GPT-5.6 Sol vs GLM-5.3 vs Muse Wonder
Too close to call on our weighted score (Muse Wonder 68, GPT-5.6 Sol 66, GLM-5.3 63). The right pick depends on what you value most.
OpenAIGPT-5.6 Sol
66/100- ECI162.6
- Price$4.00 / $20.00
- Context1.05M
Z.ai (Zhipu)GLM-5.3
63/100- ECI156.2
- Price$1.40 / $4.40
- Context1M
MetaMuse 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 2 points (Muse Wonder 68/100, GPT-5.6 Sol 66/100, GLM-5.3 63/100), so choose by what matters most for your work: GPT-5.6 Sol for raw capability and GLM-5.3 on price. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.
- CapabilityGPT-5.6 SolCapabilities Index (ECI): GPT-5.6 Sol 162.6 · Muse Wonder 161.7 · GLM-5.3 156.2
- Lowest priceGLM-5.3GLM-5.3 $2.15 · GPT-5.6 Sol $8.00 · Muse Wonder $8.00 per 1M tokens (3:1 blend)
- Longest contextGPT-5.6 Sol and Muse WonderGPT-5.6 Sol 1,050,000 · Muse Wonder 1,048,576 · GLM-5.3 1,000,000 tokens
- Widest inputsMuse WonderGPT-5.6 Sol: Text, Images, PDFs · GLM-5.3: Text · Muse Wonder: Text, Images, PDFs, Audio, Video
- Self-hostingGLM-5.3Publishes downloadable weights
| Measure | Weight | GPT-5.6 Sol | GLM-5.3 | Muse Wonder |
|---|---|---|---|---|
| CapabilityCapabilities Index (ECI) | 50% | 92 | 84 | 91 |
| Price | 25% | 7 | 33 | 7 |
| Inputs & features | 15% | 80 | 45 | 100 |
| Context window | 10% | 61 | 60 | 61 |
| Overall | 100% | 66/100 | 63/100 | 68/100 |
Every spec in one table
Highlighted cells lead their row. Dashes mean the data is not published.
| Specification | GPT-5.6 SolOpenAI | GLM-5.3Z.ai (Zhipu) | Muse WonderMeta |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | 162.6 (best) | 156.2 | 161.7 |
| ECI rank | #12 of 165 (best) | #33 of 165 | #13 of 165 |
| GPQA DiamondGraduate-level science questions | 93.5% (best) | 90.9% | — |
| FrontierMath Tiers 1–3Research-level mathematics | 89.1% (best) | 68.8% | 82.1% |
| OTIS Mock AIME 2024–2025Competition mathematics | 100% (best) | 91.1% | 99.4% |
| SimpleQA VerifiedShort factual questions | 69.7% (best) | 41.0% | — |
| Price per million tokens | |||
| Input | $4.00 | $1.40 (best) | $4.00 |
| Output | $20.00 | $4.40 (best) | $20.00 |
| Cached input | $0.40 | $0.26 | $0.20 (best) |
| Blended (3:1) | $8.00 | $2.15 (best) | $8.00 |
| Long-context rate | Over 272K: $8.00 / $30.00 | Same rate | Same rate |
| Price source | Official OpenAI API | Official Z.AI API | Official Meta API |
| Limits | |||
| Context window | 1,050,000 tokens (best) | 1,000,000 tokens | 1,048,576 tokens |
| Max output | 128,000 tokens | 131,072 tokens (best) | 131,072 tokens (best) |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | Yes | No | Yes |
| PDFs | Yes | No | Yes |
| Audio | No | No | Yes |
| Video | No | No | Yes |
| Reasoning | Yeslow · medium · high · xhigh · max | Yeslow · high · max | Yesminimal · low · medium · high · xhigh · max |
| Tool calling | Yes | Yes | Yes |
| Structured output | Yes | Yes | Yes |
| Availability | |||
| Weights | Proprietary | Open | Proprietary |
| API model ID | gpt-5.6-sol | glm-5.3 | muse-wonder-1.0 |
| API providers | 49 | 83 (best) | 9 |
| Released | Jul 9, 2026 | Aug 14, 2026 | Oct 12, 2026 |
| Knowledge cutoff | Feb 16, 2026 | — | — |
What would a month cost?
Enter your expected volume in millions of tokens. List prices only; caching and batch discounts would lower these.
- GPT-5.6 Sol$80.00
- GLM-5.3$22.80
- Muse Wonder$80.00
Which should you choose?
Which is better: GPT-5.6 Sol, GLM-5.3 or Muse Wonder?
It is close. Our weighted score puts them within 2 points (Muse Wonder 68/100, GPT-5.6 Sol 66/100, GLM-5.3 63/100), so choose by what matters most for your work: GPT-5.6 Sol for raw capability and GLM-5.3 on price. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.
Which is cheaper, GPT-5.6 Sol, GLM-5.3 or Muse Wonder?
GLM-5.3 is cheaper at $1.40 input / $4.40 output per million tokens (official Z.AI API price). GPT-5.6 Sol costs $4.00 input / $20.00 output per million tokens (official OpenAI 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 $2.15 per million tokens for GLM-5.3 versus $8.00 for GPT-5.6 Sol (3.7× as much) and $8.00 for Muse Wonder (3.7× as much).
Which scores higher on benchmarks?
GPT-5.6 Sol scores higher on the Capabilities Index (ECI): GPT-5.6 Sol 162.6 (#12 of 165), Muse Wonder 161.7 (#13 of 165) and GLM-5.3 156.2 (#33 of 165). The confidence ranges of the top two overlap (159.6–166.2 vs 159.2–164.6), so treat the gap as small. On individual benchmarks: FrontierMath Tiers 1–3 — GPT-5.6 Sol 89.1%, Muse Wonder 82.1%, GLM-5.3 68.8%; OTIS Mock AIME 2024–2025 — GPT-5.6 Sol 100%, Muse Wonder 99.4%, GLM-5.3 91.1%.
Which is better for coding?
There are no published SWE-bench Verified results for GPT-5.6 Sol, GLM-5.3 and Muse Wonder yet, so there is no like-for-like coding score. On overall capability, GPT-5.6 Sol 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?
GPT-5.6 Sol and Muse Wonder have the largest context windows (1,050,000 and 1,048,576 tokens), against 1,000,000 for GLM-5.3. Maximum output per response: GPT-5.6 Sol up to 128,000, GLM-5.3 up to 131,072, Muse Wonder up to 131,072 tokens.
Which can read images, PDFs, audio or video?
GPT-5.6 Sol accepts text, images and PDFs; GLM-5.3 accepts text; 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 publishes its weights and can be self-hosted; GPT-5.6 Sol and Muse Wonder is proprietary.
Which is newer?
Muse Wonder is the newest, released Oct 12, 2026. GLM-5.3 came out Aug 14, 2026; GPT-5.6 Sol came out Jul 9, 2026. Knowledge cutoff: GPT-5.6 Sol Feb 16, 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.
