MModelspectraIndependent AI Model Intelligence
Head-to-head · Updated 2026-09-08
Model Comparison · Head to Head

Doubao Seed Evolving vs Muse Spark 1.1

Doubao Seed Evolving wins on Overall, Coding, Multimodal. Every numeric field is compared below, with a worked monthly-cost example and a pick rule for each use case.

VendorByteDance / Meta
Data fields15+ dimensions
Updated2026-09-08
Read~9 min
01

Verdict at a glance

Bottom line: Choose Doubao Seed Evolving when coding depth, long-context reliability matter most; choose Muse Spark 1.1 when lower cost, fine-tuning/ecosystem is the priority.

Choose Doubao Seed Evolving if you…

  • Continuously updated
  • 1M context
  • Good Chinese
  • ByteDance ecosystem
  • Best for: Chinese, Long context, Continuously evolving

Choose Muse Spark 1.1 if you…

  • Completely free open weights
  • By Meta
  • Self-hostable
  • Multimodal
  • Best for: Open research, Local deployment, Experimental
02

Head-to-head aggregate scores

Scores are 0–100, aggregated from public benchmark information and independently weighted across three leaderboards. Rank is out of 22 tracked models.

Doubao Seed Evolving Higher overall
ByteDance · #15 overall
Overall68
Coding67
Multimodal83
VS
Muse Spark 1.1
Meta · #22 overall
Overall61
Coding59
Multimodal75

Aggregated from public sources and independently weighted; methodology on the Terms page. Scores within 3 points are treated as statistically tied.

03

Specs & pricing — every field side by side

List API prices in USD per 1M tokens. The highlighted cell is the stronger value/capability on that row.

DimensionDoubao Seed EvolvingMuse Spark 1.1Verdict
VendorByteDance (CN)Meta (US)Different vendors
Released2026.072026.08Muse Spark 1.1 is newer
Overall (rank)68 · #1561 · #22Doubao Seed Evolving +7
Coding67 · #1459 · #21Doubao Seed Evolving +8
Multimodal83 · #975 · #15Doubao Seed Evolving +8
Context window1M256KDoubao Seed Evolving larger
Max output256K64KMuse Spark 1.1 longer
Effective-context9280Doubao Seed Evolving more reliable
Input $/1M$0.83FreeMuse Spark 1.1 cheaper
Output $/1M$4.17FreeMuse Spark 1.1 cheaper
Cache discountcustomnoneMuse Spark 1.1 deeper
Speed~60 tok/sHardware-dependentDoubao Seed Evolving faster
TTFT0.5sHardware-dependentDoubao Seed Evolving snappier
Function calling8265Doubao Seed Evolving ahead
Refusal rate~10%~4%Muse Spark 1.1 less restrictive
English7078Muse Spark 1.1
Chinese9360Doubao Seed Evolving
Modalitiestext, imagetext, imageSame
Open weightsNoYesMuse Spark 1.1 is open
Fine-tuningNoYes
Free tierDoubao App freeFully free (model weights)
SOC2 / no-trainno / yesno / yes
Private deploymentYesYesBoth support it

Fields drawn from vendor public documentation and the Modelspectra 22-model dataset; speed varies with network, concurrency and prompt length. Verify current pricing before purchase.

04

Dimension-by-dimension analysis

Reasoning & overall intelligence

Doubao Seed Evolving leads the overall aggregate by 7 points (68 vs 61). That is a meaningful, not marginal, edge on hard, multi-step reasoning, while Muse Spark 1.1 remains a strong generalist that is not out of its depth on routine work.

Agentic coding

This is a modest gap: Doubao Seed Evolving scores 67 against 59. On multi-file edits, SWE-style tickets and long-horizon agent loops Doubao Seed Evolving needs fewer correction turns; Muse Spark 1.1 is still competent for scripts and assisted completion but trails as task complexity rises.

Multimodal

Doubao Seed Evolving leads multimodal 83 vs 75. Neither emits native video, so the comparison is about parsing images and documents, not generation.

Speed & latency

Muse Spark 1.1 is self-hosted, so its speed depends on your hardware; against a managed API like Doubao Seed Evolving (~60 tok/s, 0.5s TTFT) compare on your own infrastructure before assuming latency.

Context: window vs usable recall

Nominal windows are 1M for Doubao Seed Evolving and 256K for Muse Spark 1.1. Effective-context scores point the same way as window size — Doubao Seed Evolving is ahead on usable recall (92 vs 80), so prefer it for long-document work where details cannot be missed.

Price & total cost

Muse Spark 1.1 is free open weights (you pay only for the infrastructure you run it on), while Doubao Seed Evolving is a paid API at $0.83/$4.17 per 1M tokens. The real comparison is total cost of ownership — GPU/ops against a managed bill — not list price alone.

Chinese vs English

English: Doubao Seed Evolving 70 vs Muse Spark 1.1 78. Chinese: 93 vs 60. For Chinese-language production, Doubao Seed Evolving is the stronger pick. Note that non-Chinese models generally require overseas network access for their APIs.

Tool use & ecosystem

Function-calling score: Doubao Seed Evolving 82 vs Muse Spark 1.1 65, so Doubao Seed Evolving has the edge on structured tool use. Fine-tuning is available from Muse Spark 1.1. Factor in existing SDK/plugin familiarity — switching cost often outweighs a few-point tool-use gap.

05

Cost worked example — same workload, real token math

Assume a production workload of 100M input + 30M output tokens per month, with 90% of input tokens served from cache. Figures use public list prices.

Cost note: one of these models is free open weights, so a per-token monthly bill does not apply — budget instead for GPU and operations. The paid API counterpart works out to roughly $208/month at list for this workload.

Illustrative model; your input/output mix and cache-hit ratio change the result. Prices are list rates before any enterprise agreement.

06

Decision tree

IF the workload is agentic or multi-file coding and a wrong first pass is expensive  →  choose Doubao Seed Evolving (coding 67 vs 59).
IF you serve real-time users and latency is a product KPI  →  choose Doubao Seed Evolving (~60 tok/s, 0.5s TTFT).
IF you need free, self-hostable weights and can run your own GPU/ops  →  choose Muse Spark 1.1 (free open weights).
IF long-document recall has to be near-perfect  →  choose Doubao Seed Evolving (effective context 92 vs 80).
07

Frequently asked questions

Does Doubao Seed Evolving's higher refusal rate matter in production?
Doubao Seed Evolving refuses about 10% of prompts versus 4% for Muse Spark 1.1. In unattended pipelines that means more retries, fallbacks and manual review, raising effective cost and latency even when the token price is lower.
Does the bigger context window actually matter?
Nominal windows are Doubao Seed Evolving (1M) and Muse Spark 1.1 (256K), but usable recall follows the effective-context score (92 vs 80). Prefer the higher effective-context model for long-document work where nothing can be missed.
How do they differ for Chinese-language and data-residency use?
Doubao Seed Evolving is the Chinese model (Chinese score 93, domestic cloud, possible private deployment) while Muse Spark 1.1 is the global model (Chinese 60, overseas API). Pick by language quality, access path and where data must reside.
Can I self-host either model?
Muse Spark 1.1 ships open weights and can be self-hosted (GPU permitting) for data control; Doubao Seed Evolving is a closed managed API with no self-hosting. Choose open weights when residency or cost-at-scale dominates, managed API for convenience.
Which one supports fine-tuning?
Muse Spark 1.1 supports fine-tuning; Doubao Seed Evolving does not at this tier. If you plan to adapt the model to a narrow domain, that is a concrete differentiator.
What is the single-line recommendation?
Choose Doubao Seed Evolving for Chinese, Long context; choose Muse Spark 1.1 for Open research, Local deployment.