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AI21 Labs vs Together AI: Token Pricing, Speed & Intelligence

Full comparison of AI21 Labs and Together AI — 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

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

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

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

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.

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

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.

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

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.

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

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

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

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

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

AI21 Labs is a frontier lab, founded in 2017. Together AI is a inference api, founded in 2022. AI21 Labs as a frontier lab trains and serves its own proprietary models. Together AI 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 Together AI if you need open-model catalog — minimax m3, kimi k3, glm-5.3, deepseek v4 pro, gpt-oss-120b, qwen3.x, llama 4. 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.