Muse Wonder vs Claude Opus 5.5 vs GPT-5.6 Sol
Too close to call on our weighted score (Claude Opus 5.5 69, Muse Wonder 68, GPT-5.6 Sol 66). The right pick depends on what you value most.
MetaMuse Wonder
68/100- ECI161.7
- Price$4.00 / $20.00
- Context1.05M
AnthropicClaude Opus 5.5
69/100- ECI168.4
- Price$4.00 / $20.00
- Context1M
OpenAIGPT-5.6 Sol
66/100- ECI162.6
- Price$4.00 / $20.00
- Context1.05M
Too close to call
It is close. Our weighted score puts them within 1 points (Claude Opus 5.5 69/100, Muse Wonder 68/100, GPT-5.6 Sol 66/100), so choose by what matters most for your work: Claude Opus 5.5 for raw capability and Muse Wonder on price. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.
- CapabilityClaude Opus 5.5Capabilities Index (ECI): Claude Opus 5.5 168.4 · GPT-5.6 Sol 162.6 · Muse Wonder 161.7
- Lowest priceSame priceMuse Wonder $8.00 · Claude Opus 5.5 $8.00 · GPT-5.6 Sol $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 · Claude Opus 5.5 1,000,000 tokens
- Widest inputsMuse WonderMuse Wonder: Text, Images, PDFs, Audio, Video · Claude Opus 5.5: Text, Images, PDFs · GPT-5.6 Sol: Text, Images, PDFs
- Self-hostingNo open weightsAll three are available only through APIs
| Measure | Weight | Muse Wonder | Claude Opus 5.5 | GPT-5.6 Sol |
|---|---|---|---|---|
| CapabilityCapabilities Index (ECI) | 50% | 91 | 99 | 92 |
| Price | 25% | 7 | 7 | 7 |
| Inputs & features | 15% | 100 | 80 | 80 |
| Context window | 10% | 61 | 60 | 61 |
| Overall | 100% | 68/100 | 69/100 | 66/100 |
Every spec in one table
Highlighted cells lead their row. Dashes mean the data is not published.
| Specification | Muse WonderMeta | Claude Opus 5.5Anthropic | GPT-5.6 SolOpenAI |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | 161.7 | 168.4 (best) | 162.6 |
| ECI rank | #13 of 165 | #2 of 165 (best) | #12 of 165 |
| GPQA DiamondGraduate-level science questions | — | 90.6% | 93.5% (best) |
| FrontierMath Tiers 1–3Research-level mathematics | 82.1% | 91.2% (best) | 89.1% |
| OTIS Mock AIME 2024–2025Competition mathematics | 99.4% | 100% (best) | 100% (best) |
| SimpleQA VerifiedShort factual questions | — | 72.2% (best) | 69.7% |
| Price per million tokens | |||
| Input | $4.00 | $4.00 | $4.00 |
| Output | $20.00 | $20.00 | $20.00 |
| Cached input | $0.20 (best) | $0.20 (best) | $0.40 |
| Blended (3:1) | $8.00 | $8.00 | $8.00 |
| Long-context rate | Same rate | Same rate | Over 272K: $8.00 / $30.00 |
| Price source | Official Meta API | Official Anthropic API | Official OpenAI API |
| Limits | |||
| Context window | 1,048,576 tokens | 1,000,000 tokens | 1,050,000 tokens (best) |
| Max output | 131,072 tokens (best) | 128,000 tokens | 128,000 tokens |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | Yes | Yes | Yes |
| PDFs | Yes | Yes | Yes |
| Audio | Yes | No | No |
| Video | Yes | No | No |
| Reasoning | Yesminimal · low · medium · high · xhigh · max | Yeslow · medium · high · xhigh · max | Yeslow · medium · high · xhigh · max |
| Tool calling | Yes | Yes | Yes |
| Structured output | Yes | Yes | Yes |
| Availability | |||
| Weights | Proprietary | Proprietary | Proprietary |
| API model ID | muse-wonder-1.0 | claude-opus-5-5 | gpt-5.6-sol |
| API providers | 9 | 36 | 49 (best) |
| Released | Oct 12, 2026 | Sep 22, 2026 | Jul 9, 2026 |
| Knowledge cutoff | — | Jun 2026 | 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$80.00
- Claude Opus 5.5$80.00
- GPT-5.6 Sol$80.00
Which should you choose?
Which is better: Muse Wonder, Claude Opus 5.5 or GPT-5.6 Sol?
It is close. Our weighted score puts them within 1 points (Claude Opus 5.5 69/100, Muse Wonder 68/100, GPT-5.6 Sol 66/100), so choose by what matters most for your work: Claude Opus 5.5 for raw capability and Muse Wonder on price. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.
Which is cheaper, Muse Wonder, Claude Opus 5.5 or GPT-5.6 Sol?
Muse Wonder, Claude Opus 5.5 and GPT-5.6 Sol cost the same: $4.00 input / $20.00 output per million tokens.
Which scores higher on benchmarks?
Claude Opus 5.5 scores higher on the Capabilities Index (ECI): Claude Opus 5.5 168.4 (#2 of 165), GPT-5.6 Sol 162.6 (#12 of 165) and Muse Wonder 161.7 (#13 of 165). The confidence ranges of the top two overlap (165.4–173.0 vs 159.6–166.2), so treat the gap as small. On individual benchmarks: FrontierMath Tiers 1–3 — Claude Opus 5.5 91.2%, GPT-5.6 Sol 89.1%, Muse Wonder 82.1%; OTIS Mock AIME 2024–2025 — Claude Opus 5.5 100%, GPT-5.6 Sol 100%, Muse Wonder 99.4%.
Which is better for coding?
There are no published SWE-bench Verified results for Muse Wonder, Claude Opus 5.5 and GPT-5.6 Sol yet, so there is no like-for-like coding score. On overall capability, Claude Opus 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?
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 Claude Opus 5.5. Maximum output per response: Muse Wonder up to 131,072, Claude Opus 5.5 up to 128,000, GPT-5.6 Sol up to 128,000 tokens.
Which can read images, PDFs, audio or video?
Muse Wonder accepts text, images, PDFs, audio and video; Claude Opus 5.5 accepts text, images and PDFs; GPT-5.6 Sol accepts text, images and PDFs. Muse Wonder handles the widest range of inputs.
Are any of these open source?
No. Muse Wonder, Claude Opus 5.5 and GPT-5.6 Sol are proprietary and only available through APIs and apps.
Which is newer?
Muse Wonder is the newest, released Oct 12, 2026. Claude Opus 5.5 came out Sep 22, 2026; GPT-5.6 Sol came out Jul 9, 2026. Knowledge cutoff: Claude Opus 5.5 Jun 2026, 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.
