Jamba 1.5 LargevsGPT-o3
AI21 Labs vs OpenAI — Side-by-side model comparison
Head-to-Head Comparison
| Metric | Jamba 1.5 Large | GPT-o3 |
|---|---|---|
| Provider | ||
| Arena Rank | — | #2 |
| Context Window | 256K | 200K |
| Input Pricing | $2.00/1M tokens | $2.00/1M tokens |
| Output Pricing | $8.00/1M tokens | $8.00/1M tokens |
| Parameters | 398B (94B active) | Undisclosed |
| Open Source | Yes | No |
| Best For | Long documents, enterprise RAG, analysis | Advanced reasoning, agentic tasks, research |
| Release Date | Aug 22, 2024 | Apr 16, 2025 |
Jamba 1.5 Large
Jamba 1.5 Large, developed by AI21 Labs, is a hybrid model combining the Mamba state-space architecture with traditional Transformer layers, featuring 398 billion total parameters (94 billion active) and a 256K token context window. The novel SSM-Transformer design enables efficient processing of very long sequences while maintaining strong performance on reasoning and generation tasks. The architecture offers better throughput than pure Transformer models at equivalent quality, reducing inference costs for long-context workloads. Priced at $2.00 per million input tokens and $8.00 per million output tokens. As an open-source model, it can be self-hosted for enterprise deployments. Jamba 1.5 Large demonstrates that architectural diversity beyond the dominant Transformer paradigm can yield practical advantages, particularly for applications requiring processing of lengthy legal, scientific, or financial 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 Large vs GPT-o3
Jamba 1.5 Large supports a larger context window (256K), allowing it to process longer documents in a single request.
Jamba 1.5 Large is open-source (free to self-host and fine-tune) while GPT-o3 is proprietary (API-only access).
When to use Jamba 1.5 Large
- +You need to process long documents (256K context)
- +You need to self-host or fine-tune the model
- +Your use case involves long documents, enterprise rag, analysis
When to use GPT-o3
- +You prefer a managed API without infrastructure overhead
- +Your use case involves advanced reasoning, agentic tasks, research
Cost Analysis
Both models have similar pricing. For a typical enterprise workload processing 100M tokens per month:
Jamba 1.5 Large monthly cost
$500
100M tokens/mo (50/50 in/out)
GPT-o3 monthly cost
$500
100M tokens/mo (50/50 in/out)
The Verdict
Jamba 1.5 Large wins our head-to-head comparison with 2 out of 5 category wins. It's the stronger choice for long documents, enterprise rag, analysis, though GPT-o3 holds an edge in advanced reasoning, agentic tasks, research.
Last compared: April 2026 · Data sourced from public benchmarks and official pricing pages