Jamba 1.5 Large vs Llama 4 Maverick
Llama 4 Maverick significantly outperforms across most benchmarks. Llama 4 Maverick is 12.6x cheaper per token.
AI21 Labs · Meta · Updated for 2026
Which is better?
Jamba 1.5 Large outperforms in 0 benchmarks, while Llama 4 Maverick is better at 3 benchmarks (GPQA, MMLU, MMLU-Pro). Llama 4 Maverick significantly outperforms across most benchmarks.
On price, Llama 4 Maverick is roughly 12.6x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
Llama 4 Maverick also accepts a larger context window (1,000,000 input tokens), making it the stronger choice for long documents and large codebases.
Based on current benchmark, pricing, and model metadata for 2026.
Choose Jamba 1.5 Large
- you want predictable pricing at $2.00/M input and $8.00/M output
Choose Llama 4 Maverick
- you want the strongest raw capability — it leads on 3 of 3 shared benchmarks
- cost matters — it's about 12.6x cheaper per token
- you process long inputs — it offers a 1,000,000 token context window
- you want the most recent training data — it shipped Apr 2025
At a glance
The differences that matter most.
Performance Benchmarks
Comparative analysis across standard metrics
Jamba 1.5 Large outperforms in 0 benchmarks, while Llama 4 Maverick is better at 3 benchmarks (GPQA, MMLU, MMLU-Pro).
Llama 4 Maverick significantly outperforms across most benchmarks.
Arena Performance
Playground indexes and blind preference scores
Pricing Analysis
Price comparison per million tokens
For input processing, Jamba 1.5 Large ($2.00/1M tokens) is 11.8x more expensive than Llama 4 Maverick ($0.17/1M tokens).
For output processing, Jamba 1.5 Large ($8.00/1M tokens) is 13.3x more expensive than Llama 4 Maverick ($0.60/1M tokens).
In conclusion, Jamba 1.5 Large is more expensive than Llama 4 Maverick.*
* Using a 3:1 ratio of input to output tokens
Model Size
Parameter count comparison
Llama 4 Maverick has 2.0B more parameters than Jamba 1.5 Large, making it 0.5% larger.
Context Window
Maximum input and output token capacity
Llama 4 Maverick accepts 1,000,000 input tokens compared to Jamba 1.5 Large's 256,000 tokens. Llama 4 Maverick can generate longer responses up to 1,000,000 tokens, while Jamba 1.5 Large is limited to 256,000 tokens.
Input Capabilities
Supported data types and modalities
Llama 4 Maverick supports multimodal inputs, whereas Jamba 1.5 Large does not.
Llama 4 Maverick can handle both text and other forms of data like images, making it suitable for multimodal applications.
Jamba 1.5 Large
Llama 4 Maverick
License
Usage and distribution terms
Jamba 1.5 Large is licensed under Jamba Open Model License, while Llama 4 Maverick uses Llama 4 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 4 Community License Agreement
Open weights
Release Timeline
When each model was launched
Jamba 1.5 Large was released on 2024-08-22, while Llama 4 Maverick was released on 2025-04-05.
Llama 4 Maverick is 8 months newer than Jamba 1.5 Large.
Aug 22, 2024
2.0 years ago
Apr 5, 2025
1.4 years ago
7mo newerKnowledge Cutoff
When training data ends
Jamba 1.5 Large has a documented knowledge cutoff of 2024-03-05, while Llama 4 Maverick'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 4 Maverick's cutoff date.
Mar 2024
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Provider Availability
Jamba 1.5 Large is available from Bedrock, Google. Llama 4 Maverick is available from DeepInfra, Novita, Lambda, Groq, Fireworks, Together, Sambanova.
Jamba 1.5 Large
Llama 4 Maverick
Outputs Comparison
Judge for yourself.
Run your own prompts against Jamba 1.5 Large and Llama 4 Maverick side-by-side, then vote on the output you prefer.
FAQ
Common questions about Jamba 1.5 Large vs Llama 4 Maverick.