GLM-5.3 vs Muse Spark 1.2 vs Claude Sonnet 5.5
Too close to call on our weighted score (Claude Sonnet 5.5 72, Muse Spark 1.2 71, 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
Meta
Muse Spark 1.2
71/100- ECI155.2
- Price$1.25 / $4.25
- Context1.05M
Anthropic
Claude Sonnet 5.5
72/100- ECI166.7
- Price$2.00 / $10.00
- Context1M
Too close to call
It is close. Our weighted score puts them within a point (Claude Sonnet 5.5 72/100, Muse Spark 1.2 71/100, GLM-5.3 63/100), so choose by what matters most for your work: Claude Sonnet 5.5 for raw capability, Muse Spark 1.2 on price and Muse Spark 1.2 for long inputs. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.
- CapabilityClaude Sonnet 5.5Capabilities Index (ECI): Claude Sonnet 5.5 166.7 · GLM-5.3 156.2 · Muse Spark 1.2 155.2
- Lowest priceMuse Spark 1.2Muse Spark 1.2 $2.00 · GLM-5.3 $2.15 · Claude Sonnet 5.5 $4.00 per 1M tokens (3:1 blend)
- Longest contextMuse Spark 1.2Muse Spark 1.2 1,048,576 · GLM-5.3 1,000,000 · Claude Sonnet 5.5 1,000,000 tokens
- Widest inputsMuse Spark 1.2GLM-5.3: Text · Muse Spark 1.2: Text, Images, PDFs, Audio, Video · Claude Sonnet 5.5: Text, Images, PDFs
- Self-hostingGLM-5.3Publishes downloadable weights
| Measure | Weight | GLM-5.3 | Muse Spark 1.2 | Claude Sonnet 5.5 |
|---|---|---|---|---|
| CapabilityCapabilities Index (ECI) | 50% | 84 | 83 | 97 |
| Price | 25% | 33 | 34 | 20 |
| Inputs & features | 15% | 45 | 100 | 80 |
| Context window | 10% | 60 | 61 | 60 |
| Overall | 100% | 63/100 | 71/100 | 72/100 |
Every spec in one table
Highlighted cells lead their row. Dashes mean the data is not published.
| Specification | |||
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | 156.2 | 155.2 | 166.7 (best) |
| ECI rank | #33 of 165 | #38 of 165 | #5 of 165 (best) |
| GPQA DiamondGraduate-level science questions | 90.9% | — | 95.6% (best) |
| FrontierMath Tiers 1–3Research-level mathematics | 68.8% | — | 88.8% (best) |
| OTIS Mock AIME 2024–2025Competition mathematics | 91.1% | — | 100% (best) |
| SimpleQA VerifiedShort factual questions | 41.0% | 60.3% (best) | 46.5% |
| Price per million tokens | |||
| Input | $1.40 | $1.25 (best) | $2.00 |
| Output | $4.40 | $4.25 (best) | $10.00 |
| Cached input | $0.26 | $0.15 | $0.10 (best) |
| Blended (3:1) | $2.15 | $2.00 (best) | $4.00 |
| Long-context rate | Same rate | Same rate | Same rate |
| Price source | Official Z.AI API | Official Meta API | Official Anthropic API |
| Limits | |||
| Context window | 1,000,000 tokens | 1,048,576 tokens (best) | 1,000,000 tokens |
| Max output | 131,072 tokens (best) | 131,072 tokens (best) | 128,000 tokens |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | No | Yes | Yes |
| PDFs | No | Yes | Yes |
| Audio | No | Yes | No |
| Video | No | Yes | No |
| Reasoning | Yeslow · high · max | Yesminimal · low · medium · high · xhigh | Yeslow · medium · high · xhigh · max |
| Tool calling | Yes | Yes | Yes |
| Structured output | Yes | Yes | Yes |
| Availability | |||
| Weights | Open | Proprietary | Proprietary |
| API model ID | glm-5.3 | muse-spark-1.2 | claude-sonnet-5-5 |
| API providers | 83 (best) | 18 | 34 |
| Released | Aug 14, 2026 | Aug 5, 2026 | Sep 28, 2026 |
| Knowledge cutoff | — | — | Jun 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 1.2$21.00
Claude Sonnet 5.5$40.00
Which should you choose?
Which is better: GLM-5.3, Muse Spark 1.2 or Claude Sonnet 5.5?
It is close. Our weighted score puts them within a point (Claude Sonnet 5.5 72/100, Muse Spark 1.2 71/100, GLM-5.3 63/100), so choose by what matters most for your work: Claude Sonnet 5.5 for raw capability, Muse Spark 1.2 on price and Muse Spark 1.2 for long inputs. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.
Which is cheaper, GLM-5.3, Muse Spark 1.2 or Claude Sonnet 5.5?
Muse Spark 1.2 is cheaper at $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); Claude Sonnet 5.5 costs $2.00 input / $10.00 output per million tokens (official Anthropic 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 $2.15 for GLM-5.3 (1.1× as much) and $4.00 for Claude Sonnet 5.5 (2× as much).
Which scores higher on benchmarks?
Claude Sonnet 5.5 scores higher on the Capabilities Index (ECI): Claude Sonnet 5.5 166.7 (#5 of 165), GLM-5.3 156.2 (#33 of 165) and Muse Spark 1.2 155.2 (#38 of 165). Their confidence ranges do not overlap (163.6–171.3 vs 154.3–158.5), so the gap is a real one. On individual benchmarks: SimpleQA Verified — Muse Spark 1.2 60.3%, Claude Sonnet 5.5 46.5%, GLM-5.3 41.0%.
Which is better for coding?
There are no published SWE-bench Verified results for GLM-5.3, Muse Spark 1.2 and Claude Sonnet 5.5 yet, so there is no like-for-like coding score. On overall capability, Claude Sonnet 5.5 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 has the largest context window at 1,048,576 tokens, against 1,000,000 for GLM-5.3 and 1,000,000 for Claude Sonnet 5.5. Maximum output per response: GLM-5.3 up to 131,072, Muse Spark 1.2 up to 131,072, Claude Sonnet 5.5 up to 128,000 tokens.
Which can read images, PDFs, audio or video?
GLM-5.3 accepts text; Muse Spark 1.2 accepts text, images, PDFs, audio and video; Claude Sonnet 5.5 accepts text, images and PDFs. Muse Spark 1.2 handles the widest range of inputs.
Are any of these open source?
GLM-5.3 publishes its weights and can be self-hosted; Muse Spark 1.2 and Claude Sonnet 5.5 is proprietary.
Which is newer?
Claude Sonnet 5.5 is the newest, released Sep 28, 2026. GLM-5.3 came out Aug 14, 2026; Muse Spark 1.2 came out Aug 5, 2026. Knowledge cutoff: Claude Sonnet 5.5 Jun 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.