Model comparison
Compare Muse Spark 1.3 and DeepSeek-V4-Flash using the same provider-sourced text & reasoning rubric. No mystery score and no invented benchmark ranking.
Facts checked September 4, 2026
Set your usage. Your estimate updates as you type.
Example: 6,000 input tokens for 10 pages, plus a 500-token summary. Page lengths vary; adjust the numbers below.
One run sends your input to the model once and receives an answer. Tokens are pieces of text: input is what you send, output is the answer you receive.
Estimates exclude taxes, tools, cache storage/writes, free allowances and custom discounts. Image estimates cover output only, not prompt or reference-image charges. Quality modes differ by model. Unlisted settings are not treated as free.
| Model | Access | Estimated total (USD) |
|---|---|---|
| DeepSeek-V4-FlashDeepSeek | DeepSeek | No reviewed rate |
| Muse Spark 1.3Meta | Meta | No reviewed rate |
Quick take
Meta's latest multimodal reasoning model for long-running agents, coding, tools, and complex user collaboration.
Meta's public launch does not publish every operational limit or one complete API data-use commitment. Check the live model page, price, region, retention controls, and maximum output before production.
DeepSeek's lower-cost V4 model for high-volume reasoning, coding, agents, and million-token text workloads.
Flash's knowledge cutoff and universal latency are not published. Do not confuse it with Flash-Vision-Exp, and verify peak pricing, cache behavior, output budgets, jurisdiction, and data handling.
Compare the published facts
Values use each provider's own published units and limits. A blank means the provider did not publish a directly comparable value in the sources reviewed.
| Text & reasoning | Muse Spark 1.3 | DeepSeek-V4-Flash |
|---|---|---|
| Context windowMaximum combined prompt and working context documented by the provider. | 1M active context management in the Muse Spark API family | 1M tokens |
| Maximum outputProvider-published response limit, where available. | Not separately published | Up to 384K tokens |
| Knowledge cutoffLatest reliable knowledge date explicitly published by the model provider. Search and connected tools can retrieve newer information but do not change the model's built-in cutoff. | Not published | Not published |
| Input priceCurrent standard list price per million input tokens unless noted. | See live Meta Model API price | $0.44 / 1M peak uncached; $0.22 off-peak |
| Output priceCurrent standard list price per million output tokens unless noted. | See live Meta Model API price | $1.32 / 1M peak; $0.66 off-peak |
| InputsMedia types accepted by the listed model endpoint. | Text, image, video, PDF | Text; separate Flash-Vision-Exp accepts images |
| Tools & agentsSelected native tools and agent-building capabilities, not an exhaustive list. | Parallel tools, coding, long-running agents, high reasoning | Tools, JSON output, Responses API, thinking effort, FIM beta |
How to choose
Start with the job you need to complete, then validate cost, access, and policy details on your exact provider route.
The public Muse Spark model and release pages reviewed do not state one complete API retention or training-use commitment. Check the current Meta Model API terms and account controls before using private data.
Provider and API links
DeepSeek documents its Responses API as stateless and says responses and conversations are not stored by that endpoint. This is not a complete account-wide retention or training-use promise; review current platform terms and automatic cache behavior for sensitive data.
Provider and API links
Frequently asked questions
Muse Spark 1.3: Meta's latest multimodal reasoning model for long-running agents, coding, tools, and complex user collaboration. DeepSeek-V4-Flash: DeepSeek's lower-cost V4 model for high-volume reasoning, coding, agents, and million-token text workloads.
Consider Muse Spark 1.3 when your priority is Long-horizon coding and agent projects. Consider DeepSeek-V4-Flash when your priority is Cost-efficient coding and agent workloads. Test both with your own data and provider route before committing.
No. This comparison aligns provider-published facts for the Text & reasoning category. It does not claim a universal winner or combine incompatible third-party benchmark scores.
