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OpenAI vs Meta
Two closed APIs with open-weight side models. Meta's Muse Spark is cheaper and speaks OpenAI's format; OpenAI has the track record and the frontier tier.
By The Subconscious Team · Updated
OpenAI vs Meta: key differences
Meta's Muse API is built to be an easy switch from OpenAI. The endpoint speaks OpenAI Chat Completions, along with Anthropic Messages and a stateful agentic format, and Muse Spark 1.3 costs $1.25 in and $4.25 out with a 1M window and cached input at $0.15. That sits well under GPT-6 Astra and between GPT-6 Luna and GPT-6.1 Sol. Both companies pair a closed API with an open model for self-hosting: gpt-oss from OpenAI, and Muse Glimmer, distilled from Muse Spark, from Meta.
The difference is maturity. Meta's API is new, with a short track record, while OpenAI has the largest ecosystem, hosted tools and availability on Azure and Bedrock. Meta's Contributor tier cuts prices to $0.10 in and $0.20 out, but it lets Meta train on your prompts and drops rate limits from 3,000 to 150 requests per minute, which rules it out for most business traffic. Meta also bundles Muse Image at $0.01 per image and transcription at $0.18 per audio hour on the same key.
What OpenAI and Meta do
OpenAI
OpenAI runs the most widely adopted closed-model API. Its October 2026 lineup has GPT-6 Astra at the top for computer use, coding and long agentic runs, priced at $10 in and $50 out per million tokens. Below it sit GPT-6.1 Sol, the default for coding, research and computer use at $2 in and $10 out, GPT-6.1 Terra, released October 26 for computer use, visual reasoning and writing at $1 in and $5 out, and GPT-6 Luna for high-volume jobs at $0.10 in and $0.50 out. All four carry a 1.05M token context window with up to 128K output.
Example models: GPT-6 Astra, GPT-6.1 Sol, GPT-6.1 Terra, GPT-6 Luna
Full OpenAI 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 OpenAI or Meta?
OpenAI
Choose OpenAI for
- Production traffic that needs a longer vendor track record
- Frontier computer use on GPT-6 Astra
- Enterprise procurement through Azure or Bedrock
Meta
Choose Meta for
- Cost-sensitive coding agents at mid-tier prices
- Prototyping on the near-free Contributor tier when data sharing is fine
- Cheap image generation and transcription on one key
OpenAI vs Meta at a glance
| Attribute | OpenAI | Meta |
|---|---|---|
| Model access | Closed, plus open gpt-oss | Closed API; open Muse Spark Open and Glimmer |
| Flagship models | GPT-6 Astra, GPT-6.1 Sol, GPT-6.1 Terra, GPT-6 Luna | Muse Wonder, Muse Spark 1.3, Muse Spark Open |
| Speed | Fast mode; Ultrafast on GPT-6 Astra | ~145–233 tok/s on Muse Spark 1.3 |
| Price | $0.10–$10 in, $0.50–$50 out per 1M | $1.25–$4 in, $4.25–$20 out; Contributor tier cheaper |
| Customization | N/A | Open Muse weights to fine-tune |
| Deployment | API, Azure OpenAI, Bedrock | Meta Model API, Oracle Cloud |
| Long context | 1.05M; 2x input past 272K | 1M |
Frequently asked questions
What is the difference between OpenAI and Meta?
Two closed APIs with open-weight side models. Meta's Muse Spark is cheaper and speaks OpenAI's format; OpenAI has the track record and the frontier tier.
When should I choose OpenAI over Meta?
Production traffic that needs a longer vendor track record; Frontier computer use on GPT-6 Astra; Enterprise procurement through Azure or Bedrock.
When should I choose Meta over OpenAI?
Cost-sensitive coding agents at mid-tier prices; Prototyping on the near-free Contributor tier when data sharing is fine; Cheap image generation and transcription on one key.
Is OpenAI or Meta cheaper?
OpenAI: $0.10–$10 in, $0.50–$50 out per 1M. 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, OpenAI or Meta?
OpenAI: 1.05M; 2x input past 272K. 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.