Muse Wonder Full vs GPT-5.6 Sol
Too close to call on our weighted score (Muse Wonder Full 72, GPT-5.6 Sol 72). The right pick depends on what you value most.
MetaMuse Wonder Full
72/100- ECI—
- Price—
- Context1.05M
OpenAIGPT-5.6 Sol
72/100- ECI162.6
- Price$4.00 / $20.00
- Context1.05M
Add a model
Make it a three-way comparison.
Too close to call
It is close. Our weighted score puts them within a point (Muse Wonder Full 72/100, GPT-5.6 Sol 72/100), so choose by what matters most for your work: GPT-5.6 Sol on price. The score weighs inputs & features 60%, context window 40%. 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 priceGPT-5.6 SolGPT-5.6 Sol $8.00 per 1M tokens (3:1 blend) · Muse Wonder Full unpriced
- Longest contextAbout the sameGPT-5.6 Sol 1,050,000 · Muse Wonder Full 1,048,576 tokens
- Widest inputsMuse Wonder FullMuse Wonder Full: Text, Images, Audio, Video · GPT-5.6 Sol: Text, Images, PDFs
- Self-hostingNo open weightsBoth are available only through APIs
| Measure | Weight | Muse Wonder Full | GPT-5.6 Sol |
|---|---|---|---|
| Inputs & features | 60% | 80 | 80 |
| Context window | 40% | 61 | 61 |
| Overall | 100% | 72/100 | 72/100 |
Left out because at least one model lacks the data: capability and price. The remaining weights were rescaled.
Every spec in one table
Highlighted cells lead their row. Dashes mean the data is not published.
| Specification | Muse Wonder FullMeta | GPT-5.6 SolOpenAI |
|---|---|---|
| Capability | ||
| Capabilities Index (ECI) | — | 162.6 |
| ECI rank | — | #12 of 165 |
| GPQA DiamondGraduate-level science questions | — | 93.5% |
| FrontierMath Tiers 1–3Research-level mathematics | — | 89.1% |
| OTIS Mock AIME 2024–2025Competition mathematics | — | 100% |
| SimpleQA VerifiedShort factual questions | — | 69.7% |
| Price per million tokens | ||
| Input | — | $4.00 |
| Output | — | $20.00 |
| Cached input | — | $0.40 |
| Blended (3:1) | — | $8.00 |
| Long-context rate | — | Over 272K: $8.00 / $30.00 |
| Price source | — | Official OpenAI API |
| Limits | ||
| Context window | 1,048,576 tokens | 1,050,000 tokens (best) |
| Max output | — | 128,000 tokens |
| Inputs and features | ||
| Text | Yes | Yes |
| Images | Yes | Yes |
| PDFs | No | Yes |
| Audio | Yes | No |
| Video | Yes | No |
| Reasoning | Yes | Yeslow · medium · high · xhigh · max |
| Tool calling | Yes | Yes |
| Structured output | No | Yes |
| Availability | ||
| Weights | Proprietary | Proprietary |
| API model ID | — | gpt-5.6-sol |
| API providers | — | 49 |
| Released | Oct 12, 2026 | Jul 9, 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.
- Muse Wonder Full—
- GPT-5.6 Sol$80.00
Which should you choose?
Which is better: Muse Wonder Full or GPT-5.6 Sol?
It is close. Our weighted score puts them within a point (Muse Wonder Full 72/100, GPT-5.6 Sol 72/100), so choose by what matters most for your work: GPT-5.6 Sol on price. The score weighs inputs & features 60%, context window 40%. None of the shared benchmarks cover every model here yet, so capability is left out of this verdict.
Which is cheaper, Muse Wonder Full or GPT-5.6 Sol?
GPT-5.6 Sol is cheaper at $4.00 input / $20.00 output per million tokens (official OpenAI API price). . At a typical mix of three input tokens to one output token, that is $8.00 per million tokens for GPT-5.6 Sol versus . Muse Wonder Full has no published per-token price.
Which scores higher on benchmarks?
There is no independent benchmark that covers both models yet. Muse Wonder Full has not been scored yet and GPT-5.6 Sol has an ECI of 162.6.
Which is better for coding?
There are no published SWE-bench Verified results for Muse Wonder Full and GPT-5.6 Sol yet, so there is no like-for-like coding score. Test both on a sample of your own tasks. Both support tool calling for agent workflows.
Which has the bigger context window?
Their context windows are effectively the same size: Muse Wonder Full 1,048,576 and GPT-5.6 Sol 1,050,000 tokens. Maximum output per response: GPT-5.6 Sol up to 128,000 tokens.
Which can read images, PDFs, audio or video?
Muse Wonder Full accepts text, images, audio and video; GPT-5.6 Sol accepts text, images and PDFs. Muse Wonder Full handles the widest range of inputs.
Are any of these open source?
No. Muse Wonder Full and GPT-5.6 Sol are proprietary and only available through APIs and apps.
Which is newer?
Muse Wonder Full is the newest, released Oct 12, 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.
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