GPT-5.6 Sol vs Muse Wonder Full vs Muse Wonder
Muse Wonder comes out ahead, 84 to 72 and 72 on our weighted score.
OpenAIGPT-5.6 Sol
72/100- ECI162.6
- Price$4.00 / $20.00
- Context1.05M
MetaMuse Wonder Full
72/100- ECI—
- Price—
- Context1.05M
- Our pickMeta
Muse Wonder
84/100- ECI161.7
- Price$4.00 / $20.00
- Context1.05M
Muse Wonder is our pick
Muse Wonder is the better all-round choice, scoring 84/100 against GPT-5.6 Sol (72) and Muse Wonder Full (72). It leads on inputs & features. 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 Sol and Muse WonderGPT-5.6 Sol $8.00 · Muse Wonder $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 · Muse Wonder 1,048,576 tokens
- Widest inputsMuse WonderGPT-5.6 Sol: Text, Images, PDFs · Muse Wonder Full: Text, Images, Audio, Video · Muse Wonder: Text, Images, PDFs, Audio, Video
- Self-hostingNo open weightsAll three are available only through APIs
| Measure | Weight | GPT-5.6 Sol | Muse Wonder Full | Muse Wonder |
|---|---|---|---|---|
| Inputs & features | 60% | 80 | 80 | 100 |
| Context window | 40% | 61 | 61 | 61 |
| Overall | 100% | 72/100 | 72/100 | 84/100 |
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 | GPT-5.6 SolOpenAI | Muse Wonder FullMeta | Muse WonderMeta |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | 162.6 (best) | — | 161.7 |
| ECI rank | #12 of 165 (best) | — | #13 of 165 |
| GPQA DiamondGraduate-level science questions | 93.5% | — | — |
| FrontierMath Tiers 1–3Research-level mathematics | 89.1% (best) | — | 82.1% |
| OTIS Mock AIME 2024–2025Competition mathematics | 100% (best) | — | 99.4% |
| SimpleQA VerifiedShort factual questions | 69.7% | — | — |
| Price per million tokens | |||
| Input | $4.00 | — | $4.00 |
| Output | $20.00 | — | $20.00 |
| Cached input | $0.40 | — | $0.20 (best) |
| Blended (3:1) | $8.00 | — | $8.00 |
| Long-context rate | Over 272K: $8.00 / $30.00 | — | Same rate |
| Price source | Official OpenAI API | — | Official Meta API |
| Limits | |||
| Context window | 1,050,000 tokens (best) | 1,048,576 tokens | 1,048,576 tokens |
| Max output | 128,000 tokens | — | 131,072 tokens (best) |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | Yes | Yes | Yes |
| PDFs | Yes | No | Yes |
| Audio | No | Yes | Yes |
| Video | No | Yes | Yes |
| Reasoning | Yeslow · medium · high · xhigh · max | Yes | Yesminimal · low · medium · high · xhigh · max |
| Tool calling | Yes | Yes | Yes |
| Structured output | Yes | No | Yes |
| Availability | |||
| Weights | Proprietary | Proprietary | Proprietary |
| API model ID | gpt-5.6-sol | — | muse-wonder-1.0 |
| API providers | 49 (best) | — | 9 |
| Released | Jul 9, 2026 | Oct 12, 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
- Muse Wonder Full—
- Muse Wonder$80.00
Which should you choose?
Which is better: GPT-5.6 Sol, Muse Wonder Full or Muse Wonder?
Muse Wonder is the better all-round choice, scoring 84/100 against GPT-5.6 Sol (72) and Muse Wonder Full (72). It leads on inputs & features. 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, GPT-5.6 Sol, Muse Wonder Full or Muse Wonder?
GPT-5.6 Sol is cheaper at $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 $8.00 per million tokens for GPT-5.6 Sol versus $8.00 for Muse Wonder (1× as much). Muse Wonder Full has no published per-token price.
Which scores higher on benchmarks?
There is no independent benchmark that covers all three models yet. GPT-5.6 Sol has an ECI of 162.6, Muse Wonder Full has not been scored yet and Muse Wonder has an ECI of 161.7.
Which is better for coding?
There are no published SWE-bench Verified results for GPT-5.6 Sol, Muse Wonder Full and Muse Wonder 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?
Their context windows are effectively the same size: GPT-5.6 Sol 1,050,000, Muse Wonder Full 1,048,576 and Muse Wonder 1,048,576 tokens. Maximum output per response: GPT-5.6 Sol up to 128,000, Muse Wonder up to 131,072 tokens.
Which can read images, PDFs, audio or video?
GPT-5.6 Sol accepts text, images and PDFs; Muse Wonder Full accepts text, images, audio and video; Muse Wonder accepts text, images, PDFs, audio and video. Muse Wonder handles the widest range of inputs.
Are any of these open source?
No. GPT-5.6 Sol, Muse Wonder Full and Muse Wonder are proprietary and only available through APIs and apps.
Which is newer?
Muse Wonder Full is the newest, released Oct 12, 2026. Muse Wonder came out 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.
