ZMIME
Comparison · 3 models · Updated Nov 2, 2026

GPT-5.6 Sol vs Gemini 4 Argon vs Muse Wonder

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

  1. 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
  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. Meta

    Muse Wonder

    Released Oct 12, 2026New

    68/100
    • ECI161.7
    • Price$4.00 / $20.00
    • Context1.05M
    Full specs Remove Muse Wonder
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 · GPT-5.6 Sol $8.00 · Muse Wonder $8.00 per 1M tokens (3:1 blend)
  • Longest contextAbout the sameGPT-5.6 Sol 1,050,000 · Gemini 4 Argon 1,048,576 · Muse Wonder 1,048,576 tokens
  • Widest inputsGemini 4 Argon and Muse WonderGPT-5.6 Sol: Text, Images, PDFs · Gemini 4 Argon: Text, Images, PDFs, Audio, Video · Muse Wonder: Text, Images, PDFs, Audio, Video
  • Self-hostingNo open weightsAll three are available only through APIs
How the score is built
MeasureWeightGPT-5.6 SolGemini 4 ArgonMuse Wonder
CapabilityCapabilities Index (ECI)50%929691
Price25%7207
Inputs & features15%80100100
Context window10%616161
Overall100%66/10074/10068/100
02 — Side by side

Every spec in one table

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

GPT-5.6 Sol vs Gemini 4 Argon vs Muse Wonder specifications side by side
SpecificationGPT-5.6 SolOpenAIGemini 4 ArgonGoogleMuse WonderMeta
Capability
Capabilities Index (ECI)162.6166.1 (best)161.7
ECI rank#12 of 165#7 of 165 (best)#13 of 165
GPQA DiamondGraduate-level science questions93.5%96.4% (best)—
FrontierMath Tiers 1–3Research-level mathematics89.1% (best)86.0%82.1%
OTIS Mock AIME 2024–2025Competition mathematics100% (best)100% (best)99.4%
SimpleQA VerifiedShort factual questions69.7%76.0% (best)—
Price per million tokens
Input$4.00$2.00 (best)$4.00
Output$20.00$10.00 (best)$20.00
Cached input$0.40$0.10 (best)$0.20
Blended (3:1)$8.00$4.00 (best)$8.00
Long-context rateOver 272K: $8.00 / $30.00Same rateSame rate
Price sourceOfficial OpenAI APIOfficial Google APIOfficial Meta API
Limits
Context window1,050,000 tokens (best)1,048,576 tokens1,048,576 tokens
Max output128,000 tokens65,536 tokens131,072 tokens (best)
Inputs and features
TextYesYesYes
ImagesYesYesYes
PDFsYesYesYes
AudioNoYesYes
VideoNoYesYes
ReasoningYeslow · medium · high · xhigh · maxYeslow · medium · highYesminimal · low · medium · high · xhigh · max
Tool callingYesYesYes
Structured outputYesYesYes
Availability
WeightsProprietaryProprietaryProprietary
API model IDgpt-5.6-solgemini-4-argonmuse-wonder-1.0
API providers49 (best)249
ReleasedJul 9, 2026Oct 13, 2026Oct 12, 2026
Knowledge cutoffFeb 16, 2026Mar 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.

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

Which should you choose?

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

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

Gemini 4 Argon is cheaper at $2.00 input / $10.00 output per million tokens (official Google 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 $4.00 per million tokens for Gemini 4 Argon versus $8.00 for GPT-5.6 Sol (2× as much) and $8.00 for Muse Wonder (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 — GPT-5.6 Sol 100%, Gemini 4 Argon 100%, Muse Wonder 99.4%.

Which is better for coding?

There are no published SWE-bench Verified results for GPT-5.6 Sol, Gemini 4 Argon and Muse Wonder 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: GPT-5.6 Sol 1,050,000, Gemini 4 Argon 1,048,576 and Muse Wonder 1,048,576 tokens. Maximum output per response: GPT-5.6 Sol up to 128,000, Gemini 4 Argon up to 65,536, Muse Wonder up to 131,072 tokens.

Which can read images, PDFs, audio or video?

GPT-5.6 Sol accepts text, images and PDFs; Gemini 4 Argon accepts text, images, PDFs, audio and video; Muse Wonder accepts text, images, PDFs, audio and video. Gemini 4 Argon handles the widest range of inputs.

Are any of these open source?

No. GPT-5.6 Sol, Gemini 4 Argon and Muse Wonder 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: GPT-5.6 Sol Feb 16, 2026, Gemini 4 Argon Mar 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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