AI21 Labs vs Parasail: Token Pricing, Speed & Intelligence
Full comparison of AI21 Labs and Parasail — 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.
Parasail
Serverless inference — Kimi K3, GLM-5.3, MiniMax M3, DeepSeek V4, Qwen3.5, Llama 4
Parasail is a serverless LLM inference platform offering a broad catalog of open-weight models including Kimi K3, Kimi K2.6, GLM-5.3, GLM-5.3 Flash, MiniMax M3, DeepSeek V4 Pro/Flash, Qwen3.5 397B-A17B, Qwen3 235B-A22B, Llama 4 Maverick, Llama 3.3 70B, Mistral Small 3.2 24B, MiMo v2.5, Gemma 4 31B, gpt-oss-120b, and gpt-oss-20b. Pricing is published at parasail.io/pricing.
Key metric comparison
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Live token pricing
Strengths and weaknesses
AI21 Labs
Parasail
Key differentiators
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.
One of the broadest serverless open-weight catalogs available — Kimi K3, GLM-5.3, MiniMax M3, DeepSeek V4, Qwen3.5, and Llama 4 Maverick at competitive per-token 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.
Parasail FAQs
What is Parasail?
Parasail is a serverless LLM inference platform offering a broad catalog of open-weight models. See parasail.io/pricing for current rates and model availability.
What models does Parasail offer?
Parasail's catalog includes Kimi K3, Kimi K2.6, GLM-5.3, GLM-5.3 Flash, MiniMax M3, DeepSeek V4 Pro/Flash, Qwen3.5 397B-A17B, Qwen3 235B-A22B, Llama 4 Maverick, Llama 3.3 70B, Mistral Small 3.2 24B, MiMo v2.5, Gemma 4 31B, gpt-oss-120b, and gpt-oss-20b. See parasail.io/pricing for current rates.
How much does Parasail cost?
As of October 2026: Kimi K3 $3.00/$15.00, Kimi K2.6 $0.75/$3.50, GLM-5.3 $1.40/$4.40, GLM-5.3 Flash $0.15/$0.50, MiniMax M3 $0.30/$1.20, DeepSeek V4 Pro $1.74/$3.48, DeepSeek V4 Flash $0.14/$0.28. See parasail.io/pricing for current 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.
Parasail — Serverless inference — Kimi K3, GLM-5.3, MiniMax M3, DeepSeek V4, Qwen3.5, Llama 4
Parasail is a serverless LLM inference platform offering a broad catalog of open-weight models including Kimi K3, Kimi K2.6, GLM-5.3, GLM-5.3 Flash, MiniMax M3, DeepSeek V4 Pro/Flash, Qwen3.5 397B-A17B, Qwen3 235B-A22B, Llama 4 Maverick, Llama 3.3 70B, Mistral Small 3.2 24B, MiMo v2.5, Gemma 4 31B, gpt-oss-120b, and gpt-oss-20b. Pricing is published at parasail.io/pricing.
One of the broadest serverless open-weight catalogs available — Kimi K3, GLM-5.3, MiniMax M3, DeepSeek V4, Qwen3.5, and Llama 4 Maverick at competitive per-token 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
Parasail
- Broad open-weight model catalog: Kimi K3, GLM-5.3, MiniMax M3, DeepSeek V4, Qwen3.5, Llama 4
- Competitive serverless pricing across all tiers
- Kimi K3 and Kimi K2.6 availability — rare outside Chinese providers
- Newer platform — less battle-tested than Together AI or Fireworks
- No proprietary frontier models
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
Parasail
- Newer platform — less battle-tested than Together AI or Fireworks
- No proprietary frontier models
- Smaller community and ecosystem
Provider category context
AI21 Labs is a frontier lab, founded in 2017. Parasail is a inference api, founded in 2023. AI21 Labs as a frontier lab trains and serves its own proprietary models. Parasail 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 Parasail if you need broad open-weight model catalog: kimi k3, glm-5.3, minimax m3, deepseek v4, qwen3.5, 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.