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FastInfra vs Together AI: Token Pricing, Speed & Intelligence

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

FastInfra

Inference platform + GPU pods — 785+ models, Amazon Nova, H200 capacity

FastInfra is a hybrid inference platform combining a model router (785+ models) with its own H200 GPU capacity. It offers Amazon Nova Lite and Nova Micro at very competitive rates, with prepaid credits from $5. Part inference router, part dedicated GPU cloud.

Cost-sensitive workloadsBroad model accessAmazon Nova inference
Open-weight hostHosts open weights

Together AI

MiniMax M3, Kimi K3, GLM-5.3, DeepSeek V4 Pro, gpt-oss-120B — plus GB200/B200 GPU clusters

Together AI offers hosted inference for open-weight models, GPU clusters, provisioned throughput and fine-tuning. Compare listed rates and check the provider for current models, availability and terms.

Open-sourceFine-tuningCodingChatCost-efficiencyModel varietyGPU compute
Open-weight hostHosts open weights

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

FastInfra

785+ models via router — broad catalog coverage
Own H200 GPU capacity for low-latency inference
Very competitive Amazon Nova Lite ($0.06/$0.25) and Nova Micro ($0.04/$0.15) rates
Prepaid from $5 — low barrier to entry
Newer provider — limited ecosystem integrations and third-party reviews
Hybrid router/own-capacity model means latency may vary by model
Limited benchmark transparency

Together AI

Open-model catalog — MiniMax M3, Kimi K3, GLM-5.3, DeepSeek V4 Pro, gpt-oss-120B, Qwen3.x, Llama 4
GB200/B200/H200/H100 GPU clusters with preemptible and reserved pricing
Provisioned Throughput (PTUs) for SLA-backed capacity
Serverless Training API for fine-tuning without infrastructure
Fine-tuning for Llama 4, Qwen3.5, DeepSeek, GLM, and more
OpenAI-compatible API — easy migration
No proprietary frontier models
Throughput lower than Groq/Cerebras for speed-critical apps
Fine-tuning adds complexity vs. pure inference providers

Key differentiators

FastInfra

Hybrid inference platform with 785+ models via router and own H200 capacity, offering Amazon Nova at very competitive rates.

Together AI

An open-weight model catalog — MiniMax M3, Kimi K3, GLM-5.3, DeepSeek V4 Pro, gpt-oss-120B — with GPU clusters (GB200/B200), Provisioned Throughput, and a Serverless Training API.

Frequently asked questions

FastInfra FAQs

What is FastInfra?

FastInfra is a hybrid inference platform combining a 785+ model router with its own H200 GPU capacity. It offers Amazon Nova Lite ($0.06/$0.25 per 1M tokens) and Nova Micro ($0.04/$0.15), with prepaid credits from $5. See fastinfra.ai/pricing for current rates.

Does FastInfra have its own GPU capacity?

Yes. FastInfra operates its own H200 GPU infrastructure alongside a model router, so some models run on dedicated capacity rather than being routed to third-party providers.

Together AI FAQs

What new models did Together AI add in 2026?

Together AI expanded its catalog with MiniMax M3, Kimi K3, GLM-5.3, DeepSeek V4 Pro 0813, gpt-oss-120B, Muse Glimmer 30B, and the full Qwen3.x family. Check api.together.ai/models for current pricing.

How much does Together AI cost?

Together AI uses per-token pricing across its model catalog. Check api.together.ai/models for current rates on MiniMax M3, DeepSeek V4 Pro, GLM-5.3, Llama 3.3 70B, and other models.

Does Together AI offer GPU compute?

Yes. Together AI offers GPU clusters with H100, H200, B200, and GB200/GB300 NVL72 (contact sales). Check together.ai/pricing for current GPU compute rates.

Provider resources

FastInfra — Inference platform + GPU pods — 785+ models, Amazon Nova, H200 capacity

FastInfra is a hybrid inference platform combining a model router (785+ models) with its own H200 GPU capacity. It offers Amazon Nova Lite and Nova Micro at very competitive rates, with prepaid credits from $5. Part inference router, part dedicated GPU cloud.

Hybrid inference platform with 785+ models via router and own H200 capacity, offering Amazon Nova at very competitive rates.

Together AI — MiniMax M3, Kimi K3, GLM-5.3, DeepSeek V4 Pro, gpt-oss-120B — plus GB200/B200 GPU clusters

Together AI offers hosted inference for open-weight models, GPU clusters, provisioned throughput and fine-tuning. Compare listed rates and check the provider for current models, availability and terms.

An open-weight model catalog — MiniMax M3, Kimi K3, GLM-5.3, DeepSeek V4 Pro, gpt-oss-120B — with GPU clusters (GB200/B200), Provisioned Throughput, and a Serverless Training API.

Key strengths compared

FastInfra

  • 785+ models via router — broad catalog coverage
  • Own H200 GPU capacity for low-latency inference
  • Very competitive Amazon Nova Lite ($0.06/$0.25) and Nova Micro ($0.04/$0.15) rates
  • Newer provider — limited ecosystem integrations and third-party reviews
  • Hybrid router/own-capacity model means latency may vary by model

Together AI

  • Open-model catalog — MiniMax M3, Kimi K3, GLM-5.3, DeepSeek V4 Pro, gpt-oss-120B, Qwen3.x, Llama 4
  • GB200/B200/H200/H100 GPU clusters with preemptible and reserved pricing
  • Provisioned Throughput (PTUs) for SLA-backed capacity
  • No proprietary frontier models
  • Throughput lower than Groq/Cerebras for speed-critical apps

Key weaknesses compared

FastInfra

  • Newer provider — limited ecosystem integrations and third-party reviews
  • Hybrid router/own-capacity model means latency may vary by model
  • Limited benchmark transparency

Together AI

  • No proprietary frontier models
  • Throughput lower than Groq/Cerebras for speed-critical apps
  • Fine-tuning adds complexity vs. pure inference providers

Provider category context

FastInfra is a inference api, founded in 2024. Together AI is a inference api, founded in 2022. 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 FastInfra and Together AI 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.