AI21 Labs vs Berget AI: Token Pricing, Speed & Intelligence
Full comparison of AI21 Labs and Berget 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.
Berget AI
European AI inference — Mistral Small and GLM-5.3-Flash, priced in EUR ex-VAT
Berget AI is a Swedish AI inference provider offering open-weight models including Mistral-Small-3.2-24B-Instruct-2506 and GLM-5.3-Flash. Pricing is in EUR and excludes VAT. Continued API use requires a prepaid plan from EUR 25/month — it is not a pure no-plan pay-as-you-go service. Berget AI is positioned as a European-hosted alternative for teams with data-residency or regulatory requirements.
Key metric comparison
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Live token pricing
Strengths and weaknesses
AI21 Labs
Berget AI
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.
European-hosted AI inference with EUR pricing and GDPR-friendly data residency — Mistral Small 3.2 and GLM-5.3-Flash from a Swedish provider.
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.
Berget AI FAQs
What is Berget AI?
Berget AI is a Swedish AI inference provider offering open-weight models including Mistral-Small-3.2-24B-Instruct-2506 and GLM-5.3-Flash. Pricing is in EUR and excludes VAT. See berget.ai/en/pricing for current rates.
How much does Berget AI cost?
As of October 2026: Mistral-Small-3.2-24B-Instruct-2506 is EUR 0.30 input / EUR 0.30 output per 1M tokens; GLM-5.3-Flash is EUR 0.25 input / EUR 0.50 output per 1M tokens. Prices exclude VAT. See berget.ai/en/pricing for current rates.
Does Berget AI require a subscription?
Continued API use requires a prepaid plan from EUR 25/month. It is not a pure no-plan pay-as-you-go service. See berget.ai/en/pricing for plan details.
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.
Berget AI — European AI inference — Mistral Small and GLM-5.3-Flash, priced in EUR ex-VAT
Berget AI is a Swedish AI inference provider offering open-weight models including Mistral-Small-3.2-24B-Instruct-2506 and GLM-5.3-Flash. Pricing is in EUR and excludes VAT. Continued API use requires a prepaid plan from EUR 25/month — it is not a pure no-plan pay-as-you-go service. Berget AI is positioned as a European-hosted alternative for teams with data-residency or regulatory requirements.
European-hosted AI inference with EUR pricing and GDPR-friendly data residency — Mistral Small 3.2 and GLM-5.3-Flash from a Swedish provider.
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
Berget AI
- European-hosted inference — suitable for EU data-residency and GDPR requirements
- Mistral Small 3.2 and GLM-5.3-Flash at competitive EUR rates
- EUR-denominated pricing — no FX risk for European teams
- Prepaid plan from EUR 25/month required for continued API access — not pure PAYG
- Prices exclude VAT — effective cost is higher for non-VAT-registered users
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
Berget AI
- Prepaid plan from EUR 25/month required for continued API access — not pure PAYG
- Prices exclude VAT — effective cost is higher for non-VAT-registered users
- Small catalog compared to global inference APIs
Provider category context
AI21 Labs is a frontier lab, founded in 2017. Berget AI is a inference api, founded in 2023. AI21 Labs as a frontier lab trains and serves its own proprietary models. Berget 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 Berget AI if you need european-hosted inference — suitable for eu data-residency and gdpr requirements. 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.