Compute Comparison
vs
All providers →
GreenPTvsMeta

GreenPT vs Meta: Token Pricing, Speed & Intelligence

Full comparison of GreenPT and Meta — live token pricing, latency, throughput, context window, strengths, weaknesses, and best use cases. Rates sourced from public APIs — verify before use.

GreenPT

European LLM inference with EUR pricing

GreenPT (greenpt.com) is an LLM inference provider offering access to models including Kimi, GLM, DeepSeek, and MiniMax families via an OpenAI-compatible API, with pricing denominated in EUR.

ChatLong-context inference
Open-weight host

Meta

Muse brand — Muse Spark 1.3, Muse Glimmer, Muse Image, Muse Voice via Meta Model API

Meta AI is the creator of the Llama model family and the Muse proprietary product line. As of September 2026, Meta's managed API (Meta Model API) offers Muse Spark 1.3 (flagship multimodal), Muse Glimmer (efficient tier), Muse Image (image generation), and Muse Voice (speech synthesis). Llama 4 Scout, Maverick, and Behemoth remain open-weight and available through dozens of third-party providers. Because Llama weights are open, teams can self-host on GPU cloud for dramatically lower per-token costs at scale.

Self-hosted inferenceCost-optimised at scaleEdge/on-deviceChatVisionImage generationVoice AI
Proprietary modelsHosts open weights

Key metric comparison

GreenPT
Meta
Cheapest input ($/1M)

—

—

Cheapest output ($/1M)

—

—

Peak throughput

—

—

Best latency (TTFT)

—

—

Intelligence score

—

—

Context window

—

—

Live token pricing

Strengths and weaknesses

GreenPT

Meta

Open-weight Llama 4 models — self-host on any GPU cloud for lowest per-token cost at scale
Muse Spark 1.3: flagship multimodal model with 1M context window
Muse Image and Muse Voice for image generation and speech synthesis
Widest third-party hosting ecosystem — available on AWS, Azure, GCP, Together AI, Groq, and 20+ others
Llama 3.2 1B/3B models run on-device (mobile, edge)
No vendor lock-in on Llama — switch inference providers without changing model weights
Self-hosting requires GPU infrastructure expertise
Meta Model API has limited availability vs third-party hosts
Muse Spark 1.3 pricing not yet publicly listed at launch
Smaller proprietary model lineup vs OpenAI/Anthropic

Key differentiators

Meta

The only frontier-class model family available as open weights — plus the Muse product line (Spark, Glimmer, Image, Voice) for teams that want managed API access without self-hosting.

Frequently asked questions

GreenPT FAQs

What is GreenPT?

GreenPT is an LLM inference provider offering access to models including Kimi, GLM, DeepSeek, and MiniMax families. See greenpt.com for details.

What currency does GreenPT use for pricing?

GreenPT prices are denominated in EUR. See docs.greenpt.ai/pricing for current rates.

Is the GreenPT API OpenAI-compatible?

GreenPT provides an OpenAI-compatible API. See docs.greenpt.ai for endpoint details.

Meta FAQs

What is the Muse brand from Meta?

Muse is Meta's proprietary managed API product line, launched in 2026. It includes Muse Spark 1.3 (flagship multimodal, 1M context), Muse Glimmer (efficient tier), Muse Image (image generation), and Muse Voice (speech synthesis) — all available via the Meta Model API.

What is the Llama 4 context window?

Llama 4 Scout and Maverick support 1,000,000-token (1M) context windows. Llama 4 Behemoth also targets 1M context. This makes Llama 4 competitive with Gemini 3.x for long-document and multi-document tasks.

Can I self-host Llama models?

Yes — all Llama 3.x and Llama 4 Scout/Maverick weights are publicly available under the Llama Community License. You can run them on any GPU cloud provider. Self-hosting becomes cost-effective at high token volumes — check the live GPU table for current H100 rates.

Provider resources

GreenPT

Provider page
Website
PricingDocs

Meta

Provider page
Website
PricingDocs

GreenPT — European LLM inference with EUR pricing

GreenPT (greenpt.com) is an LLM inference provider offering access to models including Kimi, GLM, DeepSeek, and MiniMax families via an OpenAI-compatible API, with pricing denominated in EUR.

Meta — Muse brand — Muse Spark 1.3, Muse Glimmer, Muse Image, Muse Voice via Meta Model API

Meta AI is the creator of the Llama model family and the Muse proprietary product line. As of September 2026, Meta's managed API (Meta Model API) offers Muse Spark 1.3 (flagship multimodal), Muse Glimmer (efficient tier), Muse Image (image generation), and Muse Voice (speech synthesis). Llama 4 Scout, Maverick, and Behemoth remain open-weight and available through dozens of third-party providers. Because Llama weights are open, teams can self-host on GPU cloud for dramatically lower per-token costs at scale.

The only frontier-class model family available as open weights — plus the Muse product line (Spark, Glimmer, Image, Voice) for teams that want managed API access without self-hosting.

Key strengths compared

GreenPT

    Meta

    • Open-weight Llama 4 models — self-host on any GPU cloud for lowest per-token cost at scale
    • Muse Spark 1.3: flagship multimodal model with 1M context window
    • Muse Image and Muse Voice for image generation and speech synthesis
    • Self-hosting requires GPU infrastructure expertise
    • Meta Model API has limited availability vs third-party hosts

    Key weaknesses compared

    GreenPT

      Meta

      • Self-hosting requires GPU infrastructure expertise
      • Meta Model API has limited availability vs third-party hosts
      • Muse Spark 1.3 pricing not yet publicly listed at launch
      • Smaller proprietary model lineup vs OpenAI/Anthropic

      Provider category context

      GreenPT is a inference api. Meta is a open source host, founded in 2023. The category difference means these providers serve partially overlapping use cases — compare the model lists and pricing tables above to find the best fit for your specific workload.

      How to choose between them

      Choose GreenPT if you need . Choose Meta if you need open-weight llama 4 models — self-host on any gpu cloud for lowest per-token cost at scale. For high-volume production workloads, run a cost comparison using the token pricing table above with your actual prompt/completion token ratio — the cheapest provider depends heavily on your input-to-output token ratio.