: Text, Images, PDFs, Audio, Video
- Self-hostingGLM-5.3 and Muse Glimmer 30BPublishes downloadable weights (Apache 2.0)
| Measure | Weight | GLM-5.3 | Muse Glimmer 30B | Muse Spark 1.2 |
|---|---|---|---|---|
| Price | 50% | 34 | 63 | 36 |
| Inputs & features | 30% | 45 | 70 | 100 |
| Context window | 20% | 60 | 24 | 61 |
| Overall | 100% | 43/100 | 57/100 | 60/100 |
Left out because at least one model lacks the data: capability. 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 Glimmer 30BMeta | Muse Spark 1.2Meta |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | 155.8 (best) | — | 155.0 |
| ECI rank | #24 of 148 (best) | — | #30 of 148 |
| 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% | — | 60.3% (best) |
| Price per million tokens | |||
| Input | $1.40 | $0.30 (best) | $1.25 |
| Output | $4.40 | $1.20 (best) | $4.25 |
| Cached input | $0.26 | — | $0.15 (best) |
| Blended (3:1) | $2.15 | $0.525 (best) | $2.00 |
| Long-context rate | Same rate | Same rate | Same rate |
| Price source | Official Z.AI API | Median of 10 providers | Official Meta API |
| Limits | |||
| Context window | 1,000,000 tokens | 131,072 tokens | 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 | No | Yes |
| Video | No | No | Yes |
| Reasoning | Yeslow · high · max | Yes | Yesminimal · low · medium · high · xhigh |
| Tool calling | Yes | Yes | Yes |
| Structured output | Yes | Yes | Yes |
| Availability | |||
| Weights | Open | OpenApache 2.0 | Proprietary |
| API model ID | glm-5.3 | — | muse-spark-1.2 |
| API providers | 62 (best) | 12 | 15 |
| Released | Aug 14, 2026 | Aug 10, 2026 | Aug 5, 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 Glimmer 30B$5.40
- Muse Spark 1.2$21.00
Which should you choose?
Which is better: GLM-5.3, Muse Glimmer 30B or Muse Spark 1.2?
It is close. Our weighted score puts them within 2 points (Muse Spark 1.2 60/100, Muse Glimmer 30B 57/100, GLM-5.3 43/100), so choose by what matters most for your work: Muse Glimmer 30B on price and Muse Spark 1.2 for long inputs. The score weighs price 50%, inputs & features 30%, context window 20%. 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 Glimmer 30B or Muse Spark 1.2?
Muse Glimmer 30B is cheaper at $0.30 input / $1.20 output per million tokens (median across 10 API providers). Muse Spark 1.2 costs $1.25 input / $4.25 output per million tokens (official Meta API price); 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 $0.525 per million tokens for Muse Glimmer 30B versus $2.00 for Muse Spark 1.2 (3.8× as much) and $2.15 for GLM-5.3 (4.1× as much).
Which scores higher on benchmarks?
There is no independent benchmark that covers all three models yet. GLM-5.3 has an ECI of 155.8, Muse Glimmer 30B has not been scored yet and Muse Spark 1.2 has an ECI of 155.0.
Which is better for coding?
There are no published SWE-bench Verified results for GLM-5.3, Muse Glimmer 30B and Muse Spark 1.2 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 1.2 has the largest context window at 1,048,576 tokens, against 1,000,000 for GLM-5.3 and 131,072 for Muse Glimmer 30B. Maximum output per response: GLM-5.3 up to 131,072, Muse Glimmer 30B up to 131,072, Muse Spark 1.2 up to 131,072 tokens.
Which can read images, PDFs, audio or video?
GLM-5.3 accepts text; Muse Glimmer 30B accepts text and images; Muse Spark 1.2 accepts text, images, PDFs, audio and video. Muse Spark 1.2 handles the widest range of inputs.
Are any of these open source?
GLM-5.3 and Muse Glimmer 30B publishes its weights (Apache 2.0) and can be self-hosted; Muse Spark 1.2 is proprietary.
Which is newer?
GLM-5.3 is the newest, released Aug 14, 2026. Muse Glimmer 30B came out Aug 10, 2026; Muse Spark 1.2 came out Aug 5, 2026. Knowledge cutoff: Muse Glimmer 30B 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 Oct 4, 2026.
