GLM-5.3 vs Grok 4.7 vs Muse Spark Open
Muse Spark Open comes out ahead, 68 to 64 and 63 on our weighted score, and it is the cheaper option too.
Z.ai (Zhipu)GLM-5.3
63/100- ECI156.2
- Price$1.40 / $4.40
- Context1M
xAIGrok 4.7
64/100- ECI154.6
- Price$2.00 / $6.00
- Context500K
- Our pick
MetaMuse Spark Open
68/100- ECI155.1
- Price$1.25 / $4.25
- Context1.05M
Muse Spark Open is our pick
Muse Spark Open is the better all-round choice, scoring 68/100 against Grok 4.7 (64) and GLM-5.3 (63). 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 Open 155.1 · Grok 4.7 154.6
- Lowest priceMuse Spark OpenMuse Spark Open $2.00 · GLM-5.3 $2.15 · Grok 4.7 $3.00 per 1M tokens (3:1 blend)
- Longest contextMuse Spark OpenMuse Spark Open 1,048,576 · GLM-5.3 1,000,000 · Grok 4.7 500,000 tokens
- Widest inputsMuse Spark OpenGLM-5.3: Text · Grok 4.7: Text, Images, PDFs · Muse Spark Open: Text, Images, Audio, Video
- Self-hostingGLM-5.3 and Muse Spark OpenPublishes downloadable weights (Muse Model License)
| Measure | Weight | GLM-5.3 | Grok 4.7 | Muse Spark Open |
|---|---|---|---|---|
| CapabilityCapabilities Index (ECI) | 50% | 84 | 82 | 83 |
| Price | 25% | 33 | 26 | 34 |
| Inputs & features | 15% | 45 | 80 | 80 |
| Context window | 10% | 60 | 48 | 61 |
| Overall | 100% | 63/100 | 64/100 | 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) | Grok 4.7xAI | Muse Spark OpenMeta |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | 156.2 (best) | 154.6 | 155.1 |
| ECI rank | #33 of 165 (best) | #43 of 165 | #39 of 165 |
| GPQA DiamondGraduate-level science questions | 90.9% | 92.7% (best) | 88.6% |
| FrontierMath Tiers 1–3Research-level mathematics | 68.8% | 53.0% | 69.8% (best) |
| OTIS Mock AIME 2024–2025Competition mathematics | 91.1% | 98.1% (best) | 98.1% (best) |
| SimpleQA VerifiedShort factual questions | 41.0% | 56.0% | 56.6% (best) |
| Price per million tokens | |||
| Input | $1.40 | $2.00 | $1.25 (best) |
| Output | $4.40 | $6.00 | $4.25 (best) |
| Cached input | $0.26 (best) | $0.50 | — |
| Blended (3:1) | $2.15 | $3.00 | $2.00 (best) |
| Long-context rate | Same rate | Over 200K: $4.00 / $12.00 | Same rate |
| Price source | Official Z.AI API | Official xAI API | Median of 16 providers |
| Limits | |||
| Context window | 1,000,000 tokens | 500,000 tokens | 1,048,576 tokens (best) |
| Max output | 131,072 tokens | 500,000 tokens (best) | 131,072 tokens |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | No | Yes | Yes |
| PDFs | No | Yes | No |
| Audio | No | No | Yes |
| Video | No | No | Yes |
| Reasoning | Yeslow · high · max | Yeslow · medium · high · xhigh | Yes |
| Tool calling | Yes | Yes | Yes |
| Structured output | Yes | Yes | No |
| Availability | |||
| Weights | Open | Proprietary | OpenMuse Model License |
| API model ID | glm-5.3 | grok-4.7 | — |
| API providers | 83 (best) | 27 | 16 |
| Released | Aug 14, 2026 | Sep 21, 2026 | Oct 15, 2026 |
| Knowledge cutoff | — | May 2026 | 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
- Grok 4.7$32.00
- Muse Spark Open$21.00
Which should you choose?
Which is better: GLM-5.3, Grok 4.7 or Muse Spark Open?
Muse Spark Open is the better all-round choice, scoring 68/100 against Grok 4.7 (64) and GLM-5.3 (63). The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.
Which is cheaper, GLM-5.3, Grok 4.7 or Muse Spark Open?
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); Grok 4.7 costs $2.00 input / $6.00 output per million tokens (official xAI 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 $3.00 for Grok 4.7 (1.5× 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 Open 155.1 (#39 of 165) and Grok 4.7 154.6 (#43 of 165). The confidence ranges of the top two overlap (154.3–158.5 vs 153.1–157.3), so treat the gap as small. On individual benchmarks: GPQA Diamond — Grok 4.7 92.7%, GLM-5.3 90.9%, Muse Spark Open 88.6%; FrontierMath Tiers 1–3 — Muse Spark Open 69.8%, GLM-5.3 68.8%, Grok 4.7 53.0%; OTIS Mock AIME 2024–2025 — Grok 4.7 98.1%, Muse Spark Open 98.1%, GLM-5.3 91.1%; SimpleQA Verified — Muse Spark Open 56.6%, Grok 4.7 56.0%, GLM-5.3 41.0%.
Which is better for coding?
There are no published SWE-bench Verified results for GLM-5.3, Grok 4.7 and Muse Spark Open 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 Open has the largest context window at 1,048,576 tokens, against 1,000,000 for GLM-5.3 and 500,000 for Grok 4.7. Maximum output per response: GLM-5.3 up to 131,072, Grok 4.7 up to 500,000, Muse Spark Open up to 131,072 tokens.
Which can read images, PDFs, audio or video?
GLM-5.3 accepts text; Grok 4.7 accepts text, images and PDFs; Muse Spark Open 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; Grok 4.7 is proprietary.
Which is newer?
Muse Spark Open is the newest, released Oct 15, 2026. Grok 4.7 came out Sep 21, 2026; GLM-5.3 came out Aug 14, 2026. Knowledge cutoff: Grok 4.7 May 2026, 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.
