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DeepInfra vs Meta
Meta's new closed Muse API against DeepInfra's open catalog. Meta's cheapest tier costs you your data. DeepInfra's low prices come from quantization instead.
By The Subconscious Team · Updated
DeepInfra vs Meta: key differences
Meta has moved from open Llama releases to a closed API, while DeepInfra still serves the older open side of that story, with Llama 3.1 8B at $0.02 per million. The Meta Model API offers Muse Spark 1.3, a multimodal reasoning model aimed at agentic coding, tool use and computer use, with 1M context at $1.25 in and $4.25 out. It speaks OpenAI Chat Completions, Anthropic Messages and a stateful agentic format. DeepInfra offers a fully OpenAI compatible API over 200+ open models from many labs, with no single model at the center.
The price comparison hinges on Meta's Contributor tier. At $0.10 in and $0.20 out it lands close to floor pricing, but Meta trains on your prompts and completions, and rate limits drop from 3,000 to 150 requests per minute. That rules it out for most business traffic. DeepInfra reaches low prices through quantization, so teams should check precision per model. Meta also bundles Muse Image at $0.01 per image and transcription at $0.18 per hour on the same key. Choose Meta for coding agents and multimodal assistants on one capable model. Choose DeepInfra for bulk work across many open models.
What DeepInfra and Meta do
DeepInfra
DeepInfra is the price floor for open-model inference. Developers treat it as the reference point for what a token should cost, with small models like Llama 3.1 8B at $0.02 per million and DeepSeek V4 Flash at $0.09 in and $0.18 out. The catalog covers 200+ open models across text, image and speech behind a fully OpenAI compatible API. There are no minimums, setup fees or contracts on the shared API.
Example models: DeepSeek V4 Flash, Llama 3.1 8B
Full DeepInfra 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 DeepInfra or Meta?
DeepInfra
Choose DeepInfra for
- Business traffic that cannot be shared for training
- High-rate bulk calls on small open models
- Choosing among many open model families
Meta
Choose Meta for
- Agentic coding and computer use on Muse Spark 1.3
- Cheap image generation and transcription on one key
- Near-free prototyping where data sharing is acceptable
DeepInfra vs Meta at a glance
| Attribute | DeepInfra | Meta |
|---|---|---|
| Model access | Open weights | Closed API; open Muse Spark Open and Glimmer |
| Flagship models | DeepSeek V4 Flash, Llama 3.1 8B | Muse Wonder, Muse Spark 1.3, Muse Spark Open |
| Speed | Unknown | ~145–233 tok/s on Muse Spark 1.3 |
| Price | From $0.02 per 1M | $1.25–$4 in, $4.25–$20 out; Contributor tier cheaper |
| Customization | No managed fine-tuning | Open Muse weights to fine-tune |
| Deployment | Shared API, no contracts | Meta Model API, Oracle Cloud |
| Long context | 1M on DeepSeek V4 Pro | 1M |
Frequently asked questions
What is the difference between DeepInfra and Meta?
Meta's new closed Muse API against DeepInfra's open catalog. Meta's cheapest tier costs you your data. DeepInfra's low prices come from quantization instead.
When should I choose DeepInfra over Meta?
Business traffic that cannot be shared for training; High-rate bulk calls on small open models; Choosing among many open model families.
When should I choose Meta over DeepInfra?
Agentic coding and computer use on Muse Spark 1.3; Cheap image generation and transcription on one key; Near-free prototyping where data sharing is acceptable.
Is DeepInfra or Meta cheaper?
DeepInfra: From $0.02 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, DeepInfra or Meta?
DeepInfra: 1M on DeepSeek V4 Pro. 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.