Groq vs TensorX: Token Pricing, Speed & Intelligence
Full comparison of Groq and TensorX — live token pricing, latency, throughput, context window, strengths, weaknesses, and best use cases. Rates sourced from public APIs — verify before use.
Groq
LPU + LPX inference — high-throughput tokens per second, $350M Series A
Groq runs custom Language Processing Units (LPUs) and the newer LPX chips that work alongside NVIDIA next-generation GPUs for high-throughput inference. Groq raised a $350M Series A in 2026 and is building hundreds of megawatts of capacity. Check listed rates and provider documentation for current model availability and throughput figures.
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.
Key metric comparison
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Live token pricing
Strengths and weaknesses
Groq
TensorX
Key differentiators
Groq's custom LPU/LPX chips deliver high-throughput inference significantly faster than conventional GPU systems, backed by $350M in Series A funding and hundreds of megawatts of planned capacity.
EU inference with nodes in Dublin, Helsinki, and Paris, zero data retention, and prompt caching on GLM-5.3.
Frequently asked questions
Groq FAQs
How fast is Groq inference?
Groq delivers 750+ tokens/second on Llama 3.3 70B and 1,200+ tokens/second on Llama 3.1 8B using custom LPU/LPX chips, making it well-suited for real-time and low-latency applications.
What is Groq's LPX chip?
The LPX is Groq's next-generation inference chip, introduced alongside the existing LPU lineup. It expands Groq's capacity and enables even higher throughput for large-scale deployments.
How much does Groq cost?
Groq uses per-token pricing across its model catalog. Check console.groq.com/docs/openai for current rates on Llama 3.3 70B, Llama 3.1 8B, and other models.
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.
Provider resources
Groq — LPU + LPX inference — high-throughput tokens per second, $350M Series A
Groq runs custom Language Processing Units (LPUs) and the newer LPX chips that work alongside NVIDIA next-generation GPUs for high-throughput inference. Groq raised a $350M Series A in 2026 and is building hundreds of megawatts of capacity. Check listed rates and provider documentation for current model availability and throughput figures.
Groq's custom LPU/LPX chips deliver high-throughput inference significantly faster than conventional GPU systems, backed by $350M in Series A funding and hundreds of megawatts of planned capacity.
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.
Key strengths compared
Groq
- 750+ tokens/sec on Llama 3.3 70B — high-throughput GPU-class inference (Groq-published)
- Sub-100ms time-to-first-token for real-time applications
- LPX chips alongside LPUs for expanded capacity
- Limited model selection vs. Together AI or Fireworks
- No vision model support on most models
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
Key weaknesses compared
Groq
- Limited model selection vs. Together AI or Fireworks
- No vision model support on most models
- No fine-tuning capability
TensorX
- Small model catalog
- Prepaid credits only — no post-pay billing
- Newer provider — limited third-party benchmark transparency
Provider category context
Groq is a inference api, founded in 2016. TensorX is a inference api, founded in 2024. Both are inference api providers — the comparison is primarily about pricing, model selection, and feature differentiation within the same tier.
How to choose between them
Both Groq and TensorX host open-weight models. The key differentiators are latency, throughput, and which specific model versions each provider offers. Check the speed metrics above — inference API providers often differ significantly on tokens-per-second for the same model. Pricing is typically competitive between them; availability of specific model versions (e.g., Llama 3.1 405B, DeepSeek V3) may be the deciding factor.