Model Comparison
Jamba 1.5 Large vs Llama 3.3 70B InstructWhich is better in 2026?
Llama 3.3 70B Instruct significantly outperforms across most benchmarks. Llama 3.3 70B Instruct is 17.5x cheaper per token.
Verdict: Jamba 1.5 Large vs Llama 3.3 70B Instruct — which is better?
Jamba 1.5 Large (by AI21 Labs) and Llama 3.3 70B Instruct (by Meta) 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 Llama 3.3 70B Instruct is better at 3 benchmarks (GPQA, MMLU, MMLU-Pro). Llama 3.3 70B Instruct significantly outperforms across most benchmarks.
On price, Llama 3.3 70B Instruct is roughly 17.5x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
Jamba 1.5 Large also accepts a larger context window (256,000 input tokens), making it the stronger choice for long documents and large codebases.
Choose Jamba 1.5 Large if…
- you process long inputs — it offers a 256,000 token context window
Choose Llama 3.3 70B Instruct if…
- you want the strongest raw capability — it leads on 3 of 3 shared benchmarks
- cost matters — it's about 17.5x cheaper per token
- you want the most recent training data — it shipped Dec 2024
Performance Benchmarks
Comparative analysis across standard metrics
Jamba 1.5 Large outperforms in 0 benchmarks, while Llama 3.3 70B Instruct is better at 3 benchmarks (GPQA, MMLU, MMLU-Pro).
Llama 3.3 70B Instruct 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 10.0x more expensive than Llama 3.3 70B Instruct ($0.20/1M tokens).
For output processing, Jamba 1.5 Large ($8.00/1M tokens) is 40.0x more expensive than Llama 3.3 70B Instruct ($0.20/1M tokens).
In conclusion, Jamba 1.5 Large is more expensive than Llama 3.3 70B Instruct.*
* Using a 3:1 ratio of input to output tokens
Model Size
Parameter count comparison
Jamba 1.5 Large has 328.0B more parameters than Llama 3.3 70B Instruct, making it 468.6% larger.
Context Window
Maximum input and output token capacity
Jamba 1.5 Large accepts 256,000 input tokens compared to Llama 3.3 70B Instruct's 128,000 tokens. Jamba 1.5 Large can generate longer responses up to 256,000 tokens, while Llama 3.3 70B Instruct is limited to 128,000 tokens.
License
Usage and distribution terms
Jamba 1.5 Large is licensed under Jamba Open Model License, while Llama 3.3 70B Instruct uses Llama 3.3 Community License Agreement.
License differences may affect how you can use these models in commercial or open-source projects.
Jamba Open Model License
Open weights
Llama 3.3 Community License Agreement
Open weights
Release Timeline
When each model was launched
Jamba 1.5 Large was released on 2024-08-22, while Llama 3.3 70B Instruct was released on 2024-12-06.
Llama 3.3 70B Instruct is 4 months newer than Jamba 1.5 Large.
Aug 22, 2024
1.8 years ago
Dec 6, 2024
1.5 years ago
3mo newerKnowledge Cutoff
When training data ends
Jamba 1.5 Large has a documented knowledge cutoff of 2024-03-05, while Llama 3.3 70B Instruct'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 Llama 3.3 70B Instruct's cutoff date.
Mar 2024
—
Provider Availability
Jamba 1.5 Large is available from Bedrock, Google. Llama 3.3 70B Instruct is available from Lambda, DeepInfra, Hyperbolic, Groq, Sambanova, Cerebras, Bedrock, Together, Fireworks.
Jamba 1.5 Large
Llama 3.3 70B Instruct
Outputs Comparison
Key Takeaways
Jamba 1.5 Large
View detailsAI21 Labs
Detailed Comparison
| Feature | | |
|---|
FAQ
Common questions about Jamba 1.5 Large vs Llama 3.3 70B Instruct.