ZMIME
Comparison · 3 models · Updated Nov 2, 2026

Muse Wonder vs Gemini 4 Argon vs GPT-5.6 Sol

Gemini 4 Argon comes out ahead, 74 to 68 and 66 on our weighted score, and it is the cheaper option too.

  1. Meta

    Muse Wonder

    Released Oct 12, 2026New

    68/100
    • ECI161.7
    • Price$4.00 / $20.00
    • Context1.05M
    Full specs Remove Muse Wonder
  2. Our pick

    Google

    Gemini 4 Argon

    Released Oct 13, 2026New

    74/100
    • ECI166.1
    • Price$2.00 / $10.00
    • Context1.05M
    Full specs Remove Gemini 4 Argon

  3. OpenAI

    GPT-5.6 Sol

    Released Jul 9, 2026

    66/100
    • ECI162.6
    • Price$4.00 / $20.00
    • Context1.05M
    Full specs Remove GPT-5.6 Sol
01 — Verdict

Gemini 4 Argon is our pick

Gemini 4 Argon is the better all-round choice, scoring 74/100 against Muse Wonder (68) and GPT-5.6 Sol (66). It leads on capability and price. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.

  • CapabilityGemini 4 ArgonCapabilities Index (ECI): Gemini 4 Argon 166.1 · GPT-5.6 Sol 162.6 · Muse Wonder 161.7
  • Lowest priceGemini 4 ArgonGemini 4 Argon $4.00 · Muse Wonder $8.00 · GPT-5.6 Sol $8.00 per 1M tokens (3:1 blend)
  • Longest contextAbout the sameGPT-5.6 Sol 1,050,000 · Muse Wonder 1,048,576 · Gemini 4 Argon 1,048,576 tokens
  • Widest inputsMuse Wonder and Gemini 4 ArgonMuse Wonder: Text, Images, PDFs, Audio, Video · Gemini 4 Argon: Text, Images, PDFs, Audio, Video · GPT-5.6 Sol: Text, Images, PDFs
  • Self-hostingNo open weightsAll three are available only through APIs
How the score is built
MeasureWeightMuse WonderGemini 4 ArgonGPT-5.6 Sol
CapabilityCapabilities Index (ECI)50%919692
Price25%7207
Inputs & features15%10010080
Context window10%616161
Overall100%68/10074/10066/100
02 — Side by side

Every spec in one table

Highlighted cells lead their row. Dashes mean the data is not published.

Muse Wonder vs Gemini 4 Argon vs GPT-5.6 Sol specifications side by side
SpecificationMuse WonderMetaGemini 4 ArgonGoogleGPT-5.6 SolOpenAI
Capability
Capabilities Index (ECI)161.7166.1 (best)162.6
ECI rank#13 of 165#7 of 165 (best)#12 of 165
GPQA DiamondGraduate-level science questions—96.4% (best)93.5%
FrontierMath Tiers 1–3Research-level mathematics82.1%86.0%89.1% (best)
OTIS Mock AIME 2024–2025Competition mathematics99.4%100% (best)100% (best)
SimpleQA VerifiedShort factual questions—76.0% (best)69.7%
Price per million tokens
Input$4.00$2.00 (best)$4.00
Output$20.00$10.00 (best)$20.00
Cached input$0.20$0.10 (best)$0.40
Blended (3:1)$8.00$4.00 (best)$8.00
Long-context rateSame rateSame rateOver 272K: $8.00 / $30.00
Price sourceOfficial Meta APIOfficial Google APIOfficial OpenAI API
Limits
Context window1,048,576 tokens1,048,576 tokens1,050,000 tokens (best)
Max output131,072 tokens (best)65,536 tokens128,000 tokens
Inputs and features
TextYesYesYes
ImagesYesYesYes
PDFsYesYesYes
AudioYesYesNo
VideoYesYesNo
ReasoningYesminimal · low · medium · high · xhigh · maxYeslow · medium · highYeslow · medium · high · xhigh · max
Tool callingYesYesYes
Structured outputYesYesYes
Availability
WeightsProprietaryProprietaryProprietary
API model IDmuse-wonder-1.0gemini-4-argongpt-5.6-sol
API providers92449 (best)
ReleasedOct 12, 2026Oct 13, 2026Jul 9, 2026
Knowledge cutoff—Mar 2026Feb 16, 2026
03 — Cost

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
  • Gemini 4 Argon$40.00
  • GPT-5.6 Sol$80.00
04 — Questions

Which should you choose?

Which is better: Muse Wonder, Gemini 4 Argon or GPT-5.6 Sol?

Gemini 4 Argon is the better all-round choice, scoring 74/100 against Muse Wonder (68) and GPT-5.6 Sol (66). It leads on capability and price. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.

Which is cheaper, Muse Wonder, Gemini 4 Argon or GPT-5.6 Sol?

Gemini 4 Argon is cheaper at $2.00 input / $10.00 output per million tokens (official Google API price). Muse Wonder costs $4.00 input / $20.00 output per million tokens (official Meta API price); GPT-5.6 Sol costs $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 $4.00 per million tokens for Gemini 4 Argon versus $8.00 for Muse Wonder (2× as much) and $8.00 for GPT-5.6 Sol (2× as much).

Which scores higher on benchmarks?

Gemini 4 Argon scores higher on the Capabilities Index (ECI): Gemini 4 Argon 166.1 (#7 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 (163.1–170.3 vs 159.6–166.2), so treat the gap as small. On individual benchmarks: FrontierMath Tiers 1–3 — GPT-5.6 Sol 89.1%, Gemini 4 Argon 86.0%, Muse Wonder 82.1%; OTIS Mock AIME 2024–2025 — Gemini 4 Argon 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, Gemini 4 Argon and GPT-5.6 Sol yet, so there is no like-for-like coding score. On overall capability, Gemini 4 Argon 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?

Their context windows are effectively the same size: Muse Wonder 1,048,576, Gemini 4 Argon 1,048,576 and GPT-5.6 Sol 1,050,000 tokens. Maximum output per response: Muse Wonder up to 131,072, Gemini 4 Argon up to 65,536, 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; Gemini 4 Argon accepts text, images, PDFs, audio and video; 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, Gemini 4 Argon and GPT-5.6 Sol are proprietary and only available through APIs and apps.

Which is newer?

Gemini 4 Argon is the newest, released Oct 13, 2026. Muse Wonder came out Oct 12, 2026; GPT-5.6 Sol came out Jul 9, 2026. Knowledge cutoff: Gemini 4 Argon Mar 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.

05 — Keep comparing

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