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AI21 Labs vs FastInfra: Token Pricing, Speed & Intelligence

Full comparison of AI21 Labs and FastInfra — live token pricing, latency, throughput, context window, strengths, weaknesses, and best use cases. Rates sourced from public APIs — verify before use.

AI21 Labs

Jamba 1.6 — hybrid SSM-Transformer models with 256K context

AI21 Labs develops the Jamba model family, which uses a hybrid SSM (Mamba) and Transformer architecture. Jamba 1.6 Large and Mini offer 256K token context windows at competitive prices. The hybrid architecture delivers faster inference and lower memory usage than pure-Transformer models of comparable size.

Long-context chatDocument analysisSummarisationCost-sensitive inference
Proprietary models

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

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

AI21 Labs

Hybrid SSM-Transformer architecture delivers faster inference than pure-Transformer models
256K token context window on both Jamba 1.6 Large and Mini
Jamba 1.6 Mini at $0.20/$0.40 per 1M tokens is highly cost-competitive
Strong performance on long-document tasks due to SSM efficiency
Smaller model family than frontier labs — two models vs dozens at OpenAI or Anthropic
Less ecosystem support than OpenAI-compatible providers
No image, audio, or multimodal models

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

Key differentiators

AI21 Labs

Jamba's hybrid SSM-Transformer architecture enables 256K context at lower memory and latency cost than pure-Transformer models — with Jamba 1.6 Mini among the cheapest 256K-context options available.

FastInfra

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

Frequently asked questions

AI21 Labs FAQs

What is the Jamba architecture?

Jamba uses a hybrid of Mamba (SSM) and Transformer layers. This reduces memory usage and improves throughput on long sequences compared to pure-Transformer models, while maintaining strong reasoning performance.

How much does AI21 Labs API cost?

Jamba 1.6 Large is $2.00/$8.00 per 1M input/output tokens. Jamba 1.6 Mini is $0.20/$0.40 per 1M tokens. Both support 256K context. See ai21.com/pricing for current rates.

What context window does Jamba 1.6 support?

Both Jamba 1.6 Large and Jamba 1.6 Mini support 256K token context windows, making them suitable for long-document analysis and extended conversations.

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.

Provider resources

AI21 Labs — Jamba 1.6 — hybrid SSM-Transformer models with 256K context

AI21 Labs develops the Jamba model family, which uses a hybrid SSM (Mamba) and Transformer architecture. Jamba 1.6 Large and Mini offer 256K token context windows at competitive prices. The hybrid architecture delivers faster inference and lower memory usage than pure-Transformer models of comparable size.

Jamba's hybrid SSM-Transformer architecture enables 256K context at lower memory and latency cost than pure-Transformer models — with Jamba 1.6 Mini among the cheapest 256K-context options available.

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.

Key strengths compared

AI21 Labs

  • Hybrid SSM-Transformer architecture delivers faster inference than pure-Transformer models
  • 256K token context window on both Jamba 1.6 Large and Mini
  • Jamba 1.6 Mini at $0.20/$0.40 per 1M tokens is highly cost-competitive
  • Smaller model family than frontier labs — two models vs dozens at OpenAI or Anthropic
  • Less ecosystem support than OpenAI-compatible providers

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

Key weaknesses compared

AI21 Labs

  • Smaller model family than frontier labs — two models vs dozens at OpenAI or Anthropic
  • Less ecosystem support than OpenAI-compatible providers
  • No image, audio, or multimodal models

FastInfra

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

Provider category context

AI21 Labs is a frontier lab, founded in 2017. FastInfra is a inference api, founded in 2024. AI21 Labs as a frontier lab trains and serves its own proprietary models. FastInfra as an inference API provider hosts open-weight models — typically offering lower prices for equivalent capability tiers but without access to proprietary frontier models.

How to choose between them

Choose AI21 Labs if you need Long-context tasks. Choose FastInfra if you need Cost-sensitive workloads. 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.