Jamba 1.5 Mini vs Llama 3.2 3B Instruct
Jamba 1.5 Mini and Llama 3.2 3B Instruct are closely matched at -5.7 and -6.1 on the LLM Stats Score. Llama 3.2 3B Instruct is 20.0x cheaper per token.
AI21 Labs · Meta · Updated for 2026
Which is better?
Jamba 1.5 Mini and Llama 3.2 3B Instruct are closely matched on the overall LLM Stats Score at -5.7 and -6.1.
The models split the 4 individual benchmarks reported for both models evenly.
On price, Llama 3.2 3B Instruct is roughly 20.0x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
Jamba 1.5 Mini also accepts a larger context window (256,144 input tokens), making it the stronger choice for long documents and large codebases.
Based on current LLM Stats indexes, shared benchmarks, pricing, and model metadata for 2026.
Choose Jamba 1.5 Mini
- you process long inputs — it offers a 256,144 token context window
Choose Llama 3.2 3B Instruct
- cost matters — it's about 20.0x cheaper per token
- you want the most recent training data — it shipped Sep 2024
At a glance
The differences that matter most.
Capability indexes
Additional strengths measured across groups of related public benchmarks
Individual benchmarks
8 reported for Jamba 1.5 Mini · 15 for Llama 3.2 3B Instruct
Jamba 1.5 Mini outperforms in 2 benchmarks (ARC-C, MMLU), while Llama 3.2 3B Instruct is better at 2 benchmarks (GPQA, GSM8k).
Both models are evenly matched across the benchmarks.
Human preference
Blind head-to-head votes and playground preference scores
Pricing Analysis
Price comparison per million tokens
For input processing, Jamba 1.5 Mini ($0.20/1M tokens) is 20.0x more expensive than Llama 3.2 3B Instruct ($0.01/1M tokens).
For output processing, Jamba 1.5 Mini ($0.40/1M tokens) is 20.0x more expensive than Llama 3.2 3B Instruct ($0.02/1M tokens).
In conclusion, Jamba 1.5 Mini is more expensive than Llama 3.2 3B Instruct.*
* Using a 3:1 ratio of input to output tokens
Model Size
Parameter count comparison
Jamba 1.5 Mini has 48.8B more parameters than Llama 3.2 3B Instruct, making it 1519.9% larger.
Context Window
Maximum input and output token capacity
Jamba 1.5 Mini accepts 256,144 input tokens compared to Llama 3.2 3B Instruct's 128,000 tokens. Jamba 1.5 Mini can generate longer responses up to 256,144 tokens, while Llama 3.2 3B Instruct is limited to 128,000 tokens.
License
Usage and distribution terms
Jamba 1.5 Mini is licensed under Jamba Open Model License, while Llama 3.2 3B Instruct uses Llama 3.2 Community License.
License differences may affect how you can use these models in commercial or open-source projects.
Jamba Open Model License
Open weights
Llama 3.2 Community License
Open weights
Release Timeline
When each model was launched
Jamba 1.5 Mini was released on 2024-08-22, while Llama 3.2 3B Instruct was released on 2024-09-25.
Llama 3.2 3B Instruct is 1 month newer than Jamba 1.5 Mini.
Aug 22, 2024
2.1 years ago
Sep 25, 2024
2.0 years ago
1mo newerKnowledge Cutoff
When training data ends
Jamba 1.5 Mini has a documented knowledge cutoff of 2024-03-05, while Llama 3.2 3B Instruct's cutoff date is not specified.
We can confirm Jamba 1.5 Mini's training data extends to 2024-03-05, but cannot make a direct comparison without Llama 3.2 3B Instruct's cutoff date.
Mar 2024
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Provider Availability
Jamba 1.5 Mini is available from Bedrock, Google. Llama 3.2 3B Instruct is available from DeepInfra.
Jamba 1.5 Mini
Llama 3.2 3B Instruct
Outputs Comparison
Judge for yourself.
Run your own prompts against Jamba 1.5 Mini and Llama 3.2 3B Instruct side-by-side, then vote on the output you prefer.
FAQ
Common questions about Jamba 1.5 Mini vs Llama 3.2 3B Instruct.