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Jamba 1.5 MinivsGPT-o3

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

Jamba 1.5 Mini leads 4/5 categories

Head-to-Head Comparison

MetricJamba 1.5 MiniGPT-o3
Provider
Arena Rank
#2
Context Window
256K
200K
Input Pricing
$0.20/1M tokens
$2.00/1M tokens
Output Pricing
$0.40/1M tokens
$8.00/1M tokens
Parameters
52B (12B active)
Undisclosed
Open Source
Yes
No
Best For
Cost-effective long-context, summarization
Advanced reasoning, agentic tasks, research
Release Date
Aug 22, 2024
Apr 16, 2025

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 →

GPT-o3

GPT-o3 is OpenAI's most advanced reasoning model, succeeding o1 as the frontier of deliberative AI. It uses an enhanced chain-of-thought approach where the model spends more compute time 'thinking' before responding, dramatically improving performance on complex STEM, mathematical, and logical reasoning tasks. With a 200K token context window and the ability to use tools during reasoning, o3 represents a significant leap in AI problem-solving capabilities. It achieved state-of-the-art results on the ARC-AGI benchmark, demonstrating near-human performance on novel reasoning challenges. The model is particularly strong at multi-step mathematical proofs, complex code debugging, and scientific analysis where careful step-by-step reasoning is essential. Originally priced at a premium, an 80% price reduction in June 2025 made o3 accessible to a much broader range of developers and applications.

View OpenAI profile →

Key Differences: Jamba 1.5 Mini vs GPT-o3

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 supports a larger context window (256K), allowing it to process longer documents in a single request.

3

Jamba 1.5 Mini is open-source (free to self-host and fine-tune) while GPT-o3 is proprietary (API-only access).

J

When to use Jamba 1.5 Mini

  • +Budget is a concern and you need cost efficiency
  • +You need to process long documents (256K context)
  • +You need to self-host or fine-tune the model
  • +Your use case involves cost-effective long-context, summarization
View full Jamba 1.5 Mini specs →
G

When to use GPT-o3

  • +Quality matters more than cost
  • +You prefer a managed API without infrastructure overhead
  • +Your use case involves advanced reasoning, agentic tasks, research
View full GPT-o3 specs →

Cost Analysis

At current pricing, Jamba 1.5 Mini is 16.7x more affordable than GPT-o3. For a typical enterprise workload processing 100M tokens per month:

Jamba 1.5 Mini monthly cost

$30

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

GPT-o3 monthly cost

$500

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

The Verdict

Jamba 1.5 Mini wins our head-to-head comparison with 4 out of 5 category wins. It's the stronger choice for cost-effective long-context, summarization, though GPT-o3 holds an edge in advanced reasoning, agentic tasks, research.

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

Frequently Asked Questions

Which is better, Jamba 1.5 Mini or GPT-o3?
In our head-to-head comparison, Jamba 1.5 Mini leads in 4 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 GPT-o3 is better suited for advanced reasoning, agentic tasks, research. The best choice depends on your specific requirements, budget, and use case.
How does Jamba 1.5 Mini pricing compare to GPT-o3?
Jamba 1.5 Mini charges $0.20 per 1M input tokens and $0.40 per 1M output tokens. GPT-o3 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 GPT-o3?
Jamba 1.5 Mini supports a 256K token context window, while GPT-o3 supports 200K tokens. Jamba 1.5 Mini can process longer documents, codebases, and conversations in a single request. Context window size matters most for tasks involving long documents, large codebases, or extended conversations.
Can I use Jamba 1.5 Mini or GPT-o3 for free?
Jamba 1.5 Mini is a paid API model starting at $0.20 per 1M input tokens. GPT-o3 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 GPT-o3?
Jamba 1.5 Mini's arena rank is not yet available, while GPT-o3 holds rank #2. Note that benchmarks don't capture every use case — we recommend testing both models on your specific tasks.
Is Jamba 1.5 Mini or GPT-o3 better for coding?
Jamba 1.5 Mini's primary strength is cost-effective long-context, summarization. GPT-o3's primary strength is advanced reasoning, agentic tasks, research. For coding specifically, arena rank and code-specific benchmarks are the best indicators of performance.