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Comparison · 2 models · Updated Oct 4, 2026

DeepSeek V4 Pro 0813 vs Muse Spark 1.3

Muse Spark 1.3 comes out ahead, 73 to 68 on our weighted score, though DeepSeek V4 Pro 0813 is 2× cheaper per token.

  1. DeepSeek

    DeepSeek V4 Pro 0813

    Released Aug 12, 2026

    68/100
    • ECI155.4
    • Price$0.66 / $1.98
    • Context1M
    Full specs Remove DeepSeek V4 Pro 0813
  2. Our pick

    Meta

    Muse Spark 1.3

    Released Sep 2, 2026

    73/100
    • ECI156.9
    • Price$1.25 / $4.25
    • Context1.05M
    Full specs Remove Muse Spark 1.3

  3. Add a model

    Make it a three-way comparison.

01 — Verdict

Muse Spark 1.3 is our pick

Muse Spark 1.3 is the better all-round choice, scoring 73/100 against DeepSeek V4 Pro 0813 (68). It leads on capability and inputs & features. DeepSeek V4 Pro 0813 wins on price. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.

  • CapabilityMuse Spark 1.3Capabilities Index (ECI): Muse Spark 1.3 156.9 · DeepSeek V4 Pro 0813 155.4
  • Lowest priceDeepSeek V4 Pro 0813DeepSeek V4 Pro 0813 $0.99 · Muse Spark 1.3 $2.00 per 1M tokens (3:1 blend)
  • Longest contextMuse Spark 1.3Muse Spark 1.3 1,048,576 · DeepSeek V4 Pro 0813 1,000,000 tokens
  • Widest inputsMuse Spark 1.3DeepSeek V4 Pro 0813: Text · Muse Spark 1.3: Text, Images, PDFs, Audio, Video
  • Self-hostingDeepSeek V4 Pro 0813Publishes downloadable weights (MIT)
How the score is built
MeasureWeightDeepSeek V4 Pro 0813Muse Spark 1.3
CapabilityCapabilities Index (ECI)50%8587
Price25%5036
Inputs & features15%45100
Context window10%6061
Overall100%68/10073/100
02 — Side by side

Every spec in one table

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

DeepSeek V4 Pro 0813 vs Muse Spark 1.3 specifications side by side
SpecificationDeepSeek V4 Pro 0813DeepSeekMuse Spark 1.3Meta
Capability
Capabilities Index (ECI)155.4156.9 (best)
ECI rank#26 of 148#17 of 148 (best)
GPQA DiamondGraduate-level science questions91.7%—
FrontierMath Tiers 1–3Research-level mathematics64.6%74.4% (best)
OTIS Mock AIME 2024–2025Competition mathematics98.6%99.2% (best)
SimpleQA VerifiedShort factual questions52.9%—
Price per million tokens
Input$0.66 (best)$1.25
Output$1.98 (best)$4.25
Cached input$0.022 (best)$0.15
Blended (3:1)$0.99 (best)$2.00
Long-context rateSame rateSame rate
Price sourceOfficial DeepSeek APIOfficial Meta API
Limits
Context window1,000,000 tokens1,048,576 tokens (best)
Max output384,000 tokens (best)131,072 tokens
Inputs and features
TextYesYes
ImagesNoYes
PDFsNoYes
AudioNoYes
VideoNoYes
ReasoningYeslow · high · maxYesminimal · low · medium · high · xhigh · max
Tool callingYesYes
Structured outputYesYes
Availability
WeightsOpenMITProprietary
API model IDdeepseek-v4-promuse-spark-1.3
API providers37 (best)12
ReleasedAug 12, 2026Sep 2, 2026
Knowledge cutoff——
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.

  • DeepSeek V4 Pro 0813$10.56
  • Muse Spark 1.3$21.00
04 — Questions

Which should you choose?

Which is better: DeepSeek V4 Pro 0813 or Muse Spark 1.3?

Muse Spark 1.3 is the better all-round choice, scoring 73/100 against DeepSeek V4 Pro 0813 (68). It leads on capability and inputs & features. DeepSeek V4 Pro 0813 wins on price. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.

Which is cheaper, DeepSeek V4 Pro 0813 or Muse Spark 1.3?

DeepSeek V4 Pro 0813 is cheaper at $0.66 input / $1.98 output per million tokens (official DeepSeek API price). Muse Spark 1.3 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 $0.99 per million tokens for DeepSeek V4 Pro 0813 versus $2.00 for Muse Spark 1.3 (2× as much).

Which scores higher on benchmarks?

Muse Spark 1.3 scores higher on the Capabilities Index (ECI): Muse Spark 1.3 156.9 (#17 of 148) and DeepSeek V4 Pro 0813 155.4 (#26 of 148). The confidence ranges of the top two overlap (154.7–159.6 vs 153.7–157.6), so treat the gap as small. On individual benchmarks: FrontierMath Tiers 1–3 — Muse Spark 1.3 74.4%, DeepSeek V4 Pro 0813 64.6%; OTIS Mock AIME 2024–2025 — Muse Spark 1.3 99.2%, DeepSeek V4 Pro 0813 98.6%.

Which is better for coding?

There are no published SWE-bench Verified results for DeepSeek V4 Pro 0813 and Muse Spark 1.3 yet, so there is no like-for-like coding score. On overall capability, Muse Spark 1.3 leads, which tends to carry over to coding, but test on your own codebase. Both support tool calling for agent workflows.

Which has the bigger context window?

Muse Spark 1.3 has the largest context window at 1,048,576 tokens, against 1,000,000 for DeepSeek V4 Pro 0813. Maximum output per response: DeepSeek V4 Pro 0813 up to 384,000, Muse Spark 1.3 up to 131,072 tokens.

Which can read images, PDFs, audio or video?

DeepSeek V4 Pro 0813 accepts text; Muse Spark 1.3 accepts text, images, PDFs, audio and video. Muse Spark 1.3 handles the widest range of inputs.

Are any of these open source?

DeepSeek V4 Pro 0813 publishes its weights (MIT) and can be self-hosted; Muse Spark 1.3 is proprietary.

Which is newer?

Muse Spark 1.3 is the newest, released Sep 2, 2026. DeepSeek V4 Pro 0813 came out Aug 12, 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.

05 — Keep comparing

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