Model Comparison
Jamba 1.5 Large vs Kimi K3Which is better in 2026?
Kimi K3 significantly outperforms across most benchmarks. Jamba 1.5 Large is 1.7x cheaper per token.
Verdict: Jamba 1.5 Large vs Kimi K3 — which is better?
Jamba 1.5 Large (by AI21 Labs) and Kimi K3 (by Moonshot AI) are two of the AI models people compare most. Here is how they stack up on benchmarks, price and capabilities, and which one to pick in 2026.
Jamba 1.5 Large outperforms in 0 benchmarks, while Kimi K3 is better at 1 benchmark (GPQA). Kimi K3 significantly outperforms across most benchmarks.
On price, Jamba 1.5 Large is roughly 1.7x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
Kimi K3 also accepts a larger context window (1,048,576 input tokens), making it the stronger choice for long documents and large codebases.
Choose Jamba 1.5 Large if…
- cost matters — it's about 1.7x cheaper per token
- you need open weights you can self-host or fine-tune
Choose Kimi K3 if…
- you want the strongest raw capability — it leads on 1 of 1 shared benchmarks
- you process long inputs — it offers a 1,048,576 token context window
- you want the most recent training data — it shipped Jul 2026
Performance Benchmarks
Comparative analysis across standard metrics
Jamba 1.5 Large outperforms in 0 benchmarks, while Kimi K3 is better at 1 benchmark (GPQA).
Kimi K3 significantly outperforms across most benchmarks.
Arena Performance
Human preference votes
Pricing Analysis
Price comparison per million tokens
For input processing, Jamba 1.5 Large ($2.00/1M tokens) is 1.5x cheaper than Kimi K3 ($3.00/1M tokens).
For output processing, Jamba 1.5 Large ($8.00/1M tokens) is 1.9x cheaper than Kimi K3 ($15.00/1M tokens).
In conclusion, Kimi K3 is more expensive than Jamba 1.5 Large.*
* Using a 3:1 ratio of input to output tokens
Model Size
Parameter count comparison
Kimi K3 has 2402.0B more parameters than Jamba 1.5 Large, making it 603.5% larger.
Context Window
Maximum input and output token capacity
Kimi K3 accepts 1,048,576 input tokens compared to Jamba 1.5 Large's 256,000 tokens. Kimi K3 can generate longer responses up to 1,048,576 tokens, while Jamba 1.5 Large is limited to 256,000 tokens.
Input Capabilities
Supported data types and modalities
Kimi K3 supports multimodal inputs, whereas Jamba 1.5 Large does not.
Kimi K3 can handle both text and other forms of data like images, making it suitable for multimodal applications.
Jamba 1.5 Large
Kimi K3
Release Timeline
When each model was launched
Jamba 1.5 Large was released on 2024-08-22, while Kimi K3 was released on 2026-07-16.
Kimi K3 is 23 months newer than Jamba 1.5 Large.
Aug 22, 2024
1.9 years ago
Jul 16, 2026
2 days ago
1.9yr newerKnowledge Cutoff
When training data ends
Jamba 1.5 Large has a documented knowledge cutoff of 2024-03-05, while Kimi K3's cutoff date is not specified.
We can confirm Jamba 1.5 Large's training data extends to 2024-03-05, but cannot make a direct comparison without Kimi K3's cutoff date.
Mar 2024
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Provider Availability
Jamba 1.5 Large is available from Bedrock, Google. Kimi K3 is available from Moonshot AI.
Jamba 1.5 Large
Kimi K3
Outputs Comparison
Key Takeaways
Jamba 1.5 Large
View detailsAI21 Labs
Kimi K3
View detailsMoonshot AI
Detailed Comparison
Interactive Arena
Judge for yourself.
Run your own prompts against Jamba 1.5 Large and Kimi K3 side-by-side, then vote on the output you prefer.
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FAQ
Common questions about Jamba 1.5 Large vs Kimi K3.