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xAI vs Meta
Two closed labs with cheap agentic models. xAI brings X data and a longer API track record; Meta brings Muse Spark at $1.25 in, dual SDK compatibility and a near-free data-sharing tier.
By The Subconscious Team · Updated
xAI vs Meta: key differences
Price points sit close together. Meta's Muse Spark 1.3 costs $1.25 in and $4.25 out per million with a 1M context, while xAI's Grok 4.7 costs $2 in and $6 out with 500K context, and Grok 4.20 matches Meta's input price at $1.25 with $2.50 output and 1M context. Both labs sell media on the side: xAI through separate image, video and audio APIs, Meta through Muse Image at $0.01 per image and Muse Voice Transcribe at $0.18 per hour. Meta's endpoint speaks OpenAI Chat Completions and Anthropic Messages formats, which eases migration.
The differences are data and maturity. Meta's API is new, with a short track record. Its Contributor tier cuts prices about 95% to $0.10 in and $0.20 out if Meta can train on your traffic, with rate limits dropping to 150 requests per minute. xAI has no equivalent, but it bills the whole request at double past 200K prompt tokens, which hurts long agent contexts. xAI's X Search is unique for real-time agents. Meta also ships open-weight Muse Glimmer for self-hosting, where xAI is closed only.
What xAI and Meta do
xAI
xAI sells the Grok models through its own API and Amazon Bedrock. SpaceX acquired it in February 2026; it became SpaceXAI in July and SpaceX Super Intelligence (SpaceXSI) in October, the name its docs now use. Grok 4.7, released September 21, 2026, is the current flagship, pitched for coding, agentic tasks and knowledge work. It has a 500K context window and costs $2 in and $6 out per million tokens under 200K prompt tokens. Older Grok 4.20 and 4.3 models keep a 1M window at $1.25 in and $2.50 out, which is aggressive for that capability class.
Example models: Grok 4.7, Grok 4.20
Full xAI 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 xAI or Meta?
xAI vs Meta at a glance
| Attribute | xAI | Meta |
|---|---|---|
| Model access | Closed | Closed API; open Muse Spark Open and Glimmer |
| Flagship models | Grok 4.7, Grok 4.20, grok-build | Muse Wonder, Muse Spark 1.3, Muse Spark Open |
| Speed | ~54 tok/s on Grok 4.6 | ~145–233 tok/s on Muse Spark 1.3 |
| Price | $2 in, $6 out (Grok 4.7); 2x past 200K | $1.25–$4 in, $4.25–$20 out; Contributor tier cheaper |
| Customization | Unknown | Open Muse weights to fine-tune |
| Deployment | First-party API, Amazon Bedrock | Meta Model API, Oracle Cloud |
| Long context | 500K (4.7), 1M (4.20, 4.3) | 1M |
Frequently asked questions
What is the difference between xAI and Meta?
Two closed labs with cheap agentic models. xAI brings X data and a longer API track record; Meta brings Muse Spark at $1.25 in, dual SDK compatibility and a near-free data-sharing tier.
When should I choose xAI over Meta?
Real-time agents on X posts and web search; Low output prices on Grok 4.20; Teams that want an API with a longer track record.
When should I choose Meta over xAI?
Near-free prototyping when data sharing is acceptable; Drop-in migration from OpenAI or Anthropic SDKs; An open-weight sibling model to self-host.
Is xAI or Meta cheaper?
xAI: $2 in, $6 out (Grok 4.7); 2x past 200K. 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, xAI or Meta?
xAI: 500K (4.7), 1M (4.20, 4.3). Meta: 1M.
Related comparisons
Running long-horizon agents?
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.