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Jamba 1.5 Mini (SSM)vsGPT-o3

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

Jamba 1.5 Mini (SSM) leads 4/5 categories

Head-to-Head Comparison

MetricJamba 1.5 Mini (SSM)GPT-o3
Provider
Arena Rank
#2
Context Window
256K
200K
Input Pricing
/bin/zsh.20/1M tokens
$2.00/1M tokens
Output Pricing
/bin/zsh.40/1M tokens
$8.00/1M tokens
Parameters
52B (12B active)
Undisclosed
Open Source
Yes
No
Best For
Efficient long-context processing, throughput
Advanced reasoning, agentic tasks, research
Release Date
Mar 28, 2024
Apr 16, 2025

Jamba 1.5 Mini (SSM)

Jamba is AI21 Labs' pioneering hybrid architecture that combines Mamba state-space model layers with transformer attention layers. This novel approach achieves 3x throughput improvement over pure transformer models of equivalent quality. The Jamba architecture represents a significant step toward more efficient AI models that can process long contexts without the quadratic cost of full attention.

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 (SSM) vs GPT-o3

1

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

2

Jamba 1.5 Mini (SSM) supports a larger context window (256K), allowing it to process longer documents in a single request.

3

Jamba 1.5 Mini (SSM) 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 (SSM)

  • +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 efficient long-context processing, throughput
View full Jamba 1.5 Mini (SSM) 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 (SSM) is 16.7x more affordable than GPT-o3. For a typical enterprise workload processing 100M tokens per month:

Jamba 1.5 Mini (SSM) 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 (SSM) wins our head-to-head comparison with 4 out of 5 category wins. It's the stronger choice for efficient long-context processing, throughput, 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 (SSM) or GPT-o3?
In our head-to-head comparison, Jamba 1.5 Mini (SSM) leads in 4 out of 5 categories (arena rank, context window, input pricing, output pricing, and parameters). Jamba 1.5 Mini (SSM) excels at efficient long-context processing, throughput, 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 (SSM) pricing compare to GPT-o3?
Jamba 1.5 Mini (SSM) charges /bin/zsh.20 per 1M input tokens and /bin/zsh.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 (SSM) 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 (SSM) and GPT-o3?
Jamba 1.5 Mini (SSM) supports a 256K token context window, while GPT-o3 supports 200K tokens. Jamba 1.5 Mini (SSM) 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 (SSM) or GPT-o3 for free?
Jamba 1.5 Mini (SSM) is a paid API model starting at /bin/zsh.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 (SSM) or GPT-o3?
Jamba 1.5 Mini (SSM)'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 (SSM) or GPT-o3 better for coding?
Jamba 1.5 Mini (SSM)'s primary strength is efficient long-context processing, throughput. 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.