ZMIME
Comparison · 3 models · Updated Oct 4, 2026

Gemini 3.7 Flash vs Muse Spark 1.3 vs GLM-5.3

Too close to call on our weighted score (Gemini 3.7 Flash 75, Muse Spark 1.3 73, GLM-5.3 64). The right pick depends on what you value most.

  1. Google

    Gemini 3.7 Flash

    Released Aug 13, 2026

    75/100
    • ECI157.4
    • Price$0.75 / $3.75
    • Context1.05M
  2. Meta

    Muse Spark 1.3

    Released Sep 2, 2026

    73/100
    • ECI156.9
    • Price$1.25 / $4.25
    • Context1.05M
  3. Z.ai (Zhipu)

    GLM-5.3

    Released Aug 14, 2026

    64/100
    • ECI155.8
    • Price$1.40 / $4.40
    • Context1M
01 — Verdict

Too close to call

It is close. Our weighted score puts them within 2 points (Gemini 3.7 Flash 75/100, Muse Spark 1.3 73/100, GLM-5.3 64/100), so choose by what matters most for your work: Gemini 3.7 Flash for raw capability. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.

  • CapabilityGemini 3.7 FlashCapabilities Index (ECI): Gemini 3.7 Flash 157.4 · Muse Spark 1.3 156.9 · GLM-5.3 155.8
  • Lowest priceGemini 3.7 FlashGemini 3.7 Flash $1.50 · Muse Spark 1.3 $2.00 · GLM-5.3 $2.15 per 1M tokens (3:1 blend)
  • Longest contextGemini 3.7 Flash and Muse Spark 1.3Gemini 3.7 Flash 1,048,576 · Muse Spark 1.3 1,048,576 · GLM-5.3 1,000,000 tokens
  • Widest inputsGemini 3.7 Flash and Muse Spark 1.3Gemini 3.7 Flash: Text, Images, PDFs, Audio, Video · Muse Spark 1.3: Text, Images, PDFs, Audio, Video · GLM-5.3: Text
  • Self-hostingGLM-5.3Publishes downloadable weights
How the score is built
MeasureWeightGemini 3.7 FlashMuse Spark 1.3GLM-5.3
CapabilityCapabilities Index (ECI)50%888785
Price25%423634
Inputs & features15%10010045
Context window10%616160
Overall100%75/10073/10064/100
02 — Side by side

Every spec in one table

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

Gemini 3.7 Flash vs Muse Spark 1.3 vs GLM-5.3 specifications side by side
SpecificationGemini 3.7 FlashGoogleMuse Spark 1.3MetaGLM-5.3Z.ai (Zhipu)
Capability
Capabilities Index (ECI)157.4 (best)156.9155.8
ECI rank#14 of 148 (best)#17 of 148#24 of 148
GPQA DiamondGraduate-level science questions94.8% (best)—90.9%
FrontierMath Tiers 1–3Research-level mathematics71.6%74.4% (best)68.8%
OTIS Mock AIME 2024–2025Competition mathematics97.2%99.2% (best)91.1%
SimpleQA VerifiedShort factual questions69.2% (best)—41.0%
Price per million tokens
Input$0.75 (best)$1.25$1.40
Output$3.75 (best)$4.25$4.40
Cached input$0.075 (best)$0.15$0.26
Blended (3:1)$1.50 (best)$2.00$2.15
Long-context rateSame rateSame rateSame rate
Price sourceOfficial Google APIOfficial Meta APIOfficial Z.AI API
Limits
Context window1,048,576 tokens (best)1,048,576 tokens (best)1,000,000 tokens
Max output65,536 tokens131,072 tokens (best)131,072 tokens (best)
Inputs and features
TextYesYesYes
ImagesYesYesNo
PDFsYesYesNo
AudioYesYesNo
VideoYesYesNo
ReasoningYeslow · medium · highYesminimal · low · medium · high · xhigh · maxYeslow · high · max
Tool callingYesYesYes
Structured outputYesYesYes
Availability
WeightsProprietaryProprietaryOpen
API model IDgemini-3.7-flashmuse-spark-1.3glm-5.3
API providers241262 (best)
ReleasedAug 13, 2026Sep 2, 2026Aug 14, 2026
Knowledge cutoffMar 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.

  • Gemini 3.7 Flash$15.00
  • Muse Spark 1.3$21.00
  • GLM-5.3$22.80
04 — Questions

Which should you choose?

Which is better: Gemini 3.7 Flash, Muse Spark 1.3 or GLM-5.3?

It is close. Our weighted score puts them within 2 points (Gemini 3.7 Flash 75/100, Muse Spark 1.3 73/100, GLM-5.3 64/100), so choose by what matters most for your work: Gemini 3.7 Flash for raw capability. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.

Which is cheaper, Gemini 3.7 Flash, Muse Spark 1.3 or GLM-5.3?

Gemini 3.7 Flash is cheaper at $0.75 input / $3.75 output per million tokens (official Google API price). Muse Spark 1.3 costs $1.25 input / $4.25 output per million tokens (official Meta API price); GLM-5.3 costs $1.40 input / $4.40 output per million tokens (official Z.AI API price). At a typical mix of three input tokens to one output token, that is $1.50 per million tokens for Gemini 3.7 Flash versus $2.00 for Muse Spark 1.3 (1.3× as much) and $2.15 for GLM-5.3 (1.4× as much).

Which scores higher on benchmarks?

Gemini 3.7 Flash scores higher on the Capabilities Index (ECI): Gemini 3.7 Flash 157.4 (#14 of 148), Muse Spark 1.3 156.9 (#17 of 148) and GLM-5.3 155.8 (#24 of 148). The confidence ranges of the top two overlap (155.4–160.1 vs 154.7–159.6), so treat the gap as small. On individual benchmarks: FrontierMath Tiers 1–3 — Muse Spark 1.3 74.4%, Gemini 3.7 Flash 71.6%, GLM-5.3 68.8%; OTIS Mock AIME 2024–2025 — Muse Spark 1.3 99.2%, Gemini 3.7 Flash 97.2%, GLM-5.3 91.1%.

Which is better for coding?

There are no published SWE-bench Verified results for Gemini 3.7 Flash, Muse Spark 1.3 and GLM-5.3 yet, so there is no like-for-like coding score. On overall capability, Gemini 3.7 Flash 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?

Gemini 3.7 Flash and Muse Spark 1.3 have the largest context windows (1,048,576 and 1,048,576 tokens), against 1,000,000 for GLM-5.3. Maximum output per response: Gemini 3.7 Flash up to 65,536, Muse Spark 1.3 up to 131,072, GLM-5.3 up to 131,072 tokens.

Which can read images, PDFs, audio or video?

Gemini 3.7 Flash accepts text, images, PDFs, audio and video; Muse Spark 1.3 accepts text, images, PDFs, audio and video; GLM-5.3 accepts text. Gemini 3.7 Flash handles the widest range of inputs.

Are any of these open source?

GLM-5.3 publishes its weights and can be self-hosted; Gemini 3.7 Flash and Muse Spark 1.3 is proprietary.

Which is newer?

Muse Spark 1.3 is the newest, released Sep 2, 2026. GLM-5.3 came out Aug 14, 2026; Gemini 3.7 Flash came out Aug 13, 2026. Knowledge cutoff: Gemini 3.7 Flash 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 Oct 4, 2026.