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DeepSeek vs Meta
DeepSeek offers open MIT flagships at low per-token rates. Meta offers a closed Muse Spark API, compatible with OpenAI and Anthropic formats, plus a near-free tier that trains on your data.
By The Subconscious Team · Updated
DeepSeek vs Meta: key differences
The licensing runs opposite to what their histories suggest. DeepSeek ships its flagship weights under MIT on Hugging Face. Meta has moved from open Llama releases to a closed API, keeping only the distilled Muse Glimmer as open weights. On price, Meta's Muse Spark 1.3 is $1.25 in and $4.25 out with cached input at $0.15, well above DeepSeek V4.1 Flash's $0.30 and $1.20 at peak, and DeepSeek halves that off-peak. Both offer 1M context. Meta's Contributor tier drops to $0.10 in and $0.20 out in exchange for training on your prompts.
Meta's endpoint speaks OpenAI Chat Completions, Anthropic Messages and a stateful agentic format, and the same key reaches Muse Image at $0.01 per image and transcription at $0.18 per audio hour. DeepSeek offers image understanding on V4.1 Flash but no generation. Data handling is the sharpest split. DeepSeek stores hosted data in China, while Meta's Contributor tier hands your data to Meta. Meta's API also has a short track record. Self-hosters and off-peak batch users fit DeepSeek better. Teams that want one key for text, images and speech fit Meta.
What DeepSeek and Meta do
DeepSeek
DeepSeek is the Chinese lab whose open-weight models reset price expectations for the whole market. Its main model is V4.1 Flash, with 1M context and 384K max output, which shipped September 10, 2026 with built-in image understanding at $0.30 in and $1.20 out at peak. An updated checkpoint, V4.1-Flash-1017, replaced it on October 17 at the same price. DeepSeek had planned to route deepseek-v4-pro requests to V4.1 Flash from September 14 but reversed course, and still serves V4 Pro at $1.32 in and $3.96 out at peak until a V4.1 Pro launches. Cache hits cost a few cents per million or less, and the weights ship on Hugging Face under an MIT license.
Example models: DeepSeek V4.1 Flash
Full DeepSeek profileMeta
Meta has moved from open Llama releases toward its own closed API. Meta Superintelligence Labs builds the Muse family, and in July 2026 Meta launched the Meta Model API with Muse Spark 1.1, a multimodal reasoning model aimed at agentic coding, tool use and computer use. At Meta Connect in September, Meta made the API generally available globally. Muse Spark 1.3 has a 1M token context and costs $1.25 in and $4.25 out per million tokens, with cached input at $0.15. Muse Wonder, released October 12, 2026, sits above it for longer, harder agent work at $4 in and $20 out, also with 1M context. The endpoint speaks OpenAI Chat Completions, Anthropic Messages and a stateful agentic format.
Example models: Muse Wonder, Muse Spark 1.3, Muse Spark Open
Full Meta profileShould you choose DeepSeek or Meta?
DeepSeek vs Meta at a glance
| Attribute | DeepSeek | Meta |
|---|---|---|
| Model access | Open weights (MIT) | Closed API; open Muse Spark Open and Glimmer |
| Flagship models | DeepSeek V4.1 Flash | Muse Wonder, Muse Spark 1.3, Muse Spark Open |
| Speed | ~209 tok/s on V4.1 Flash | ~145–233 tok/s on Muse Spark 1.3 |
| Price | Off-peak hours at half price | $1.25–$4 in, $4.25–$20 out; Contributor tier cheaper |
| Customization | Open weights to fine-tune | Open Muse weights to fine-tune |
| Deployment | First-party API, Hugging Face weights | Meta Model API, Oracle Cloud |
| Long context | 1M, 384K max output | 1M |
Frequently asked questions
What is the difference between DeepSeek and Meta?
DeepSeek offers open MIT flagships at low per-token rates. Meta offers a closed Muse Spark API, compatible with OpenAI and Anthropic formats, plus a near-free tier that trains on your data.
When should I choose DeepSeek over Meta?
Self-hosting a flagship under MIT; Off-peak batch work at half price; Output-heavy tasks up to 384K tokens.
When should I choose Meta over DeepSeek?
Drop-in Anthropic or OpenAI format compatibility; Image generation and transcription on one key; Near-free prototyping where data sharing is acceptable.
Is DeepSeek or Meta cheaper?
DeepSeek: Off-peak hours at half price. Meta: $1.25–$4 in, $4.25–$20 out; Contributor tier cheaper. The cheaper choice depends on the model and workload.
Which has more context, DeepSeek or Meta?
DeepSeek: 1M, 384K max output. Meta: 1M.
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If your agents run past 200K tokens, compare both against Subconscious. Our inference stack treats a long-horizon trace as the primary workload, so speed, cost, and accuracy hold up deep into the trace.