Hyperbolic vs Xiaomi MiMo: Token Pricing, Speed & Intelligence
Full comparison of Hyperbolic and Xiaomi MiMo — live token pricing, latency, throughput, context window, strengths, weaknesses, and best use cases. Rates sourced from public APIs — verify before use.
Hyperbolic
GPU marketplace + inference API — Llama 4, DeepSeek V4 Pro, and H100/H200 on-demand
Hyperbolic operates both a GPU marketplace and a serverless inference API. The inference catalog has expanded in 2026 to include Llama 4 Scout/Maverick, DeepSeek V4 Pro, Kimi K3, and Qwen3 alongside the existing Llama 3.x and DeepSeek R1 lineup. The GPU marketplace offers H100 and H200 instances at spot-market rates, making Hyperbolic a dual-purpose platform for both managed inference and raw compute.
Xiaomi MiMo
MiMo-V2.5-Pro, MiMo-V2.5, MiMo-V2.5-Pro-UltraSpeed — reasoning-focused models from Xiaomi
Xiaomi MiMo is the LLM inference platform from Xiaomi, offering the MiMo model family: MiMo-V2.5-Pro (flagship, 1M context), MiMo-V2.5 (efficient), and MiMo-V2.5-Pro-UltraSpeed (high-throughput). The MiMo models are reasoning-focused, with strong performance on math and coding benchmarks. Pricing is published at platform.xiaomimimo.com/docs/pricing.
Key metric comparison
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Live token pricing
Strengths and weaknesses
Hyperbolic
Xiaomi MiMo
Key differentiators
A provider combining a GPU marketplace (H100/H200 spot pricing) with a broad open-weight inference API — covering both managed inference and raw compute from a single platform.
Xiaomi's reasoning-focused MiMo model family with 1M context on the Pro tier and a UltraSpeed variant for high-throughput inference at competitive per-token rates.
Frequently asked questions
Hyperbolic FAQs
What models does Hyperbolic offer in 2026?
Hyperbolic hosts Llama 4 Scout and Maverick, DeepSeek V4 Pro, Kimi K3, Qwen3, Llama 3.3 70B, DeepSeek R1, and other popular open-weight models. The catalog is updated frequently as new models are released.
Does Hyperbolic offer GPU compute as well as inference?
Yes. Hyperbolic operates a GPU marketplace offering H100 and H200 instances at spot-market rates. This makes it a dual-purpose platform for teams that need both managed inference and raw GPU access.
How does Hyperbolic pricing compare to competitors?
Hyperbolic is among the most affordable options for open-weight model inference, often undercutting Together AI and Fireworks AI on price. GPU marketplace rates are competitive with other spot GPU providers.
Xiaomi MiMo FAQs
What is Xiaomi MiMo?
Xiaomi MiMo is Xiaomi's LLM inference platform, offering the MiMo-V2.5 model family. MiMo-V2.5-Pro supports 1M context, MiMo-V2.5 is the efficient tier, and MiMo-V2.5-Pro-UltraSpeed is optimised for high-throughput workloads. See platform.xiaomimimo.com/docs/pricing for current rates.
What context window does MiMo-V2.5-Pro support?
MiMo-V2.5-Pro supports a 1M token context window, enabling full-document and long-context workloads in a single API call.
How much does Xiaomi MiMo cost?
As of October 2026: MiMo-V2.5-Pro $0.435/$0.87 per 1M tokens (input/output), MiMo-V2.5 $0.14/$0.28, MiMo-V2.5-Pro-UltraSpeed $1.305/$2.61. See platform.xiaomimimo.com/docs/pricing for current rates.
Provider resources
Hyperbolic — GPU marketplace + inference API — Llama 4, DeepSeek V4 Pro, and H100/H200 on-demand
Hyperbolic operates both a GPU marketplace and a serverless inference API. The inference catalog has expanded in 2026 to include Llama 4 Scout/Maverick, DeepSeek V4 Pro, Kimi K3, and Qwen3 alongside the existing Llama 3.x and DeepSeek R1 lineup. The GPU marketplace offers H100 and H200 instances at spot-market rates, making Hyperbolic a dual-purpose platform for both managed inference and raw compute.
A provider combining a GPU marketplace (H100/H200 spot pricing) with a broad open-weight inference API — covering both managed inference and raw compute from a single platform.
Xiaomi MiMo — MiMo-V2.5-Pro, MiMo-V2.5, MiMo-V2.5-Pro-UltraSpeed — reasoning-focused models from Xiaomi
Xiaomi MiMo is the LLM inference platform from Xiaomi, offering the MiMo model family: MiMo-V2.5-Pro (flagship, 1M context), MiMo-V2.5 (efficient), and MiMo-V2.5-Pro-UltraSpeed (high-throughput). The MiMo models are reasoning-focused, with strong performance on math and coding benchmarks. Pricing is published at platform.xiaomimimo.com/docs/pricing.
Xiaomi's reasoning-focused MiMo model family with 1M context on the Pro tier and a UltraSpeed variant for high-throughput inference at competitive per-token rates.
Key strengths compared
Hyperbolic
- GPU marketplace: H100 and H200 at spot-market rates
- Expanded 2026 inference catalog: Llama 4, DeepSeek V4 Pro, Kimi K3, Qwen3
- Among the lowest per-token prices for open-weight inference
- Less established reliability than larger providers
- Throughput lower than Groq/Cerebras for speed-critical apps
Xiaomi MiMo
- MiMo-V2.5-Pro: 1M context window at competitive pricing
- MiMo-V2.5-Pro-UltraSpeed: high-throughput variant for latency-sensitive workloads
- Reasoning-focused architecture — strong on math and coding
- Smaller ecosystem than OpenAI or Anthropic
- Limited English-language documentation
Key weaknesses compared
Hyperbolic
- Less established reliability than larger providers
- Throughput lower than Groq/Cerebras for speed-critical apps
- No fine-tuning support
Xiaomi MiMo
- Smaller ecosystem than OpenAI or Anthropic
- Limited English-language documentation
- Newer platform — less battle-tested at scale
Provider category context
Hyperbolic is a inference api, founded in 2023. Xiaomi MiMo is a frontier lab, founded in 2024 (as LLM service). Hyperbolic as an inference API provider hosts open-weight models — typically offering lower prices for equivalent capability tiers. Xiaomi MiMo as a frontier lab trains and serves proprietary models with capabilities not available elsewhere.
How to choose between them
Choose Hyperbolic if you need gpu marketplace: h100 and h200 at spot-market rates. Choose Xiaomi MiMo if you need mimo-v2.5-pro: 1m context window at competitive pricing. 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.