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Model comparison · accepted catalogue facts 2026-10-21

DeepSeek V4.1 Flash vs Muse Spark 1.3

Neither model has both an equal-or-higher measured score and an equal-or-lower estimated price in this pair. Retaining your current model is a valid outcome.

Editorial comparison: DeepSeek budget efficiency vs Meta high-ranking Spark Inclusion does not recommend either model.

DeepSeek V4.1 Flash

LMArena general · Elo · higher is better

Scale starts at 1040 Elo

1462.5

Balanced effective USD / 1M tokens · lower is better

$0.182/M

Price under confirmation since Oct 12, 2026
Muse Spark 1.3

LMArena general · Elo · higher is better

Scale starts at 1040 Elo

1489.8

Balanced effective USD / 1M tokens · lower is better

$2.00/M

In-Depth Analysis

DeepSeek V4.1 Flash vs Muse Spark 1.3: Measured Technical Breakdown

Comprehensive comparison across measured human-preference evaluation, effective production token costs, architectural limits, and migration trade-offs.

Measured Capability (LMArena)
Muse Spark 1.3 leads by 27.3 Elo

DeepSeek V4.1 Flash: 1462.5 ±6.29 · Muse Spark 1.3: 1489.8 ±5.65 Statistically significant preference separation

Cost Comparison Across Canonical Production Workloads

Rates represent effective cost per 1M tokens under standard token blends. Cached prompt reads are factored according to workload context reuse.

Workload & RatioDeepSeek V4.1 FlashMuse Spark 1.3Cost DifferenceAdvantage
Balanced 3 tokens in per 1 out$0.182 /1M tokens$2.00 /1M tokens$1.82 (91% diff)DeepSeek V4.1 Flash costs less
Summarise Huge input, tiny output$0.067 /1M tokens$1.09 /1M tokens$1.02 (94% diff)DeepSeek V4.1 Flash costs less
Chat Long cached system prompt$0.247 /1M tokens$2.12 /1M tokens$1.87 (88% diff)DeepSeek V4.1 Flash costs less
Code gen Output dominates$0.360 /1M tokens$2.96 /1M tokens$2.60 (88% diff)DeepSeek V4.1 Flash costs less
Agentic Context replayed each turn$0.105 /1M tokens$1.05 /1M tokens$0.941 (90% diff)DeepSeek V4.1 Flash costs less

Architectural & Operational Specifications

SpecificationDeepSeek V4.1 FlashMuse Spark 1.3Operational Note
Context window1,048,576 tokens1,048,576 tokens—
Max output generation943,718 tokens943,718 tokens—
Base input price$0.053 / 1M tokens$1.25 / 1M tokensDeepSeek V4.1 Flash input rate is cheaper
Base output price$0.570 / 1M tokens$4.25 / 1M tokensDeepSeek V4.1 Flash output rate is cheaper
Cached input price$0.010 / 1M tokens$0.150 / 1M tokensDeepSeek V4.1 Flash offers lower cached prompt cost
Reasoning & thinking tokensSupported; standard ratesSupported; standard rates—
Input modalitiestext, imagetext, image, video, file, audio—
Tool calling / function useSupportedSupported—
Open weights & licenceProprietary (API-only)Proprietary (API-only)—
Provider & reseller marketDeepSeek · 31 provider offers (11.19× spread)Meta · 1 provider offers—

When to Choose DeepSeek V4.1 Flash

  • Direct integration with DeepSeek tooling and API features.
Risks when moving from Muse Spark 1.3 → DeepSeek V4.1 Flash:
  • video input is not supported by the candidate.
  • file input is not supported by the candidate.
  • audio input is not supported by the candidate.

When to Choose Muse Spark 1.3

  • Higher measured general capability (1489.8 Elo on human evaluation).
  • Broader multimodal input support: text, image, video, file, audio.
  • Direct integration with Meta tooling and API features.

Detailed Evidence Passports & Independent Audits

DeepSeek V4.1 Flash Full model card, pricing ladder & provider offers → Muse Spark 1.3 Full model card, pricing ladder & provider offers → Alternatives to DeepSeek V4.1 Flash Better-and-cheaper dominance audit → Alternatives to Muse Spark 1.3 Better-and-cheaper dominance audit →

Compare · model decision

Choose two or three models

Inspect the differences, estimate your workload and keep the evidence. All standard catalogue models are available, including unrated ones.

Catalogue facts
2026-10-21

2 / 3 selected · 0 requirements
Open public comparison link
Public workload and requirements

These settings are included in the share link. The fixed-request scenario and private evaluation data below are excluded.

A ↔ B

Neither model has both an equal-or-higher measured score and an equal-or-lower estimated price in this pair. Retaining your current model is a valid outcome.

Estimated blend: 75% input, 25% output; 0% cached input. Base context tier. Prompt length selects the billing tier. An unlisted cache-read rate uses that tier’s full input rate in this blend; missing required input or output rates prevent an estimate. The fixed-request estimate below validates actual context and output limits and requires a published cache-read rate when cache hits are assumed.

What changes between these models

Quality first, then estimated price. LMArena scores are human-preference measurements, not a benchmark of your application. A missing score is unrated.

  • DeepSeek V4.1 Flash · Meets the stated model requirements
  • Muse Spark 1.3 · Meets the stated model requirements
Material differences and unknown evidence. Deltas compare each model with model A. Unknown facts remain visible.
Measured factA DeepSeek V4.1 FlashB Muse Spark 1.3
LMArena general score (Elo)1,462.51,489.8Δ vs A: +27.3 Elo
Score interval half-width (± Elo)6.295.65Δ vs A: -0.64 Elo
LMArena document score (Elo)Unknown1,470.7
Estimated effective USD / 1M tokens$0.18225$2Δ vs A: +1.81775 USD/M
Base input USD / 1M tokens$0.053$1.25Δ vs A: +1.197 USD/M
Base output USD / 1M tokens$0.57$4.25Δ vs A: +3.68 USD/M
Base cached-input USD / 1M tokens$0.01$0.15Δ vs A: +0.14 USD/M
Price statusUnder confirmation since 2026-10-12As of the catalogue date
Input modalitiestext, imagetext, image, video, file, audio
Open weightsUnknownUnknown
Recorded licenceUnknownUnknown
Model providerDeepSeekMeta
Distinct sellers in the catalogue291Δ vs A: -28
Serving precision differs across offersSupportedNot supportedΔ vs A: -1
Recorded retirement dateUnknownUnknown
6 shared measured facts
Shared measured facts. Deltas compare each model with model A. Unknown facts remain visible.
Measured factA DeepSeek V4.1 FlashB Muse Spark 1.3
Benchmark reasoning effortmaxmax
Context window (tokens)1,048,5761,048,576Δ vs A: 0 tokens
Output limit (tokens)943,718943,718Δ vs A: 0 tokens
Tool useSupportedSupportedΔ vs A: 0
ReasoningSupportedSupportedΔ vs A: 0
Retirement evidenceNone announced; not a guaranteeNone announced; not a guarantee

Provider counts and precision flags describe catalogue offers. They do not establish the precision, availability, region, tool behaviour or limits of your chosen endpoint. Open each model’s provider table before switching.

Complete price ladders and billing conditions

DeepSeek V4.1 Flash

Rates below are USD per 1M tokens. A threshold selects that whole input/output rate pair.

Input-token thresholdInputOutputCached input
Base, up to and including first threshold$0.053$0.57$0.01

Muse Spark 1.3

Rates below are USD per 1M tokens. A threshold selects that whole input/output rate pair.

Input-token thresholdInputOutputCached input
Base, up to and including first threshold$1.25$4.25$0.15
Migration preflight · compare each candidate with model A

Keeping DeepSeek V4.1 Flash is a valid decision. No pairwise comparison certifies a drop-in replacement.

DeepSeek V4.1 Flash → Muse Spark 1.3

No known model-capability loss

  • Provider endpoint, serving precision, availability and task success need your own verification. Catalogue model capabilities do not certify an endpoint.
Check alternatives to DeepSeek V4.1 Flash

Estimate a fixed request shape

Private to this tab unless you save locally or explicitly export private details. These are estimates, not observed invoices. Cross-model token counts and task success are assumptions.

0.1 extra attempts means 10 extra full attempts per 100 requests. Cache writes, tool charges, taxes and unlisted charges are excluded.

  • DeepSeek V4.1 FlashEstimated total: $0.391 1,000 full attempts · base rates
  • Muse Spark 1.3Estimated total: $4.625 1,000 full attempts · base rates
Prompt and output sensitivity · sampled scenarios

Every point recalculates the entire request shape. Tier-boundary samples include one token below, at and above each threshold. Ordering between samples is not guaranteed. Lowest known cost excludes unknown estimates and is not a replacement recommendation.

Vary input; hold output, requests, cache and retries fixed.
Input tokensDeepSeek V4.1 FlashMuse Spark 1.3Coverage
2,000$0.391Lowest known$4.625All computed
4,096$0.502088Lowest known$7.245All computed
32,768$2.021704Lowest known$43.085All computed
131,072$7.231816Lowest known$165.965All computed
Vary output; hold input, requests, cache and retries fixed.
Output tokensDeepSeek V4.1 FlashMuse Spark 1.3
128$0.17896$3.044
2,048$1.27336$11.204
8,192$4.77544$37.316

Bring your observed evaluation results

JSON is parsed locally. Prompts, filenames, individual responses and extra fields are not retained. Import only aggregate measurements for selected models. Task/version labels do not establish that two evaluations used the same dataset.

Expected format
[{"model":"provider/exact-model-id","task":"support-answer","version":"rubric-1","attempts":100,"successes":84,"costUsd":2.4,"latencyMs":950}]

Use the exact catalogue ID. Replace the example values with observed measurements. Omit costUsd or latencyMs when they are unknown. No public score is inferred from these observations.

Keep the decision and its evidence

A portable record retains selected facts, complete tier ladders, public requirements and the publication manifest. It also embeds the full permitted public catalogue to verify the input artifact checksum. Files are larger for this reason (up to 2 MB); local storage is limited to 12 records. Team review is local to this browser; there is no hosted collaboration.

Saving is opt-in and includes private review fields. Shared comparison links never include them. Version 1 Check references remain separate and are not overwritten or guessed into this format.

Saved local decisions · 0

No version 2 decision records are stored in this browser.

Questions this page answers

Is DeepSeek V4.1 Flash a better-and-cheaper replacement for Muse Spark 1.3?

Neither model has both an equal-or-higher measured score and an equal-or-lower estimated price in this pair. Retaining your current model is a valid outcome.

Which model is higher rated: DeepSeek V4.1 Flash or Muse Spark 1.3?

Muse Spark 1.3 scores higher on LMArena general (1489.8 ±5.7) compared to DeepSeek V4.1 Flash (1462.5 ±6.3), a margin of 27.3 Elo points. The measured confidence intervals do not overlap, demonstrating a statistically significant preference lead on human evaluations.

Which model is more cost-effective: DeepSeek V4.1 Flash or Muse Spark 1.3?

On a standard balanced workload (3 prompt tokens per 1 generated token), DeepSeek V4.1 Flash costs $0.182 (price under confirmation since 2026-10-12) per 1M tokens versus $2.00 for Muse Spark 1.3. Muse Spark 1.3 is approximately 11.0× the price of DeepSeek V4.1 Flash. Base input rates are $0.053 for DeepSeek V4.1 Flash and $1.25 for Muse Spark 1.3; base output rates are $0.570 for DeepSeek V4.1 Flash and $4.25 for Muse Spark 1.3.

How do their context windows and generation limits compare?

Both DeepSeek V4.1 Flash and Muse Spark 1.3 provide an identical 1,048,576-token context window. Maximum output generation limits are 943,718 tokens for DeepSeek V4.1 Flash and 943,718 tokens for Muse Spark 1.3.

What capabilities are lost when switching between DeepSeek V4.1 Flash and Muse Spark 1.3?

Switching from DeepSeek V4.1 Flash to Muse Spark 1.3 causes no detected architectural capability loss. Conversely, moving from Muse Spark 1.3 to DeepSeek V4.1 Flash involves: video input is not supported by the candidate; file input is not supported by the candidate; audio input is not supported by the candidate. Run test suites on your specific prompt templates and tool declarations before cutting over production traffic.

Can DeepSeek V4.1 Flash or Muse Spark 1.3 be self-hosted or deployed privately?

Both DeepSeek V4.1 Flash and Muse Spark 1.3 are proprietary cloud models offered via managed API endpoints. DeepSeek V4.1 Flash is served by DeepSeek and 31 catalogue offers, while Muse Spark 1.3 is served by Meta and 1 catalogue offers.

What is included in this comparison?

Accepted model capabilities, context and output limits, complete price-tier ladders, independent LMArena measurements and missing evidence. Provider endpoint precision and application success still need verification.

Can I compare a different workload or keep a decision record?

Yes. Change the public workload, prompt length and requirements in the comparison workspace. Fixed-request scenarios, aggregate evaluations and review notes stay local unless explicitly exported.

Evidence & Ask
Markdown for LLMs