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Comparison · 3 models · Updated Oct 4, 2026

Gemini 3.6 Flash vs DeepSeek-R1 vs Muse Spark 1.1

Too close to call on our weighted score (Gemini 3.6 Flash 73, Muse Spark 1.1 70, DeepSeek-R1 51). The right pick depends on what you value most.

  1. Google

    Gemini 3.6 Flash

    Released Jul 21, 2026

    73/100
    • ECI154.3
    • Price$0.75 / $3.75
    • Context1.05M
    Full specs Remove Gemini 3.6 Flash

  2. DeepSeek

    DeepSeek-R1

    Released Jan 20, 2025

    51/100
    • ECI139.0
    • Price$0.70 / $2.60
    • Context128K
    Full specs Remove DeepSeek-R1

  3. Meta

    Muse Spark 1.1

    Released Jul 9, 2026

    70/100
    • ECI154.3
    • Price$1.25 / $4.25
    • Context1.05M
    Full specs Remove Muse Spark 1.1
01 — Verdict

Too close to call

It is close. Our weighted score puts them within 3 points (Gemini 3.6 Flash 73/100, Muse Spark 1.1 70/100, DeepSeek-R1 51/100), so choose by what matters most for your work: Gemini 3.6 Flash for raw capability and DeepSeek-R1 on price. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.

  • CapabilityGemini 3.6 FlashCapabilities Index (ECI): Gemini 3.6 Flash 154.3 · Muse Spark 1.1 154.3 · DeepSeek-R1 139.0
  • Lowest priceDeepSeek-R1DeepSeek-R1 $1.18 · Gemini 3.6 Flash $1.50 · Muse Spark 1.1 $2.00 per 1M tokens (3:1 blend)
  • Longest contextGemini 3.6 Flash and Muse Spark 1.1Gemini 3.6 Flash 1,048,576 · Muse Spark 1.1 1,048,576 · DeepSeek-R1 128,000 tokens
  • Widest inputsGemini 3.6 FlashGemini 3.6 Flash: Text, Images, PDFs, Audio, Video · DeepSeek-R1: Text · Muse Spark 1.1: Text, Images, PDFs, Video
  • Self-hostingDeepSeek-R1Publishes downloadable weights
How the score is built
MeasureWeightGemini 3.6 FlashDeepSeek-R1Muse Spark 1.1
CapabilityCapabilities Index (ECI)50%846484
Price25%424736
Inputs & features15%1003590
Context window10%612461
Overall100%73/10051/10070/100
02 — Side by side

Every spec in one table

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

Gemini 3.6 Flash vs DeepSeek-R1 vs Muse Spark 1.1 specifications side by side
SpecificationGemini 3.6 FlashGoogleDeepSeek-R1DeepSeekMuse Spark 1.1Meta
Capability
Capabilities Index (ECI)154.3 (best)139.0154.3
ECI rank#34 of 148 (best)#104 of 148#35 of 148
GPQA DiamondGraduate-level science questions94.1% (best)71.7%—
FrontierMath Tiers 1–3Research-level mathematics59.0%——
OTIS Mock AIME 2024–2025Competition mathematics94.2% (best)53.3%—
SimpleQA VerifiedShort factual questions66.2% (best)—57.8%
Price per million tokens
Input$0.75$0.70 (best)$1.25
Output$3.75$2.60 (best)$4.25
Cached input$0.075 (best)—$0.15
Blended (3:1)$1.50$1.18 (best)$2.00
Long-context rateSame rateSame rateSame rate
Price sourceOfficial Google APIMedian of 11 providersOfficial Meta API
Limits
Context window1,048,576 tokens (best)128,000 tokens1,048,576 tokens (best)
Max output65,536 tokens32,768 tokens131,072 tokens (best)
Inputs and features
TextYesYesYes
ImagesYesNoYes
PDFsYesNoYes
AudioYesNoNo
VideoYesNoYes
ReasoningYesminimal · low · medium · highYesYesminimal · low · medium · high · xhigh
Tool callingYesYesYes
Structured outputYesNoYes
Availability
WeightsProprietaryOpenProprietary
API model IDgemini-3.6-flash—muse-spark-1.1
API providers25 (best)1213
ReleasedJul 21, 2026Jan 20, 2025Jul 9, 2026
Knowledge cutoffMar 2026Jul 2024—
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 3.6 Flash$15.00
  • DeepSeek-R1$12.20
  • Muse Spark 1.1$21.00
04 — Questions

Which should you choose?

Which is better: Gemini 3.6 Flash, DeepSeek-R1 or Muse Spark 1.1?

It is close. Our weighted score puts them within 3 points (Gemini 3.6 Flash 73/100, Muse Spark 1.1 70/100, DeepSeek-R1 51/100), so choose by what matters most for your work: Gemini 3.6 Flash for raw capability and DeepSeek-R1 on price. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.

Which is cheaper, Gemini 3.6 Flash, DeepSeek-R1 or Muse Spark 1.1?

DeepSeek-R1 is cheaper at $0.70 input / $2.60 output per million tokens (median across 11 API providers). Gemini 3.6 Flash costs $0.75 input / $3.75 output per million tokens (official Google API price); Muse Spark 1.1 costs $1.25 input / $4.25 output per million tokens (official Meta API price). At a typical mix of three input tokens to one output token, that is $1.18 per million tokens for DeepSeek-R1 versus $1.50 for Gemini 3.6 Flash (1.3× as much) and $2.00 for Muse Spark 1.1 (1.7× as much).

Which scores higher on benchmarks?

Gemini 3.6 Flash scores higher on the Capabilities Index (ECI): Gemini 3.6 Flash 154.3 (#34 of 148), Muse Spark 1.1 154.3 (#35 of 148) and DeepSeek-R1 139.0 (#104 of 148). The confidence ranges of the top two overlap (152.6–156.3 vs 152.2–157.1), so treat the gap as small.

Which is better for coding?

There are no published SWE-bench Verified results for Gemini 3.6 Flash, DeepSeek-R1 and Muse Spark 1.1 yet, so there is no like-for-like coding score. On overall capability, Gemini 3.6 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 3.6 Flash and Muse Spark 1.1 have the largest context windows (1,048,576 and 1,048,576 tokens), against 128,000 for DeepSeek-R1. Maximum output per response: Gemini 3.6 Flash up to 65,536, DeepSeek-R1 up to 32,768, Muse Spark 1.1 up to 131,072 tokens.

Which can read images, PDFs, audio or video?

Gemini 3.6 Flash accepts text, images, PDFs, audio and video; DeepSeek-R1 accepts text; Muse Spark 1.1 accepts text, images, PDFs and video. Gemini 3.6 Flash handles the widest range of inputs.

Are any of these open source?

DeepSeek-R1 publishes its weights and can be self-hosted; Gemini 3.6 Flash and Muse Spark 1.1 is proprietary.

Which is newer?

Gemini 3.6 Flash is the newest, released Jul 21, 2026. Muse Spark 1.1 came out Jul 9, 2026; DeepSeek-R1 came out Jan 20, 2025. Knowledge cutoff: Gemini 3.6 Flash Mar 2026, DeepSeek-R1 Jul 2024.

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.

05 — Keep comparing

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