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Moonshot AI vs Meta
A lab that opened its flagship against one that moved to a closed API. Kimi K3 is the stronger open coder; Meta's Muse Spark is cheaper and bundles media on one key.
By The Subconscious Team · Updated
Moonshot AI vs Meta: key differences
Meta and Moonshot have moved in opposite directions. Meta shifted from open Llama releases to a closed API for its Muse family, keeping only Muse Glimmer, a distilled model, as open weights. Moonshot published full weights for Kimi K3, its flagship until K3.1 Pro launched in October. On price, Meta's Muse Spark 1.3 costs $1.25 in and $4.25 out with a 1M window, well under K3's $3 in and $15 out. Both target agentic coding, but only K3 comes with independent coding results in its listing, including 93.4% on SWE-bench Verified from Vals AI and third place on the Artificial Analysis Intelligence Index.
Meta's API is broader in scope. The same key serves Muse Image at $0.01 per image, Muse Voice Transcribe at $0.18 per hour of audio and web search grounding, and it speaks OpenAI, Anthropic and stateful agentic formats. Its Contributor tier is near-free if Meta may train on your data. Moonshot's strengths are open weights and a 1M context built for repo-scale work, with Kimi Code for terminal users. K3's costs are its 33 tokens per second and verbosity. Meta's is maturity, since its API is new.
What Moonshot AI and Meta do
Moonshot AI
Moonshot AI is the Beijing lab behind the Kimi models. Its flagship Kimi K3 launched July 16, 2026 as a 2.8 trillion parameter mixture-of-experts model that activates 16 of 896 experts per token, with native vision and a 1M token context. It is the first open model in the 3T class, and full weights landed on Hugging Face on July 27. The hosted API costs $3 in and $15 out per million tokens, with cached input at $0.30, and it runs through an OpenAI compatible endpoint, Kimi Code in the terminal, OpenRouter and Cloudflare Workers AI.
Example models: Kimi K3.1 Pro, Kimi K3
Full Moonshot AI 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 Moonshot AI or Meta?
Moonshot AI
Choose Moonshot AI for
- Coding agents that need a top open model
- Self-hosting or fine-tuning flagship-class weights
- Repo-scale work that uses the full 1M window
Meta
Choose Meta for
- Cost-sensitive agents at $1.25 in and $4.25 out
- Apps that need image generation and transcription on one key
- Prototypes on the Contributor tier when data sharing is acceptable
Moonshot AI vs Meta at a glance
| Attribute | Moonshot AI | Meta |
|---|---|---|
| Model access | Open weights, custom license | Closed API; open Muse Spark Open and Glimmer |
| Flagship models | Kimi K3.1 Pro, Kimi K3 | Muse Wonder, Muse Spark 1.3, Muse Spark Open |
| Speed | ~33 tok/s on Kimi K3 | ~145–233 tok/s on Muse Spark 1.3 |
| Price | $2 in, $10 out (K3.1 Pro); $3 in, $15 out (K3) | $1.25–$4 in, $4.25–$20 out; Contributor tier cheaper |
| Customization | Open weights to fine-tune | Open Muse weights to fine-tune |
| Deployment | API, Kimi Code, OpenRouter | Meta Model API, Oracle Cloud |
| Long context | 1M | 1M |
Frequently asked questions
What is the difference between Moonshot AI and Meta?
A lab that opened its flagship against one that moved to a closed API. Kimi K3 is the stronger open coder; Meta's Muse Spark is cheaper and bundles media on one key.
When should I choose Moonshot AI over Meta?
Coding agents that need a top open model; Self-hosting or fine-tuning flagship-class weights; Repo-scale work that uses the full 1M window.
When should I choose Meta over Moonshot AI?
Cost-sensitive agents at $1.25 in and $4.25 out; Apps that need image generation and transcription on one key; Prototypes on the Contributor tier when data sharing is acceptable.
Is Moonshot AI or Meta cheaper?
Moonshot AI: $2 in, $10 out (K3.1 Pro); $3 in, $15 out (K3). 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, Moonshot AI or Meta?
Moonshot AI: 1M. Meta: 1M.
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