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Jamba 1.5 MinivsJamba 1.5 Large

AI21 Labs vs AI21 Labs — Side-by-side model comparison

Jamba 1.5 Mini leads 2/5 categories

Head-to-Head Comparison

MetricJamba 1.5 MiniJamba 1.5 Large
Provider
Arena Rank
Context Window
256K
256K
Input Pricing
$0.20/1M tokens
$2.00/1M tokens
Output Pricing
$0.40/1M tokens
$8.00/1M tokens
Parameters
52B (12B active)
398B (94B active)
Open Source
Yes
Yes
Best For
Cost-effective long-context, summarization
Long documents, enterprise RAG, analysis
Release Date
Aug 22, 2024
Aug 22, 2024

Jamba 1.5 Mini

Jamba 1.5 Mini is AI21 Labs' efficient model sharing the same hybrid SSM-Transformer architecture as its larger sibling. At 52 billion total parameters with only 12 billion active, it delivers strong performance on long-context tasks while being highly cost-effective. The 256K context window combined with low inference costs makes it particularly attractive for applications processing large volumes of documents.

View AI21 Labs profile →

Jamba 1.5 Large

Jamba 1.5 Large is AI21 Labs' flagship model based on their novel hybrid SSM-Transformer architecture that combines the efficiency of state-space models with the capabilities of transformers. With a 256K context window and 398 billion total parameters, it processes extremely long documents efficiently while delivering strong performance on reasoning and generation tasks. The unique architecture offers better throughput than pure transformer models at equivalent quality.

View AI21 Labs profile →

Key Differences: Jamba 1.5 Mini vs Jamba 1.5 Large

1

Jamba 1.5 Mini is 16.7x cheaper on average, making it the better choice for high-volume applications.

2

Jamba 1.5 Mini has 52B (12B active) parameters vs Jamba 1.5 Large's 398B (94B active), which affects inference speed and capability.

J

When to use Jamba 1.5 Mini

  • +Budget is a concern and you need cost efficiency
  • +Your use case involves cost-effective long-context, summarization
View full Jamba 1.5 Mini specs →
J

When to use Jamba 1.5 Large

  • +Quality matters more than cost
  • +Your use case involves long documents, enterprise rag, analysis
View full Jamba 1.5 Large specs →

Cost Analysis

At current pricing, Jamba 1.5 Mini is 16.7x more affordable than Jamba 1.5 Large. For a typical enterprise workload processing 100M tokens per month:

Jamba 1.5 Mini monthly cost

$30

100M tokens/mo (50/50 in/out)

Jamba 1.5 Large monthly cost

$500

100M tokens/mo (50/50 in/out)

The Verdict

Jamba 1.5 Mini wins our head-to-head comparison with 2 out of 5 category wins. It's the stronger choice for cost-effective long-context, summarization, though Jamba 1.5 Large holds an edge in long documents, enterprise rag, analysis.

Last compared: March 2026 · Data sourced from public benchmarks and official pricing pages

Frequently Asked Questions

Which is better, Jamba 1.5 Mini or Jamba 1.5 Large?
In our head-to-head comparison, Jamba 1.5 Mini leads in 2 out of 5 categories (arena rank, context window, input pricing, output pricing, and parameters). Jamba 1.5 Mini excels at cost-effective long-context, summarization, while Jamba 1.5 Large is better suited for long documents, enterprise rag, analysis. The best choice depends on your specific requirements, budget, and use case.
How does Jamba 1.5 Mini pricing compare to Jamba 1.5 Large?
Jamba 1.5 Mini charges $0.20 per 1M input tokens and $0.40 per 1M output tokens. Jamba 1.5 Large charges $2.00 per 1M input tokens and $8.00 per 1M output tokens. Jamba 1.5 Mini is the more affordable option, approximately 16.7x cheaper on average. For high-volume production workloads, the pricing difference can significantly impact total cost of ownership.
What is the context window difference between Jamba 1.5 Mini and Jamba 1.5 Large?
Jamba 1.5 Mini supports a 256K token context window, while Jamba 1.5 Large supports 256K tokens. Context window size matters most for tasks involving long documents, large codebases, or extended conversations.
Can I use Jamba 1.5 Mini or Jamba 1.5 Large for free?
Jamba 1.5 Mini is a paid API model starting at $0.20 per 1M input tokens. Jamba 1.5 Large is a paid API model starting at $2.00 per 1M input tokens. Open-source models can be self-hosted for free but require your own GPU infrastructure.
Which model has better benchmarks, Jamba 1.5 Mini or Jamba 1.5 Large?
Jamba 1.5 Mini's arena rank is not yet available, while Jamba 1.5 Large's rank is not yet available. Note that benchmarks don't capture every use case — we recommend testing both models on your specific tasks.
Is Jamba 1.5 Mini or Jamba 1.5 Large better for coding?
Jamba 1.5 Mini's primary strength is cost-effective long-context, summarization. Jamba 1.5 Large's primary strength is long documents, enterprise rag, analysis. For coding specifically, arena rank and code-specific benchmarks are the best indicators of performance.