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TensorX vs Xiaomi MiMo: Token Pricing, Speed & Intelligence

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

TensorX

EU inference — Dublin, Helsinki, Paris — GLM-5.3, Kimi K3, zero data retention

TensorX is an EU inference provider with nodes in Dublin, Helsinki, and Paris. It offers GLM-5.3, Kimi K3, and GLM-5.3 Flash with zero data retention and prepaid credits. USD pricing. Suited for EU workloads that need geographic diversity within Europe and a zero-retention policy.

EU inferencePrivacy-sensitive workloadsGeographic diversity
Open-weight hostHosts open weights

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.

ReasoningMathCodingLong-contextCost-efficiency
Proprietary models

Key metric comparison

Cheapest input ($/1M)

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Cheapest output ($/1M)

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Peak throughput

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Best latency (TTFT)

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Intelligence score

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Context window

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Live token pricing

Strengths and weaknesses

TensorX

EU nodes in Dublin, Helsinki, and Paris — geographic diversity
Zero data retention policy
Prompt caching on GLM-5.3 (cached $0.44/1M vs $1.75/1M standard)
USD pricing — no currency conversion for international customers
Small model catalog
Prepaid credits only — no post-pay billing
Newer provider — limited third-party benchmark transparency

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
Competitive input/output pricing across the model family
Smaller ecosystem than OpenAI or Anthropic
Limited English-language documentation
Newer platform — less battle-tested at scale

Key differentiators

TensorX

EU inference with nodes in Dublin, Helsinki, and Paris, zero data retention, and prompt caching on GLM-5.3.

Xiaomi MiMo

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

TensorX FAQs

What is TensorX?

TensorX is an EU inference provider with nodes in Dublin, Helsinki, and Paris. It offers GLM-5.3, Kimi K3, and GLM-5.3 Flash with zero data retention and prepaid credits. See tensorx.ai/pricing for current rates.

Does TensorX retain my data?

No. TensorX operates a zero data retention policy.

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

TensorX — EU inference — Dublin, Helsinki, Paris — GLM-5.3, Kimi K3, zero data retention

TensorX is an EU inference provider with nodes in Dublin, Helsinki, and Paris. It offers GLM-5.3, Kimi K3, and GLM-5.3 Flash with zero data retention and prepaid credits. USD pricing. Suited for EU workloads that need geographic diversity within Europe and a zero-retention policy.

EU inference with nodes in Dublin, Helsinki, and Paris, zero data retention, and prompt caching on GLM-5.3.

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

TensorX

  • EU nodes in Dublin, Helsinki, and Paris — geographic diversity
  • Zero data retention policy
  • Prompt caching on GLM-5.3 (cached $0.44/1M vs $1.75/1M standard)
  • Small model catalog
  • Prepaid credits only — no post-pay billing

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

TensorX

  • Small model catalog
  • Prepaid credits only — no post-pay billing
  • Newer provider — limited third-party benchmark transparency

Xiaomi MiMo

  • Smaller ecosystem than OpenAI or Anthropic
  • Limited English-language documentation
  • Newer platform — less battle-tested at scale

Provider category context

TensorX is a inference api, founded in 2024. Xiaomi MiMo is a frontier lab, founded in 2024 (as LLM service). TensorX 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 TensorX if you need EU inference. 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.